WO1990005563A1

WO1990005563A1 - Method and apparatus for laser angioplasty

Info

Publication number: WO1990005563A1
Application number: PCT/US1989/005295
Authority: WO
Inventors: William Wray Macy, Jr.; Michael Douglas House; Douglas Roger Murphy-Chutorian
Original assignee: Mcm Laboratories, Inc.
Priority date: 1988-11-22
Filing date: 1989-11-22
Publication date: 1990-05-31
Also published as: CA2003535A1

Abstract

A system for distinguishing healthy tissue from diseased tissue for purposes of controlling a treatment laser to reopen a channel in blood vessels. The system uses predetermined reference data that define the fluorescent optical characteristics of healthy tissue such as non-atherosclerotic blood vessel wall. The tissue under study is excited to fluorescence by excitation light from a laser (11). The fluorescent light is detected (33) to determine its optical characteristics such as peak intensity, wavelength at the peak and shape of the spectrum. These characteristics are compared to the characteristics of known healthy tissue. If this comparison indicates that the tissue under study is probably diseased, one or more pulses of laser light is guided through a fiber optical waveguide (27) to ablate the diseased tissue. Criteria for determining whether the tissue under treatment is normal may be derived from data generated from abnormal tissue samples.

Description

—METHOD AND APPARATUS FOR LASER ANGIOPLASTY--

Field of the Invention

This invention pertains to the field of laser • angioplasty, and, more particularly, to the field of systems for distinguishing healthy tissue from' plaque. Specifically, the invention concerns methods which use optical characteristics of normal and abnormal tissue to control probe arid fire laser systems. More generally, the invention relates to a treatment and problem-solving method involving a hierarchy of iterative test steps^'.

Background of the Invention

Angiography provides visualization such that the position of a fiber optic probe for use in laser angioplasty or for other uses may be observed. This technique involves the use of radiopaque dyes and x-rays to visualize from x-ray attenuation data the position of a blood vessel obstruction and assists a physician in guid¬ ing a fiber optic probe to an occlusion. One problem with this method results from the use of a fluoroscope to as¬ sist the physician in guiding the optical fiber, which provides only a two-dimensional view of the fiber and the suspected lesion or other tissue. Thus, when the laser is fired, the physician cannot be certain in advance that the fiber is properly aimed at the treatment site, even though this may appear from the fluoroscope to be the case, thus leading to damage of healthy tissue adjacent the treatment area.

Laser pulses have been used both percutaneously (to clear occluded vessels) and intraoperatively to recanalize occluded blood vessels. (Abela, G.S. et al., Laser Angioplasty With Anqioscopic Guidance in Humans, J Am Coll Cardiol (1986) 8_:184, No. 1 at pp. 184-192; Underhill, D.J. et al., High Resolution Anqioscopy: Feasibility, Limitation, and Design Considerations For Laser Coronary Angioplasty, Surg Forum (1985) 36;299) ♦

Several methods for guiding medical laser systems have been described in the prior art. Methods presently in use do not, however, always assure that healthy tissue will not be ablated by a rapidly firing high energy laser, especially methods of distinguishing healthy tissue from plaque including the step of directly butting the end of the fiber optic probe against the obstruction. Furthermore, the physician generally has no means to make a decision adequately and with certainty as to whether the probe is pointed at plaque or healthy tis¬ sue. Since some types of plaque, such as fibrous or calcified plaque, require levels of laser energy to destroy them that are above the energy level that will destroy healthy tissue, any mistake in identifying ap¬ propriate tissue to fire the laser at can result in destruction of healthy tissue such as a blood vessel wall. Perforation of the blood vessel wall is. noted in Underhill et al., supra, as a major clinical obstacle.

One problem with present laser angioplasty systems is that human reaction time is relatively slow, such that when the operator wishes to stop the firing of the laser, unwanted damage is caused by the continued fir¬ ing of the laser even after the operator visually identi¬ fies the need to stop. Thus, a reliable system for automatic laser angioplasty is needed. Another basic problem with all laser angioplasty is how to make the distinction between healthy tissue and plaque or other unwanted obstruction before firing the laser. One approach which has been tried in the prior art to make this distinction is to utilize differences in light reflectivity, i.e., selective light absorption, between healthy tissue and plaque. Preferential absorp¬ tion of laser light by atherosclerotic plaque compared with healthy tissue at selected wavelengths assures more extensive ablation of plaque than healthy tissue by providing better ability to make the decision when and if to fire the laser. For instance, tetracycline has been applied to atherosclerotic plaque to enhance it, for greater reliability in the destruction of atheroma by ultraviolet laser radiation. See Murphy-Chutorian, Douglas, et al. , Selective Absorption of Ultraviolet Laser Energy by Human Atherosclerotic Plaque Treated with Tetra¬ cycline, Am J Cardiol 1985; 55: 1293-1297, which is in¬ corporated herein by reference. See also Prince, M.R. et al. , Preferential Light Absorption in Atheromas In Vitro: Implication For Laser Angioplasty, J Clin Invest (1986) 78:295, in which it is taught that atheromas from cadavers absorb more laser light than normal aorta tissue between 420 and 530 nm. This absorbance was attributable to yel¬ low chromophores consisting primarily of a mix of carotenoids that are known constituents of atheromatous lesions. The reference concludes that preferential absorption of blue laser light by carotenoids in atheromas may permit selective ablation of atheromatous obstruc¬ tions . The reference suggests that selective absorption of some wavelengths of laser light by plaque may be used for distinguishing healthy tissue from unwanted obstruc¬ tions to circumvent the problem of vessel perforations, aneurisms and other forms of inadvertent laser damage to normal tissue lying adjacent to or under atheromas. The reference also suggests that increased absorption proper¬ ties of atheromas may be obtained by administration of chromophores such as beta carotene orally. However, this selective absorption technique does not prevent ablation of healthy tissue with sufficiently high accuracy for widespread commercial use. Further, not all plaques have the same light absorption spectra, and there is some clinical evidence to suggest that the spectrum of light absorption of plaque shifts between the in vivo and in vitro states . Thus, a system tuned for one type of plaque characterized by in vitro studies may not be accurate in making fire decisions for different kinds of plaque or the same type of plaque in an in vivo setting.

Other references teach the administration of chromophores to the patient before treatment to enhance the fluorescent intensity of unwanted tissue to be ablated. , For instance, two related patents owned by the assignee of the present invention, U.S. patent 4,641,650 and its continuation in part_r U.S. patent 4,682,594, teach a probe-and-fire laser system for angioplasty, optionally using an administered atheroma-enhancing agent (such as tetracycline) , which is preferentially absorbed by plaque and which causes diseased tissue to have distinguishing properties (namely, a characteristic fluorescent spectrum) to aid the system in distinguishing normal tissue from diseased tissue for purposes of making treatment laser firing decisions . These two patents provide for automatically monitoring and controlling the output of the laser and for terminating its operation before there is a destruction of healthy tissue around the treatment site. Similarly, U.S. Patent No. 4,336,809 and international Patent No. PCT/US84/00840 teach that the visualization of a tumor can be enhanced with hematoporphyrin dye which fluoresces when illuminated with a particular wavelength of light. Several investigators have noted differences in the fluorescence intensities of atherosclerotic plaque and healthy tissue (Lu, D. et al . , Atherosclerotic Plaque Identification Using Surface Fluorescence, Clin Res (1986) _34_:630A (Abstract) (wide band xenon source excitation of cadaver thoracic atherosclerotic aortas at UV 340-380 nm, blue 450-490 nm and green 530-560 nm with fluorescent intensity scanned from 350 to 670 nm showing blue fluorescence having a peak at 540 nm and a weak shoulder at 580_, nm with fluorescence intensity noted to be greater in normal tissue regions than in diseased regions); Leon, M. et al . , Human Arterial Surface Fluorescence: Atherosclerotic Identification and Effects of laser

Atheroma Ablation, J Am Plaque^' Coll Card (published July, 1988); Sartori, M. et al . , Estimation of Arterial Wail thickness and Detection of Atherosis by Laser Induced Argon Fluorescence, Circ (1986-) 7_6_^:IV-408) . At least one researcher has noted the difference in shape between fluorescence spectra of normal tissue versus atherosclerotic tissue. (Kittrell et al . , Diagnosis of Fibrous Arterial Atherosclerosis Using Fluorescence, Ap¬ plied Optics, Vol. 24, No. 15, at pp. 2280-2281 (1985)) . Thresholds for tissue spectra are discussed as ratios or products of ratios published in the Abela and Underhill articles referenced above and in the article by Deckelbaum et al., Clinical Res, Vol. 34:292A (1986) . The tissue spectra on which these analyses are "based are dissimilar from those obtained _in vivo.

Some methods which distinguish plaque from healthy tissue use ratios of intensities of fluorescent emission spectra excited between 450 nm and 490 nm (Kittrell, C. et al . , supra; Sartori, M. et al . , Autofluorescence Maps of Human Arteries, J Am Coll Cardiol (1986) 2^: 07A; Sartori, M. et al . , supra; Casale, P.N. et al . , Improved Criteria for Detecting Atherosclerotic Plaque by Fluorescence Spectroscopy_f Circ (1987) 76 IV- 524) (suggesting excitation at 337 nm with ratio taken at 460/385 nm as the best two wavelengths to use) ; Deckelbaum, L.I. et al. , Discrimination of Normal and Atherosclerotic Aorta. By Laser Induced Fluorescence, Clin Res (1986), Vol. 34, No. 2 at 292A) . A difficulty with ratioing intensities of normal tissue spectra to unwanted substance spectra at a few wavelengths is that the optical characteristics of unwanted substances can vary significantly from substance to substance and between in vitro and in vivo states. That is, different plaques have different fluorescence spectrum shapes. Methods based on a few ratios are not able to differentiate healthy tissue from all unwanted substances that may be found at a diseased site or in an arterial obstruction with suf¬ ficient accuracy to risk possibly damaging healthy tissue. Thus, although fluorescence intensities can assist in the guidance of a laser system and in the diagnosis of the tissue, they lack the necessary consistency and accuracy to be used alone for treatment laser firing decisions.

Other references which teach the use of laser systems within the body cavity do not distinguish between healthy tissue and unwanted substances before firing the treatment laser. European Patent 86302603.5 teaches the administration before treatment of a chromophore which is preferentially absorbed by plaque. This chromophore absorbs laser light. Therefore, laser energy ablates plaque more readily than healthy tissue. U.S. Patent Nos. 3,858,577 and 4,273,109 are fiber optic systems which deliver laser light to an internal diseased site.

Other references teach the use of laser systems which operate outside of the body cavity. U.S. Patent No. 4,438,765 teaches the use of a medical device which fires a laser to fuse the retina. This device senses eye motion and only fires the laser when the eye is not moving. U.S. Patent No. 4,316,467 teaches the use of a laser system which removes pigmented tissue from skin. The laser is fired only when a photodetector in the system senses the characteristic color of pigmented tissue.

U.S. patent 4,718,417 describes a method of diagnosis of the type of tissue in an artery using laser light at about 480 nm. Excitation of in vitro tissue produces spectra which have peaks at 550 nm and 600 nm, and a valley at 580 nm. These features result from absorption by hemoglobin in the tissue. Recent collabora¬ tive studies carried out by MCM Laboratories and the National Institutes of Health indicate that hemoglobin absorption does not occur in in vivo tissue or in vitro tissue which is less than several hours old. Therefore, the method described in U.S. patent 4 , 718, 417 will discriminate normal tissue from atheromatous tissue in in vitro samples more than several hours old, but may not work well in living patients.

Although there is a substantial amount of exist¬ ing technology for laser. surgery, a method is needed which distinguishes healthy tissue from substantially all unwanted substances which may be found at a particular site inside the body cavity, with or without the necessity of administering a chromophore before treatment, and which minimizes the risk of damage to healthy tissue with a higher degree of accuracy than available from most exist¬ ing technology.

Summary of the Invention

It is accordingly a general object of the inven¬ tion to provide an improved method of distinguishing unwanted substances from healthy tissue within the body cavity so that laser energy will be directed at only the unwanted substance. It is a more specific object of the invention to provide a method of distinguishing healthy tissue from unwanted substances without requiring administration of chromophores before treatment. In addition, due to the possible occurrence of several types of unwanted substances at a site, a specific object of the invention is to distinguish substantially all unwanted substances whose optical signal differs from that of healthy tissue.

It is another particular object of this inven¬ tion to provide a method of controlling the firing of a laser for treatment of diseased areas wherein optical characteristics of diseased areas are distinguished from those of healthy areas, such as by distinguishing the respective fluorescent spectra or atherosclerotic plaque from the spectra of healthy arterial walls .

It is a specific objective of the invention that a computer-implemented process of distinguishing healthy from diseased tissue be used wherein the details of the form of the method shall be chosen so as to give the best performance in distinguishing unwanted substances from healthy tissues.

It is a specific objective of the invention that the calculations made by the algorithm be completed in a period of time which is shorter than the period of time in which the distal end of the fiber moves to a different position.

It is another object of the ^'invention to describe the process of controlling laser firing to safely clear occluded arteries by comparing incoming optical signals from said arteries to standard reference signals and generating a fire/no fire signal as appropriate to said object.

In order to implement the invention, there is contemplated electrooptical means such that incoming opti¬ cal signals (e.g., electromagnetic radiation such as light) to said means are converted into an outgoing electrical or optical signal which can trigger a treatment means (e.g., a laser) to treat or avoid treating the area of interest. It is a general feature of the invention that the incoming optical signals are complex and multi¬ form and that the electrooptical means converts said signals into simpler representations which effects ap¬ propriate and safe treatment of the diseased areas.

It is a further object to describe a method of determining control signals by first determining either standard normal curves or a range of values of specific intensities (relative or absolute) for a specific wavelength or range of wavelengths of electromagnetic radiation (e.g., light) from nondiseased substances likely to be encountered by a fiber cable means (e.g., blood, air, healthy internal blood vessel surfaces and vessel walls) and similarly for diseased substances (e.g., thrombus, atheroma, etc.) by obtaining adequate numbers of specimens of each substance and then calculating threshold levels which serve as criteria to identify or distinguish these nondiseased substances and/or these diseased substances and/or combinations of substances from each other.

It is a further object that said threshold levels are written into the control system and electrooptically connected to incoming light from said substances either inherent to or induced from said substances (e.g., by photoexcitation with a light source to cause tissue fluorescence) in order to react ap¬ propriately to trigger or inhibit an electrical and/or optical signal to a treatment means intended to remove diseased substances (e.g., laser light to remove atherosclerotic plaque) .

According to the teachings of the invention a treatment laser and a diagnostic laser have their light outputs coupled to a fiber optic probe catheter (hereafter the catheter) . A computer with associated interface circuitry controls the diagnostic laser to cause it to send one or more pulses of excitation light to the site in front of the current position of the catheter. The fluorescence spectrum emitted from the site is then compared to a composite normal tissue fluorescence spectrum in several respects in order to make a fire deci¬ sion for control of the treatment laser.

Three types of information are extracted by the computer in the analysis of returned light and in the comparison to the reference normal tissue spectrum. These three tests are: a comparison of the relative shapes of the return light spectrum and the reference normal tissue spectrum; a comparison of the relative wavelength posi¬ tions of the respective peak intensities in the return light spectrum and the reference normal tissue spectrum; and the relative intensity of the fluorescent return light versus the intensity of the reference normal tissue spectrum. All three tests must indicate the catheter is pointed at plaque before the treatment laser will be fired.

The method of the invention uses a signal processing technique which considers the optical signal of normal tissue as a reference. It is recognized that there are several mathematical forms for signal processing techniques which compare a reference signal with a signal obtained by a sensor system. The mathematical form chosen is that found to give best performance from analysis of optical signal data.

In order to implement the method of invention it is necessary to determine the composite healthy tissue reference spectrum from signals at many healthy tissue sites from many different donors. The composite normal tissue fluorescent spectrum is mathematically derived by obtaining the individual fluorescent spectra of healthy tissue from multiple donors. Each spectrum is then normalized and shifted so that the intensity peaks of the individual spectra all occur at the same wavelength and have the same intensity. The wavelength of the peak for each normal tissue spectrum is found by fitting a parabola to the normal tissue fluorescent spectrum from each source. The intensity at that peak wavelength is then

10 normalized to equal the intensity at the peak of the composite healthy tissue spectrum. The individual spectra are then aligned for best fit with the composite by a shifting process that mathematically amounts to finding the smallest least squares residual for a series of dif¬

15 ferent wavelength shifts. The shift that results in the best fit for a particular spectrum is then used to shift all intensity points on that spectrum to fit the composite. The intensity at each wavelength for all the shifted curves is then averaged to determine the shape of

20 the composite normal tissue 'spectrum.

During this process -of mathematically deriving the composite healthy tissue reference spectrum, the range of peak intensity wavelengths for normal tissue is recorded. In other words the maximum wavelength of the

25 peak and the minimum wavelength of the peak of any of the normal tissue spectra is recorded for purposes of perform¬ ing the peak position test mentioned above.

After the composite healthy tissue spectrum is mathematically computed, the relative intensity test

30. thresholds are determined before treatment begins . This test provides information to distinguish plaque from healthy tissue based upon the fact that normal tissue has a higher fluorescent intensity by a factor of two than most kinds of plaque. This test cannot be used alone

35 however because some types of plaque such as calcified plaque fluoresce as brightly as normal tissue. To determine these thresholds, the fiber is moved close to (and may be abutted against) tissue such as known plaque and an excitation light pulse is emitted by the diagnostic laser. A lower limit intensity threshold is then set to prevent the treatment laser from being fired at noise. The higher limit intensity threshold is then set by recording a value approximately two times as intense as the fluorescent return from the plaque, since it is known that normal tissue usually fluoresces more than two times as brightly as plaque. The actual upper limit is set ac-. cording to actual readings of intensity values from normal and diseased tissue taken during analysis of diagnostic data. Accuracy can be improved if the diagnostic data for relative intensity (from which the normal tissue reference spectrum is' computed) comes from the very patient to be operated upon.

Finally, a curve shape threshold is determined by which the shapes of the return light spectrum and the healthy tissue reference spectrum may be compared. This curve shape threshold is determined by finding the great¬ est least squares residual from all the individual healthy tissue- reference spectra used to generate the composite and using this largest residual as an indicator of the worst fit between a normal tissue spectrum and the composite. This largest residual is used as the curve shape threshold to make sure that normal tissue is not mistaken for plaque.

The data and thresholds so collected are now ready for use by the computer in controlling a treatment laser. In the preferred embodiment, 50 cycles of il¬ luminating the operation situs with pulses from the diagnostic excitation laser and reading the fluorescent return light and making a fire decision are performed before the fiber is moved and the system is readjusted. After each excitation pulse, the return light is analyzed by the three tests mentioned above. First, the intensity of the return light is compared to the maximum and minimum intensity thresholds. If the intensity is within the range defined by these two threshold, the first test is passed, indicating that the fiber may be pointed at plaque. Next, the wavelength of the peak intensity of the return light is determined and a determination is made as to whether this wavelength is within or outside the range of wavelengths of peaks for normal tissue. If it is outside the range of wavelengths in which the peaks of normal tissue spectra were found, then the second test is passed and the probability that the fiber is pointed at plaque rises. Finally, the shape of the return spectrum is compared to the shape of the reference healthy tissue spectrum. This is done by normalizing the return spectrum and computing the fit to the reference spectrum using the least squares residual technique. The maximum least squares residual is then compared to the curve shape threshold. If the fit is worse than the fit of any of the individual healthy tissue spectra to the composite refer¬ ence 'spectrum computed from these individual healthy tis¬ sue spectra, then the conclusion is drawn that the fiber is pointed at plaque, and the computer commands the treat- ent laser to fire a pulse through the fiber. If any of the tests indicates that the fiber may not be pointed at plaque, then the treatment laser is not fired and other tests are conducted, as discussed below.

It is also important to obtain signals from ab- normal substances. The deviations of individual healthy tissue signals from the reference signal are used to select the thresholds for firing the treatment laser. The deviation of individual signals from unwanted signals are used to select details of the mathematical form of the method of the invention. The method of the invention in a broader ap¬ plication comprises steps for clinical diagnosis and treatment of a variety of types of medical or other tasks where action must be taken on the basis of data generated from the patient or object to be acted upon. This method includes the development of hardware for the task in ques¬ tion; the collection of diagnostic data; the selection of techniques to solve the problem in question; the develop¬ 0 ment of processes to implement the chosen techniques; the testing- of the processes and revision thereof if neces_¬ sary; and compensation for changes in hardware characteristics and tissue types.

5 Brief Description of the Drawings

Figure 1 is a block diagram of the apparatus in which the teachings of the invention are employed.

Figure 1A is a diagram of a linear array of pixels generated by the apparatus of Figure 1. 0 Figure 2 is an illustration of the composite reference spectrum generation process.

Figure 2A shows a fomula used by the method of Figure 2.

Figure 3 is a flow chart of the process of

25 generating the composite reference spectrum.

Figure 4 is a flow chart of the process of mak¬ ing the fire decision for the treatment laser given the characteristics of the return fluorescent light.

Fig. 5 is a plot showing a typical optical

30. signal of healthy tissue and an optical signal of healthy tissue with hemoglobin absorption on the left side of the curve.

Figure 6 is a graph of a curve fit between the composite reference spectrum and a normalized fluorescent

35 return light spectrum. Figure 7 is a flow chart of the preferred embodiment of the treatment process according to the teachings of the invention.

Figure 8 is a flow chart of an alternative embodiment of the method of the invention, incorporating a series of hierarchical, iterative, automatic decision- making steps.

Figure 9 is a flow chart of a generalized problem-solving method based upon the method of Figure 8.

Figure 10 shows a formula utilized by the method of Figure 8.

Figure 11 is a block diagram showing an alterna¬ tive to the embodiment of Figure 1.

Figure 12 is a block diagram showing an alterna¬ tive to the embodiment of Figure 1.

Detailed Description of the Preferred Embodiments

Figure 1 is a block diagram of a typical system in which the teachings of the invention may be employed. The description immediately below will be with reference to Figures 1-7, following which is a detailed description of a preferred embodiment of the invention relating to the flow charts^' of Figures 8 and 9.

The exact details of the optics- shown in Figure 1 are not critical to the invention, and any conventional optics to selectively couple the outputs of two lasers to a single fiber and to coupled light returning from the patient through the fiber to a spectrometer will suffice for purposes of practicing the invention. The excitation laser 11 has a shutter 10 which is controlled by a computer 13 via a control bus 15. The laser 11 may be, for instance, the HeCd laser made by Omnichrome of Chino, California. The control bus 15 carries signals to control the shutter 10 so that excitation light from the laser 11 is allowed to be coupled into the fiber only during the period prior to firing a treatment laser 17 when the fir¬ ing decision is being made by the computer 13. The treat¬ ment laser may be the flash lamp pumped dye laser avail¬ able from Candela of Wayland, Massachusetts.

The treatment laser 17 includes a shutter 34 or some other mechanism that can be controlled by the computer 13 via a control bus 19 so that a treatment pulse to destroy obstruction material may be generated under the control of the computer.

The excitation laser 11 and the treatment laser 17 are coupled through a beam splitter 21, a lens 23, and a holed mirror 25 into a fiber optical waveguide which has been threaded by angiography to the position of an obstruction. As will become clear from the discussion below, the excitation laser is pulsed by the computer 13 to cause a pulse of excitation light at 325 nm to il¬ luminate the tissue in front of the fiber inside the blood vessel being operated upon. The material in front of the fiber 27 emits fluorescent light which is guided back by the fiber, to then exit the fiber and impinge upon the holed mirror 25. This light is reflected by the holed mirror through a lens 29 to a spectrometer 31 which includes a diffraction grating. This diffraction grating spreads the various wavelengths of fluorescent light out at different angles to impinge upon various pixels of a linear photosensitive array in a detector 33, such as the array of pixels 1-512 shown in Figure 1A. The spectrometer 31 and detector may be such as those made by Princeton Applied Research (EG&G) of Princeton, New Jersey. The detector 33 detects the intensity of all light in a- predetermined frequency band, which in the preferred embodiment is the band from 375 to 650 nm. Each of the pixels in the detector 33 may be individually read by the computer 13 through conventional interface circuitry. An operator interfaces with the computer 13 through a terminal 35, through which commands regarding the number of cycles between readjustments, the minimum and maximum thresholds of intensity, and the treatment laser firing rate in Hz may be issued to the computer 13.

Although the description below of the embodiments of the invention will be by reference to return light which is fluoresced by the treatment tissue of the patient, such return light may also be generated by reflectance of the irradiating laser beams. Thus, the method should be understood also to encompass the alterna¬ tive embodiments wherein such reflected return light is used, in which case the details of analysis of the return spectra will need to be adjusted.

The method of the invention as described here¬ after is implemented with the apparatus shown in Figure 1. However, alternative apparatus may also be used to imple¬ ment the method, such as that shown in Figure 11, which shows an alternative to the embodiment of Figure 1 wherein the treatment laser 17 also acts as a diagnostic or excitation laser, thus eliminating the second laser 11 which was used in the configuration of Figure 1. This also eliminates the need for the beam splitter 21. In this embodiment, the laser 17 is energized, and sends a beam or pulse to the treatment site of the patient, thereby ablating a portion of tissue. The tissue fluoresces or reflects due to the treatment light, and the return light is then received by the detector and analyzed in the same manner as if two separate lasers 11 and 17 were used. The analysis of the return light is then used to decide whether to fire the laser again at the site. For a description of a system utilizing a single-laser apparatus, see Laufer, Guenther, et al. , Excimer Laser- Induced Simultaneous Ablation and Spectral Identification of Normal and Atherosclerotic Arterial Tissue Layers, Circulation 1988; 78: 1031-1039, which is incorporated herein by reference.

The operation of the above system will be described utilizing the example of distinguishing atheromatous plaque -from healthy tissue by their fluorescent spectra from excitation at 325 nm and emission between 375 nm and 650 nm. Before the system can operate to make distinctions based upon return fluorescent light, two things must be established: first, a healthy-tissue, normal reference spectrum; and secondly, certain thresholds for use in comparing the spectrum of return fluorescent light to the reference healthy tissue spectrum. To do this it is necessary to obtain diagnostic optical signals from representative samples of normal tis¬ sue and plaque.

In order to obtain such signals, the operative end of the optical fiber may be placed on or adjacent various arterial specimens such as intima, media, atheroma, graft occlusions, thrombus, adventitia and' blood, as well as in air. This diagnostic data is col¬ lected before any operation is performed by illuminating healthy tissue from multiple human sources with excitation light from the diagnostic laser and collecting data regarding the intensity of the return fluorescent light at each of a plurality of wavelengths. Further, diagnostic plaque fluorescent intensity data is also obtained by il¬ luminating known atherosclerotic tis^'sue, i.e., known plaque, with excitation light at the same wavelength as will be used in the actual operation. Usually, this proc¬ ess of collecting diagnostic data is done on both healthy and atherosclerotic tissue taken from in vivo measure¬ ments, but improvements in accuracy can be obtained by taking these readings on the actual patient to be operated upon. The diagnostic plaque fluorescent intensity data from cadaver sources is supplemented during the operation by absolute plaque fluorescent intensity data from the patient being operated upon for purposes of adjusting the maximum intensity threshold value to be described below. The purpose of collection of the diagnostic data and the processing thereof to be described below is to provide healthy tissue reference values. These values are used to compare the actual return light from the situs of the operation for purposes of deciding whether the fiber is pointed at healthy tissue or plaque. The manner in which these decisions are made will be described in more detail below.

Either a continuous wave or pulse of light may be used (at, e.g., 325 nm or 337 nm) from a laser, and transmitted through an optical fiber to a light detecting system, which may comprise the spectrometer 31 in conjunc¬ tion with the detector 33, discussed above. Light intensities (e.g. photon counts) of the returning light may be divided into discrete wavelength ranges (e.g. every 1 nm) , and a spectral curve may be generated for each specimen tested,_, i.e. inti a, media, etc. The, spectra are stored for later comparison with spectra generated at a later time from in vivo or other specimens, in a manner to be described in detail below. Details of generating such spectra are discussed below.

Thus, the shape of the fluorescent intensity emission spectrum versus* wavelength of normal tissue is preferably generated by constructing a composite of many normal spectra. The composite spectrum is found by super¬ imposing multiple normal tissue spectra and then averaging them. This process is illustrated in Figure 2 (and is carried out according to the formula of Figure 2A) , and the method is represented by the flow chart of Figure 3. Figure 2 shows the process of normalizing and shifting one normal tissue fluorescent spectra to a reference spectrum, which may itself be a composite of several or many spectra.

In one embodiment of the invention, a composite spectrum is generated for plaque or other abnormal tissue in the same manner as the normal-tissue composite spectrum is generated. In this embodiment, the test tissue spectrum is compared to both the normal and abnormal composite spectra (in a manner to be described below relative to the normal tissue spectrum) , thus increasing the reliability of the abnormal tissue identification.

Thus, Figure 3 is a flow chart showing a method of the invention for calculating the composite healthy tissue reference spectrum and setting the various thresholds. The first step in this procedure of generat¬ ing a composite is to first generate a reference spectrum for healthy tissue and fit the spectrum to a parabola. The peak may be normalized by dividing all the values of this first reference spectrum by the peak value, thereby preserving the shape of the spectrum while forcing the peak value to equal 1.

Another spectrum is then generated for the next sample of healthy tissue, and this is also fitted to a parabola, as represented by step 42 of Figure 3. The curve fitting process is carried out by a least squares analysis or other standard curve-fitting method, and identifies in reliable fashion the wavelength at which the peak intensity of the curve 40 occurs. This process of curve fitting to find the peak intensity is represented by step 42 of Figure 3. The process of fitting a parabola to the spectrum 40 finds the wavelength of peak intensity more accurately than searching for the peak intensity on the curve, since noise spikes on the curve could lead to a false answer in the latter case by erroneously indicating a highest value which is noise and not part of the actual fluorescence spectrum. This next spectrum is also normalized so that the peak value is 1, as with the first (reference) spectrum of the unknown test tissue of a patient at its peak so that it will have the same intensity at its peak as that of the partially complete composite spectrum to which it will be added. Other methods of normalization may be used, so long as the same normalization method is used for all the spectra. In this embodiment, the posi¬ tions of the peaks are of greater importance than the peaks ' absolute magnitudes .

In Figure 2, the spectrum 40 is thus a normal tissue fluorescent spectrum taken by exciting healthy tis¬ sue from some human source such as a cadaver. However, in vivo tissue is preferably used to generate the normal composite spectrum, because in vitro tissue becomes pigmented very quickly after death, which skews the spectra taken from it. If relatively old tissue is used (such as more than a few hours), then compensation must be made for the spectral skewing, which may be difficult to implement and lead to unreliable results. Indeed, a large increase in accuracy in making firing decisions for the treatment laser can be obtained if the healthy tissue spectra from which the composite is generated are taken from the patient to be operated upon prior to the operation.

The process of normalizing the curve 40 is represented by steps 44 and 48 in Figure 3. The first step in doing this is to note the intensity of the curve 40 at its peak as symbolized by step 44. In the case of spectrum 40, the peak intensity I at wavelength lambda. is noted. The peak intensity I for the first reference spectrum 46 (which for later steps will be a composite of numerous spectra) is then noted, and all intensity values on the spectrum 40 are multiplied by the fraction I EF^¹! to normalize the curve 40 as symbolized by step 48 in Figure 3. This results in the curve 52 in Figure 2.

Note that the ratio used in step 48 uses the term I . This term refers to the intensity at the peak of the particular healthy tissue spectrum being operated upon at the time since the same step 48 will be used to operate upon all the healthy tissue spectra that go into making up the composite reference spectrum 46. The same process of curve fitting for peak determination and normalization is carried out on each healthy tissue spectrum. The first healthy tissue spectrum that is operated upon becomes the initial composite reference spectrum. Thereafter, subsequent healthy tissue spectra are normalized and fit¬ ted to this first healthy tissue spectrum until all the healthy tissue spectra have been so processed.

The individual healthy tissue spectrum is then aligned with the composite spectrum by finding the least squares residual of the individual spectrum and the composite spectrum, by use of the formula shown in Figure 2A.' This process essentially amounts to -shifting the spectrum 52 by several discrete steps j of wavelength and then, for each j, taking the sum of the squares of the differences between the curve 52 as shifted and the composite waveform for all wavelengths i (wavelengths will be referred to as either i or lambda interchangeably) . This process determines the best fit by finding the j where the sum of the squares of the ^"differences is at a minimum. In the presently-described embodiment, the proc¬ ess is carried out with the equation:

(1) R(j)= sum for all i of ( I( j+i)-C(i) )

where:

C(i) = the composite reference healthy tissue function comprising a spectrum of fluorescent intensity values at each of a plurality of wavelengths i (i = lambda in Figure 2 ) ;

I(j+i) = the individual healthy tissue spectrum component being averaged into the composite reference spectrum expressed in terms of a series of fluorescent intensity values at a plurality of wavelengths (j+i); j = any of a series of offset wavelengths, each of which results in a least squares residual number R(j) when i is cycled through all its possible values and the expression of Equation 1 is evaluated for all i and that particular j ; i = the wavelength lambda at which to evaluate C(i) and I (j+i) with the current j to determine the intensity values.

Thus, C(i) represents the intensity of the composite spectrum at pixel i. Pixel i refers to the intensity at a particular wavelength by virtue of the operation of the diffraction grating described above in spreading out the spectrum so that different wavelengths fall on different pixels of the- spectrometer. I(i+j) represents the^' intensity of the individual spectrum at pixel i+j, where j is a parameter which introduces a shift of I(i) . The value of j is varied to find a minimum value of the least squares residual, R(j) . The superposition of the individual spectrum and the composite (reference) spectrum is optimized at the minimum value of R(j) . The values of the first reference spectrum.and those of the next-generated (and now standardized, i.e. normalized and shifted) spectrum are then summed for each pixel.

As indicated by step 54A in Figure 3, the above procedure is carried out on numerous healthy tissue spectra, each time utilizing the first reference spectrum as the standardizing spectrum, and each time summing the succeeding standardized spectra with the sum of the fore¬ going spectra. Finally, the sum of all the spectra is divided by the number of spectra added, thus generating a composite spectrum.

This process may be repeated as often as desired, as indicated in step 54C, each time using the previously-generated composite spectrum as the reference spectrum for the next cycle. The use of step 54C lessens any weight which may be given to the resulting composite spectrum by the use of the first reference spectrum since, as described above, the first reference spectrum is used as standard with respect to which the remaining spectra' are shifted by the least squares method. Thus, repeating the above steps, each time using the newly-generated composite spectrum as the reference spectrum for the next sequence (using the same spectra data again in the subsequent sequence of steps) minimizes the artificial weighting effect.

Step 50 shows a step relating to determination of a range of peak positions for healthy tissue. In this step, the wavelength of the peak of each healthy tissue spectrum generated, such, as spectrum 40, is compared to the range of wavelengths in which healthy tissue peaks oc¬ curred for purposes of updating the range, if necessary. The purpose of this is to determine the range of wavelengths in which peaks for healthy tissue spectrum occurred for purposes of comparing against the wavelength of the peak of the return light from the situs of the operation when actual patient tissue^" is treated, to aid in making the determination of whether the fiber is pointed at healthy tissue or diseased tissue. This step may be carried out after the composite spectrum is generated, as indicated in Figure 3, or it may be carried out as the composite spectrum is being generated, in which case it would come between steps 48 and 54. In the latter case, the first two healthy tissue spectra that are analyzed initially set the bounds of the healthy peak range. Thereafter, the wavelength of each healthy tissue peak is compared to the current maximum wavelength and minimum wavelength range limits. If the wavelength is less than the minimum wavelength in the current range, the range limit on the minimum wavelength end is updated with the new, lower wavelength. Similar updating of the maximum range limit occurs if the wavelength of the peak exceeds the current range limit on the maximum end.

Thresholds for various tests are found after normal tissue is characterized by generation of the composite healthy tissue reference spectrum. As noted earlier, one of the types of tests to be performed in mak¬ ing the firing decision is a determination as to whether the intensity of the return light from the tissue at which the fiber is pointed is within a certain, intensity range. Since it is known that normal tissue intensity for return light is generally at least twice as high as return light from many types of plaque, the range of intensity values to which the return light is compared is set so that if the intensity of return light is in this range-, the fiber is probably pointed at plaque. This test cannot be used alone, however, since some plaques such as calcified plaque is almost as bright as normal tissue. The range of intensity values is set with a minimum intensity threshold and a maximum intensity threshold. The minimum intensity threshold is the minimum intensity required to give adequate signal-tσ-noise ratio. This threshold is used to ensure that the treatment laser is not fired when noise is causing the apparent return light. .This process is symbolized by step 56 in Figure 3. The computer retains the intensity data from the healthy tissue spectra used to compute the composite reference spectrum. This intensity data is examined to set the minimum intensity threshold.

The maximum intensity threshold is determined from relative intensity ratios of plaque and healthy tis- sue found during analysis of diagnostic data and the absolute intensity of plaque measured during surgery. This process is symbolized by step 58 in Figure 3. The absolute intensity data is collected by the computer and used to readjust the maximum intensity threshold, if necessary, during the interval between cycle groups. The normal mode of operation of the instrument is in cycle groups of 50 cycles, wherein each cycle is characterized by illumination of the tissue in front of the fiber by a pulse from the excitation laser followed by analysis of the return light and a decision to fire or not to fire the treatment laser. After 50 such cycles, the system may be readjusted, including adjustment of the maximum intensity threshold, and 50 more cycles are run.

The curve position thresholds are used to set a range of a maximum wavelength and a minimum wavelength. These thresholds define a wavelength range, such that all the peaks of the healthy tissue spectra used to generate the composite fall within this range.^* This is determined by the upper and lower values of wavelengths of the peaks of the healthy tissue fluorescent- intensity emission spectrum versus wavelength.

The curve shape threshold is determined by the greatest least squares residual R(j), computed from the spectrom taken from a representative sample of normal tis¬ sue and from the composite healthy tissue reference spectrum. The greatest residual is used as a threshold so the normal tissue will not be mistaken for plaque. That is, the greatest minimum R(j) of all the minimum R(j)'s computed during the process of computing the composite is stored as the curve shape threshold. This threshold will later be compared to the minimum R(j) computed for the return light as compared to the composite as part of the analysis of the return light in making the fire decision for the treatment laser. In some embodiments, an additional step 59 is performed to determine a "heme stain" threshold. The ef¬ fects of heme stain on normal tissue spectra is explained in more detail below, but suffice it to 'say that the pres¬ ence of heme stain can lead to mistaking normal heme stain tissue for plaque. The determination of the heme stain threshold step 59 symbolizes the process of determining the intensity ratio between absorption at 425 nm and the intensity at the peak for both heme-stained normal tissue and non-heme-stained normal tissue. These two ratios are then compared by subtraction or division or some other mathematical relationship to determine the heme stain threshold. The exact mathematical manner of comparison is not important as long as the same mathematical method of comparison is used during actual treatment to compare similar ratios to those described above for purposes of comparing to the heme threshold. More detail on the calculation of intensity ratios during treatment is given below in connection with discussion of Figures 5-7.

Following the collection of diagnostic data, optical signals of normal tissue ^'are analyzed by consider¬ ing their intensities, the fluorescent intensity emission spectrum versus wavelength locations, and curve shapes. Aspects of these features used to characterize normal tis¬ sue will be discussed, and then the way they are used by the system of the invention will be described.

Diagnostic data from clinical studies show that healthy tissue does not have a characteristic absolute intensity which can be used to control a laser system because some plaques are almost as bright as healthy tis¬ sue while others are much darker. However, the emission intensity of normal tissue is more than twice as great as that of most unwanted substances found in the vicinity of normal tissue sites which have been probed. Diagnostic data from clinical studies also show that for normal tissue, the range over which the wavelength positions of the peaks of fluorescent intensity emission spectra occur is less than that of unwanted substances in arteries. As noted above, the positions of these peaks is obtained by fitting a parabola to the emis¬ sion curve. This is a more reliable method of determining the peak than the maximum intensity. The fluorescent intensity emission spectrum versus wavelength has a relatively flat top so a small noise spike in this region could give a maximum intensity that is not representative of the curve's peak position, if parabola fitting were not used.

Figure 4 shows the method of the invention for probe-and-fire laser treatment after the thresholds have been found. Step 60 represents the process of causing the excitation laser to emit a pulse of excitation light at 325 nm and reading the fluorescent intensity spectrum of the tissue at the distal end of the fiber by reading the output of all pixels of the detector in Figure 1 to obtain the intensity of the return light at each wavelength. This intensity data is stored in the CPU's associated memory for analysis by subsequent steps.

In step 62, the peak intensity of the return light is found by any reliable method, and the intensity and wavelength at the peak are stored for future use. In the preferred embodiment, the peak s found by curve fit¬ ting a parabola to the return light spectrum.

Next, the intensity at the peak of the return light is compared with the minimum intensity threshold in step 64. If the peak intensity is less than the minimum threshold, control returns to step 60, and the first cycle is over. If the peak intensity is greater than the minimum threshold, processing continues to other steps since the intensity indicates that an adequate signal to noise ratio exists. Step 66 represents the process of comparing the peak intensity, of the return light to the maximum intensity threshold, the threshold having been determined by the pre-operation analysis of diagnostic data. During calibration, about 50 spectra are preferably taken for plaque from the patient being operated upon, and the maximum intensity threshold is then established by taking the average of the peak intensities of these spectra, and doubling this average.

If the peak intensity of the return light is greater than the maximum intensity threshold, the fiber may be pointed at healthy tissue, so no firing of the treatment laser will be allowed, and this cycle is terminated by returning processing to step 60. If the peak intensity of the return light is less than the maximum threshold, it is more likely that the fiber is pointed at plague or some unwanted obstruction such as a blood clot. Step 66, the maximum intensity test, tests if the intensity of the return light is significantly higher than the plaque , absolute, intensity measured during surgery prior to the probe-and-fire laser treatment. If the intensity has increased significantly so that it exceeds the maximum intensity threshold, the laser -will not be fired and another spectrum will be obtained for analysis by the sensing system as symbolized by step 60. In the event the peak intensity of the return light is less than the maximum intensity threshold, the^" presence of plaque is indicated, and processing proceeds to the next test symbolized by step 68.

Step 68 is a peak position test for determining whether the peak of the spectrum of the return light (i.e. the fluorescent light from the test tissue) is within the range of wavelengths encompassed by the peaks of healthy tissue spectrum used to calculate the composite reference spectra. If it is not in this range, the material at the distal end of the fiber is an unwanted substance and the laser is fired as symbolized by the path 70. If the wavelength of the peak of the return light is within the range of healthy tissue peaks, healthy tissue may be in front of the fiber so a spectrum shape test must be performed to further reduce the odds of firing the treat¬ ment laser at healthy tissue. The details given relative to step 128 of Figure 8 may be used also for the peak position test of step 68.

Step '72 represents the tissue index test for the test tissue, and is given in detail relative to step 130 below. In this test, the return light spectrum obtained by the sensor is normalized and is compared with the composite reference spectrum. The tissue index technique used to construct the composite reference normal spectrum is also used to determine the deviation of the return light spectrum from the composite reference spectrum. The tissue- index for the test tissue is compared to the tissue index threshold determined from the normal composite spectrum. The tissue index threshold is generally given by the largest least squares residual of the composite and the healthy tissue spectra used to compute the composite. This amounts to a determination of whether the best fit of the test tissue spectrum to the composite is worse than any of the best fits of all of the known healthy tissue spectra used to compute the composite reference spectrum.

If the tissue index for the test tissue is equal to or less than tissue index threshold, then no firing of the treatment laser is done during this cycle, and processing returns to step 60 via path 74. If the fit is worse than the worst fit of any normal tissue spectrum (i.e., the test tissue index is higher), then the presence of plaque or other unwanted obstruction in front of the treatment laser is indicated, and the treatment laser is fired as indicated by path 76 to the firing step 78. After firing, processing returns to step 60 via path 74 through steps 80 and 82. Step 80 is to determine if 50 cycles (or any other number of desired cycles) have been performed. In the preferred embodiment, the operat¬ ing physician is provided with a foot switch, and the computer operator has a keyboard for controlling the system (not separately shown) . The laser is interlocked with the foot switch such that it will not fire if the physician takes his foot off the switch, and in addition the laser will stop firing if the computer operator hits a predetermined key on the keyboard. If not, step 82 incre¬ ments the cycle counter and step 60 is performed again. If the requisite number of cycles have been performed, step 85 is performed to stop the cycling process and prompt the operator for any needed adjustments .

A difficulty with this technique is that a small fraction of normal tissue exhibits hemoglobin absorption as shown by the reduction in intensity on the left side of the peak in Fig. 5. The method of the invention therefore tests for this reduction in intensity by using a ratio test. If this heme dip shown in Figure 5 is found to oc¬ cur, the least squares residual analysis is only carried out on the right side of the curve.

It is difficult to compare the method discrimination results of one diagnostic study with another because of differences which include 1) choices of excitation light sources, 2) methods of emission detec¬ tion, and 3) tissue sites and tissue types. The data set of spectra used to construct the algorithm described here is much more extensive in size than any of those used in the prior art discussed. In addition, prior art considered only in vitro data, and no prior art known to applicants teaches or considers the use of a laser angioplasty system to collect data in vivo for use in mak¬ ing firing decisions. Much of the data used to develop the method described herein was obtained in vivo, and some data was obtained under actual clinical conditions. The shapes of in vivo plaque spectra tend to more closely resemble the shape of normal tissue spectra than the shape of i_n vitro plaque spectra. Also, spectra obtained during laser angioplasty surgery show peak shifts not observed in in vitro data. In addition, spectra can vary from optical system to optical system. Thus, results obtained with an actual laser angioplasty system which has an optical fiber and an optical multiplexer are more valid for determining the capability of a method to distinguish tissue types.

Due to the difficulty of comparing results for different diagnostic studies, and due to the greater validity of the data used to determine the method described herein, only this more valid data set will be considered in discussing discrimination capability. Alternative methods of discrimination considered in making the following comparison include line widths, areas, peak positions, intensities, ratios, centroidε, correlation functions and least square residuals (i.e. tissue indices) . These methods have been tested against the entire data set. Results show that absolute.intensities and one or two ratios can give no better than 50% correct identification of abnormal tissue, leading to erroneous identification of abnormal tissue as normal 50% of the time (although they may properly identify normal tissue as such close to 100% of the time) . Shape tests using the least square residual identify abnormal tissue 66% of the time (misidentifying abnormal tissue as normal the other 34%, although again, normal tissue may be correctly identified 100% of the time) (Leon, M.B. et al. , Circ (1987) 2i^:IV-⁴⁰⁸'^* Leon, M.B. et al. , J Am Coll Card, in press). This discrimination percentage for abnormal tis¬ sue is improved to 85% when peak positions are used as a criterion. Analysis indicates that if a composite of a few normal spectra of a particular patient to be operated upon is used instead of a composite of normal spectra from many patients, discrimination of tissue types for identifying abnormal tissue can be increased to over 90%. For instance, in actual tests which have been conducted using the method of the invention, the peak position test (Figure 4, step 68) and tissue index test (Figure 4, step 72) used in conjunction have been found to result in 91% accuracy in identifying noncalcified plaque, while maintaining 100% accuracy in identifying normal tissue. See Bartorelli, Al, In Vivo Coronary Plaque Recognition by Laser-Induced Fluorescence Spectroscopy, Supplement II Circulation, Vol. 78, No. 4, October 1988, in which the term "specificity" refers to percentage of successful identifications of normal tissue, and "sensitivity" refers to percentage of successful identifications of noncalcified plaque.

In summary, the process according to the teach¬ ings of the invention takes advantage of the fact that the fluorescent spectra of normal tissue of all patients are similar, while the fluorescent spectra of plaques differ even for plaques in the same category. The teaching of the invention is to make discriminations based upon this fact by determining when the spectrum of given plaque dif¬ fers by more than a specified amount from a composite normal tissue spectrum. The normal tissue reference spectrum used according to the teachings of the invention is derived from 75 in vivo spectra^' obtained from ap¬ - proximately 25 patients.

There is one additional complication in the discrimination picture. Normal tissue occasionally exhibits absorption by hemoglobin at approximately 425 n which is on the left side of the peak of the normal tissue composite spectrum 46 of Figure 2. The spectrum which results by "heme stain" is shown at 90 in Figure 5, and a non-heme-stained spectrum is shown at 92 of that figure. This phenomenon occurs about 5% of the time, so the normal tissue composite spectrum has the shape shown at 92 in Figure 5. Since the process according to the teachings of the invention compares the spectra of return light to the composite normal tissue spectra, he e-stained normal tis¬ sue might accidently be mistaken as plaque and fired upon by the treatment laser because of the differences in shape of the heme-stained normal tissue spectrum. To prevent this from happening, in the preferred embodiment of the invention, an additional test for absorption at 425 nm is performed.

This test can be best understood by referring to Figure 6, which shows the composite normal tissue spectrum at 46 and a typical return light spectrum at 48. The heme stain absorption test is simply a comparison of two intensity ratios. The first of these two ratios is the ratio of the intensity of the composite normal tissue spectrum at wavelength A, 425 nm, divided by the intensity of the composite normal tissue spectrum at wavelength C. The inverse ratio could also be used. The second ratio is the intensity of the return light spectrum at wavelength A divided by the intensity of the return light spectrum at wavelength D, which is the peak of the return light. The inverse ratio could also be used. If the difference between these two ratios is greater than a predetermined heme threshold set in advance by analysis of diagnostic data regarding spectra of heme-stained and non-heme- stained normal tissue, then plaque is indicated, and the treatment laser may be fired.

Figure 7 shows a method of controlling the treatment and excitation lasers incorporating this ad- ditiσnal heme stain absorption test. The method of Fiσur^Ω

7 is similar to the method shown on Figure 4, except that an additional test step 84 is present, and Step 72 has been split up into two steps, 72 and 72A. Step 84 calculates the ratios defined above and compares them to the heme stain threshold. If the heme stain threshold is exceeded, then there is no heme stain, and the program branches to Step 72, whereby the entire treatment tissue spectrum is used to compute the tissue index. If the heme stain threshold is not exceeded, then there is heme stain, and the program branches to Step 72A, whereby only the right side of the spectrum is used to compute the tissue index. Both Steps 72 and 72A test branch to Step 80 if the tissue index for the return light spectrum is found to be within the predetermined range, and branch to Step 78 if not.

By placing the distal end of a fiber on tissue and analyzing the return spectrum of the tissue, the systems shown in Figs. 1 and 11 can determine the kind of tissue which would be ablated if the treatment laser were to fire. However, these systems utilize a very small field of view, so the location of the fiber in the artery is not well known, and the distribution of unwanted tissue is not well known. The addition of a technique having a wider field of view would assist in positioning the fiber to increase patient safety and to increase the proportion of unwanted tissue which could be ablated.

Wider field of view techniques than sensing fluorescent spectra can be added as shown in Fig. 12. These methods could be used as adjuncts to the fluorescent-tissue type discrimination, or they could be used alone without fluorescence. The preferred method is to use a wider field of view technique in conjunction with a fluorescence technique, because a wider field of view technique detects the tissue type at the distal end of the treatment fiber with lower certainty than fluorescence sensing. Wider field of view techniques may include ultrasound, magnetic resonance, angioscopy, or other proc¬ esses. In the case of ultrasound, device 12 in Figure 12 is an ultrasound transducing crystal, and is positioned in an appropriate housing. In the case of magnetic resonance, device 12 is a magnetic resonance transducer. In the case of angioscopy, device 12 represents a lens and an optical transducer.

Item 16 in Figure 12 represents an appropriate wire or cable, which carries electronic signals to and from supply 18 in the case of ultrasound or magnetic resonance. In the case of angioscopy, item 16 represents an optical fiber bundle which carries the optical signal for an image from the body, and also carries light energy from supply 18 to the body. Item 16 generally will run parallel to the optical fiber 27, at least in the region close to the patient. In some usages, items 16 and fiber 27 will be in a catheter in the body.

Electronics unit .18 includes an electronic power supply for the device, including items 16- and 12 in the case of ultrasound and magnetic resonance. Unit 18 may include the light source in the case of angioscopy. Unit 18 may also include necessary image processing electron¬ ics . The power supply, light source and the image processing apparatus may actually be located in different physical units .

Item 8 is a screen showing the image returned by the wide field of view device. This image can be used by a physician to position fiber 27, so that its distal end is placed against unwanted tissue. The image on screen 8 will show where remaining unwanted tissue is located in the artery, and it may be able to show the physician the type of unwanted tissue which remains in the artery.

Item 9 is an electrical communication wire which links the wide field of view image processing electronics unit 18 and the system control computer 13. Item 9 is optional when using a wide field of view subsystem. The wide field of view image processing electronics 18 is preferably linked to the system control computer 13, so that the program may utilize information from the wide field of view image. An example of such a usage would be that an image is obtained before a treatment laser sequence after the fiber 27 and items 16 and 12 are cor¬ rectly positioned for treatment. The program would use a mathematical technique such as a correlation method to make sure fiber 27 and items 16 and 12 remain correctly positioned during a treatment laser sequence. If the position changes by more than a predetermined amount, the treatment laser is prevented from firing. Thus, the embodiment of Figure 12 improves the accuracy of the abla¬ tion method.

Following is a description of an alternative, preferred embodiment of the invention, wherein numerous factors, including those,^' described above such as heme stain, spectra ratios, and the like, are taken into ac¬ count in an iterative analysis which greatly reduces the likelihood of firing the laser onto normal or healthy tis¬ sue. This method is depicted in the flow charts of Figures 8, and is utilized in software which is stored in the computer 13 shown in Figure 1.

The following description should be understood on two levels: first, as an alternative embodiment to the above-described method of the invention, involving ad¬ ditional steps and techniques, as in Figure 8; and secondly, as a generalized problem-solving method which in the present implementation is used for the specific purpose of laser ablation of abnormal tissue, but whose implications and applications are in practice much broader, as in Figure 9. The method implemented by the software depends on a hierarchy of factors. In general, if -there is a change in a factor at a particular level, factors at lower levels are affected. The factors in this hierarchy are: 1) purpose of the control system; 2) criteria for choosing the system hardware 3) basic components of the hardware;

4) collection of data for the development of the process;

5) analysis of data to determine the best recognition technique and thresholds; and 6) detailed determination of the decision making flow. Factors 4 through 6 are carried out in an iterative fashion. As with the embodiment discussed above, data is^' first collected from sample normal tissues—preferably from several hundred samples for a good statistical sampling—and the data generated is later used in a variety of tests relative to data col¬ lected in vivo, for determining whether the laser should be fired in the carrying out of angioplasty.

More generally, as mentioned above, the present invention also teaches a method for problem-solving, based upon the application of a series -of tests to be performed, with the application of certain tests dependent upon the outcome of earlier tests. This method has numerous ap¬ plications, including but not limited to use in the medical areas discussed herein.

1. Purpose of the control system:

The purpose of the control system in the present embodiment is, as discussed, to distinguish between the signals of healthy and diseased tissue so that a treatment laser will fire only at diseased tissue, and further to distinguish between signals of diseased material and other material which should not cause the laser to fire, such as blood and air. In the present invention, the control system includes the apparatus depicted in Figure 1, including the software used in the computer. The control system also has features which increase patient safety and protect components of the system. Examples of increasing patient safety are closing a shutter in front of the ultraviolet diagnostic laser when patient exposure is not necessary, and lowering the treatment laser energy level when soft diseased material is detected. An example of protecting system hardware is closing a shutter in front of the detector before firing the treatment laser.

2. Criteria for choosing hardware:

There are several criteria for choosing hardware which affect the diagnostic signal in the present inven¬ tion. The hardware must support a technique which ef¬ fectively discriminates between healthy and diseased tis¬ sue. The technology on which the hardware is based must be capable of operating effectively in a clinical setting. These features include speed, reliability and size. The method used must be safe for the patient and the clinical operators of the system.

3. Basic Hardware:

The basic hardware in the present system are those components shown in Figure 1.

In the case of the present system the excitation source is a laser which emits ultraviolet light. A continuous wave HeCd laser emitting at 325 nm may be used, but experiments show that a pulsed nitrogen laser emitting at 337 nm gives very similar results. The treatment source is a pulsed dye laser which is operated at 485 nm. The computer preferably comprises an optical multichannel analyzer, such as the OMA III model 1460 made by EG&G Princeton Applied Research of Princeton, New Jersey. The diagnostic laser light and the collected tissue fluorescent light are transmitted by the same optical components including an optical fiber or fiber bundle, such as fiber or bundle 37 shown in Figure 1. The sensor or detection system is a spectrometer coupled with a detector having an intensified photodiode array and including an optical fiber bundle 32. Aspects of the hardware which may affect the implementation of the present method are discussed below.

The carrying out of particular steps in the method may change due to changes in the hardware which cause the diagnostic signal to change, or they may change due to changes in the hardware which alter aspects of the system which can be controlled by the computer.

Features of the diagnostic source which affect the diagnostic signal, include the type of signal such as electromagnetic waves, ultrasound or magnetic resonance. The wavelength of' the source may affect the signal. For example, tissue exposed to an ultraviolet laser source yields a signal which differs from that of the tissue exposed to white light. The diagnostic signal produced by a pulsed source may depend on the pulse width ^land frequency in some cases. Also, the source intensity can affect the signal. Thus, the preferred embodiment of the system controls the pulse rate, the period of exposure, and the intensity. If there are two diagnostic sources, the capability of varying the wavelength by alternating between the two should be provided, such as between laser light and white light. In addition, the capability of varying between two different diagno^'stic systems, such as laser light and ultrasound, may be provided. Other diagnostic media besides light and ultrasound may be used.

The method of the invention preferably also controls the ablation depth of the treatment laser. Fac¬ tors which may affect the ablation depth include the wavelength, pulse width, pulse rate and energy per pulse. The pulse rate and energy are variable, but should be great enough that progress in a clinical case is adequate. However, the depth ablated should not exceed the tissue depth at which fluorescence originates. When possible, ablation of diseased tissue should be adequate and abla¬ tion of healthy tissue should be poor. The pulse width and wavelength may be varied as necessary.

The capability of the computer affects the method of the invention. The greater the speed of the computer, of course, the more complex the method which can be accommodated by the software stored therein, especially when utilizing a real-time in vivo ablation implementation of the invention. This is because in such a setting, the computer's decision of whether or not the treatment laser is to be fired must be made in as short a period as pos¬ sible following the collection of the diagnostic spectrum, so that the fiber tip does not move significantly, which could cause the firing of the laser upon healthy tissue.

Other computer factors affecting the complexity of the method which may be implemented include the memory size, number and type of input/output ports, and the capability of synchronizing timing. - Currently the computer controls a pulse which fires the treatment laser and it has output control of shutters both in the treat¬ ment laser cavity and in front of the diagnostic laser and spectrometer. An input signal from a foot switch can start and terminate the sequence which determines if the treatment laser fires .

The collection optics can affect the spectral resolution and the spectral transfer function or wavelength region over which the system is sensitive. The efficiency of the optical system affects the intensity of the detected signal. Shapes of tissue spectra obtained with this new optical system differ from spectra obtained previously, because an additional wavelength region contributes to the spectrum. Changes in the sensor or detector system can also cause spectra or images to change. In the case of images these changes include the spacial resolution, the wavelength region over which the system is sensitive, and the contrast. In the case of spectra these changes include the spectral resolution and the wavelength region over which the system is sensitive. The sensitivity of the detection affects the intensities measured. The present system uses a spectrometer whose grating is blazed for optimum operation at 300 nm. The detector has a wavelength resolution of two pixels per nm and a sensitiv¬ ity of about 0.2 counts per photon.

4. Data collection:

Generally data collection begins with spectra of in vitro tissue. We have found that the age of the tissue can have a significant effect on the shape of the fluorescent spectrum. Spectra taken from tissue harvested over a day after death can look very different from these of fresh tissue. Spectra of fresh tissue looks similar to spectra of tissue obtained JLn vivo. This result is important because articles in this field which statisti¬ cally test methods for tissue type recognition (Anderson P.S. et al, Lasers in Med. Sci., V2:261 1987, and Casala et al, Circulation Abstracts, V76SuppiV:524 1987) base their analyses on spectra which look like spectra of old tissue and not spectra of in vivo tissue. Tissue types are easier to discriminate in older tissue, but results of 'methods tested with these spectra are misleading when considering the capability of a given method for discriminating between tissue types in clinical in ivo treatment cases .

In vitro analyses are, however, useful for determining the ablation depth of a laser pulse. As explained above, the ablation depth must be known for the method to choose the optimum pulse energies and rates .

In vivo diagnostic spectra are generally acquired after preliminary in vitro studies. Unlike actual clinical cases where the treatment laser is used, the tissue type of spectra taken during a diagnostic case can be identified with relatively high accuracy. These spectra are generally obtained during open heart surgery and balloon angioplasty cases. Although physicians cannot actually see the tissue in a balloon angioplasty case, the location of a fiber indicated by angiography is often of whether the distal end of the fiber is against plaque or normal tissue. Comparison of angioplasty spectra and surgery spectra indicate that identification based upon angiography alone is relatively accurate. Therefore, these _in vivo diagnostic spectra are used to develop the method.

In vivo spectra are also obtained during clinical cases. There are materials inside arterial obstructions whose spectra appear different from those obtained during in vivo diagnostic cases. For' this reason a method cannot be based on spectra found in diagnostic cases alone. An example is thrombus, whose spectra are frequently encountered in clinical treatment cases but rarely in diagnostic cases .

All of the spectra for a given case are col¬ lected at one time, so that changes in spectra—preferably due to factors such as blood in the field and the varying ' distance between the fiber tip and tissue caused by tissue ablation—can be examined.

5. Analysis of Spectral Data:

Spectral features can be identified by their shape, wavelength position, variability and intensity. There are a variety of simple mathematical techniques which describe these features. Shapes can be described by ratios, slopes, widths, areas (of normalized curves), and minimum least square analyses compared with a reference shape. Curve positions can be described by their curve fitted peaks, true peaks, and centroids, as mentioned in the above discussion of the embodiment of Figure 5. Variability can be described by changes in area and the intensity at particular points.

A trial and error approach is used to determine the best method for distinguishing between the spectra of different tissue types. The spectra.of different tissue types are put into arrays. There are arrays which include all healthy tissue, all diseased tissue, particular types of diseased tissue and normal and diseased tissue with blood in the field. The analytic methods are put in a second type of array. The analytic methods are applied to the spectra in the tissue arrays. The result of these calculations is- distributions of values for healthy and unhealthy .material for each technique. There are several criteria for choosing the best discrimination technique. The treatment laser must not fire at healthy tissue and healthy tissue with blood. The best analytical techniques for discriminating tissue types are those which yield the 5 lowest percentage of values for diseased-tissue spectra in the range of values found for spectra of healthy tissue. Another desirable criterion for selecting method techniques is that not only should the.distributions of the spectra of unhealthy and healthy tissue have minimum 0 Overlap, but the .separation between values for each tissue type should be large. Since the distributions for healthy and unhealthy tissue values generally overlap, the bound¬ ary where they overlap is the threshold where the laser will and will not fire. 5

In some cases the capability to distinguish between tissue types may be improved by combining method techniques. For example, consider a particular type of diseased tissue whose spectra have widths which are greater than the widths of all normal tissue spectra fifty percent of the time. Suppose that sixty percent of the fifty percent of diseased tissue spectra which are in the range of normal tissue have peak positions which are outside of all normal tissue. Eighty percent of the diseased tissue can be distinguished from the healthy tis¬ sue with a method which instructs the laser to fire at all tissue whose spectra either have widths greater than all normal tissue spectra widths or have peak positions which are outside the range of all normal tissue spectra peaks.

Different tissue types will have different spectra. Therefore, different recognition criteria are needed. For example, fibrous plaque spectra have peaks at wavelengths shorter than those of normal tissue and thrombus spectra have peaks at wavelengths longer than those of normal tissue.

6. Method Development:

Figure 9 is a flowchart showing^' the generalized method of the invention, and is discussed in detail fol¬ lowing the discussion of Figure 8. Generally, changes in the method are initiated by the development of new hardware, the occurrence of tissue types not currently considered, and the development of new method techniques. If changes in the hardware affect the diagnostic spectrum then new data must be acquired unless the effect is small or unless a transfer function can be generated which ac¬ curately predicts how the spectrum will be changed. Other changes in the hardware affect the features of the system which the method can control. An example of a hardware change which changes the spectrum is one in which an improvement in the optics which increases the wavelength bandwidth of the system has required changes in the method because the shapes of the fluorescent spectra emitted by tissue appear to be different. An example of a hardware change in which the method can control a feature of a component which could not be controlled previously is the treatment laser power. Thrombus is an unwanted material with a double peaked spectrum which can be ablated with the laser set at a low power. A thin layer of blood between the fiber and tissue also produces a double peaked spectrum. Lowering the laser intensity permits the abla¬ tion of thrombus, but reduces the damage to tissue behind a thin blood layer.

Changes are initiated within the loop at Step 124, which considers if the method performs adequately during clinical cases . Many changes in the method have been based on results of clinical cases. The need to consider peak positions in addition to curve shapes was found from clinical treatment cases when a diseased material which has a spectrum shape similar to that of normal but has a peak shift was frequently detected. Automatic grouping of pixels shown in Step 120 of the cur¬ rent method box was introduced when too much time was spent during clinical cases changing the grouping outside of the loop.

Referring now to Figure 8, a flow chart is shown for a specific application of the invention relating to laser ablation of atherosclerotic lesions in arterial ves¬ sels. The method will be described -in conjunction with the flow chart boxes by reference to the letters thereof.

Step 100: Information obtained prior to fiber insertion.

The information which is obtained in advance, as discussed above relative to test cadavers or other tissue, includes the range of peak positions of a parabola fitted to a spectrum for normal and abnormal tissue, thus generating a threshold value for normal tissue without the presence of blood. Also, the positions of the spectrum used to compute the parabola are given. A second threshold supplied at this time is the hemoglobin or blood stain ratio, as described in further detail relative to step 128 below. Positions of the spectrum where this ratio is computed are also supplied. This factor is described below in greater detail relative to step 126. A third threshold which is supplied is for the least squares deviation between data spectra and a spectrum referred to as the standard normal which is a composite of normal tis¬ sue spectra obtained i.n vivo. Also supplied are the points on the spectrum used to compute the least square deviation. Default minimum and maximum intensities are also given. ^• A detector background must be subtracted from every spectrum. The background is obtained at the begin¬ ning of a clinical treatment case.

In addition to the above information, preferably a relative pixel gain calibration value is also generated, in order to compensate for the fact that the response of each system to a stable broadband source is different from the responses of other systems. Improvements in the system can reduce these differences, but there are limita¬ tions to the improvements which can be made.

The present method is based on the shapes of spectra obtained with a single or a small' number of systems, i.e. the physical arrangement.of apparatus such as that shown in Figure 1. Other systems, and in fact other identical apparatus, will measure slightly different shapes when observing the same material or source, simply because of inherent differences between the instruments, even instruments made to the same specifications . Therefore, it is preferable to calibrate all systems with a standard source, such as a light source traceable to the National Bureau of Standards. Such a lamp is available, for instance, from General Electric as calibrated by Optronics Laboratories of Orlando, Florida. By comparing the white light spectrum measured by the diagnostic system used to acquire spectra on which the method is based, a calibration file can be computed. This calibration file is used to modify every spectrum measured by the treatment system so that the method treats the modified data as though it had been obtained by the original diagnostic system.

The present method when used in other applica¬ tions may require different thresholds obtained from diagnostic testing. Thresholds for images would be based on values obtained from image recognition methods in which an image found during treatment is compared with a refer¬ ence image, which might be acquired just prior to begin¬ ning a treatment cycle. Background and gain correction files can also be implemented in the system of the inven¬ tion.

Step 102: Phosphor reference test.

Prior to clinical treatment, diagnostic tests may be run to test the system. At this time, the software and diagnostic system hardware are tested by comparing a signal obtained from a reference phosphor (obtained when the system went through quality control) with the signal measured from that same phosphor prior to clinical treatment. The difference between the data spectrum and the reference signal must not exceed a threshold based on whether or not the tissue will be able to successfully identify tissue types.

Also at this time, the background signal due to the electronic and optical apparatus itself is subtracted. In order to do this, the equipment is activated, and read¬ ings are taken, but with the shutter 36 closed. Any data generated by the detector 33 under these circumstances must be due to background noise of the equipment, and the program stores the amount of apparent intensity for later subtraction from any counts that are generated from actual specimens or patients.

Step 104: Insert fiber.

Once the phosphor reference test is completed, the optical fiber is inserted into the patient.

Step 106: Probe and display.

After the fiber has been inserted into the patient's body and the distal end of the fiber is placed on the area of diseased tissue the probe and display mode is used. At this time in this mode the diagnostic source excites tissue fluorescence and method parameter values and the spectrum are printed on the computer screen. At a future date probe and display might also include _. images, and other information.

Step 108: Information obtained with, the fiber in situ.

At this time intensities found from material in the arterial obstruction are used to determine the intensity range in which the laser will be allowed to fire. Diseased material generally fluoresces more weakly than normal tissue, so that if the intensity of material is found to be low then the intensity range will have low values, with the result that diseased material will be ablated without ablating normal tissue.

Other factors used by the method in the closed loop part of the flow chart of Figure 8 (see the box fol¬ lowing Step 108) could also be obtained while the fiber is in situ. Under some circumstances, it may be desirable to obtain a spectrum of a patient's normal tissue as a refer¬ ence curve for material which should not be ablated. Reference images could be obtained to indicate the orientation of the fiber and position of the fiber tip. A marker on the distal end of the fiber would be used to indicate the tip position.

Steps 110 through 136 comprise a "probe and fire" portion of the inventive method, in a closed loop which may be carried out for a predetermined number of times or until the operator causes an exit to the loop.

Step 110: Store data.

The program of the invention determines and stores how many times the laser fires in a closed loop cycle, and in the preferred embodiment stores method parameters and .complete spectra. -Other data may, of course, be stored as desired.

Step 112:' Diagnostic source(s) on. Adjust if necessary.

At this time the continuous wave HeCd laser which emits at 325 nm is used to excite a fluorescent signal in tissue. Although the laser is on continuously, tissue is exposed to the HeCd beam only during the period while the detector is collecting the fluorescent spectrum (which is then used by the method to determine if the treatment laser should be fired) . The computer program controls a mechanical shutter 10 which is in front of the laser 11, which is opened when data collection begins and is closed when data collection has been completed. The shutter 36 is closed when treatment is being conducted, and is open when diagnostic light is being used.

O

Conversely, shutter 34 is closed when diagnostic light is being used (in the case of a two-laser embodiment), and is open when treatment light is used. - When a pulsed nitrogen laser is used, the method determines when a pulse is to be triggered. Two or more sources could be used in the same system. The method could open a shutter in front of an ultraviolet laser, obtain a spectrum, close the shutter and then open a shut- _j_0 ter in front of a white light source and obtain a second spectrum. It could control an ultrasound or magnetic resonance device and obtain images. In the case of light emitting devices the method might control the intensity with an electrical or an optical device.

15

Step 114: Read detector(s). Adjust if necessary

At this time an intensified photodiode detector with 512 pixels is used. The fluorescent spectrum is

20 measured between about 375 nm and ,^'650 n . The method can control the integration time for one spectrum. It controls another shutter 36 positioned in front of the detector 33, as shown in Figure 1, and the shutter 36 is closed before the treatment laser is fired so that the

25 detector is not damaged. In an alternative embodiment, the dynamic range of the detector may also be controlled.

' Step 116: Pre-in situ determined data corrections.

30 ' At this time, spectra are corrected by subtract¬ ing a background. In the future gain calibrations as discussed in Step 100 will be used. Corrections for bad pixels, bad detector areas or signal contamination by components in the system may have to be removed.

35Step 118: Signal intensity adequacy determination. At this time, adequate signal intensity is indicated by peak intensity. The maximum allowable intensity is the intensity at which the detector becomes saturated (typically indicated by a flattening out or other distortion of the output spectrum) , and the minimum allowable intensity is the intensity at which the signal- to-noise ratio is not adequate to interpret spectra. These maximum and minimum intensities are the extreme values which can be used in an intensity test. The criteria for determining an intensity range discussed in Step 108 will generally produce a more restrictive intensity range than the criteria discussed in this sec¬ tion. Other signal quality features may be considered, such as contrast of images.

If the intensity is of the signal is in the cor¬ rect, predetermined range for analysis, the program proceeds to Step 124, which includes the test for whether the least squares parabola fit is within the desired range. If the signal intensity is not within the desired range, the program branches to Step 120.

Step 120: Signal correction possible.

If the peak intensity lies in a certain pre¬ determined range of low values, then the signal-to-noise ratio can be improved by summing adjacent pixels, i.e. the pixels 1-512 shown in Figure 1A. If the peak intensity is below this range, it is deemed too weak for analysis, even 'by the pixel-adding technique of this step, and the program branches back to Step 110. The range for correct¬ able intensities for the peak value can be empirically determined, and depends upon such factors as the relative magnitudes of the peak intensity signal and the signal-to- noise ratio, the contrast in the case of images, the sensitivity of the detector, and other factors which may be found to adversely affect the reliability of the signal, especially as it affects the ultimate computer determination of whether given tissue is normal or ab¬ normal .

The purpose of this step is, therefore, to determine if the peak intensity lies in the range in which the signal-to-noise ratio can be improved. In the preferred embodiment, a signal correction is made if the peak intensity is between the minimum threshold intensity and one-eighth of the minimum threshold.

Step 122: Correct signal.

By the action of the diffraction grating (not separately shown) carried by the spectrometer 31 shown in Figure 1, the spectrum of fluorescent light obtained from in vitro specimens or a patient is diffracted- such that each pixel 1-512 in the linear array 38 (see Figure 1A) receives a narrow band of wavelengths of the spectrum, and the computer then stores 512 signals, each having an intensity corresponding to a given band of wavelengths. The graphs of Figure 5 are representations of such data. In the present embodiment, since the spectrometer detec¬ tion range chosen is about 375 to 650 nm, this leads to a spectrometer resolution of 512/(650-375) pixels per nm, or approximately 1.9 pixels per nm. Other resolutions may be utilized by changing the size of the array 38 (including the size of the individual pixels) or by changing the dif¬ fraction grating.

If the signal received by a given pixel has in¬ sufficient intensity, it is then corrected by grouping or summing signals received from adjacent pixels. This reduces the wavelength resolution, but improves the signal-to-noise ratio. The method first groups two pixels (such as pixels 1 and 2, pixels 3 and 4, etc. , in Figure 1A) , adding their intensities, and tests if the new peak intensity is adequate. If the intensity remains in¬ adequate it then groups 4 pixels (e.g., pixels 1-4, pixels 5-8, etc.), and again makes the intensity test. If the peak intensity is still below the predetermined threshold, the program groups 8 pixels and once more makes the intensity test.

Applicant has found that the capability of the method to discriminate tissue types is not significantly diminished by the loss of wavelength resolution, by a fac¬ tor of 8 when pixels are summed or grouped by 8, which is at least in part due to the fact that the spectra gener¬ ated tend to be rather smooth, with few or no steep slopes between intensities, because the intensity responses of similar wavelengths are relatively close. The effective result of grouping a 512-point spectrum eight pixels at a timβ is to produce a spectrum with 64- points which is eight times as intense. Other signal corrections may be needed; for instance where images are being generated, enhancement of the images may be desirable, such as by using known, computer-controlled image improvement techniques .

Step 124: Parabola fit test.

The intensity range set in Step 108 is tested in

Step 124. At this time the method tests the peak position to see if it is in a range in which both diseased and healthy tissue peaks are observed. Also at this time the least squares deviation of the parabola fitted to the data to find the peak is compared with the data. If the fit is

2 not good (e.g., if the r value in standard least squares formulae is not acceptable) , then the curve does not have the general shape found for healthy and unhealthy tissue. In an alternative embodiment, the system is provided with an imaging-capable system, such as ultrasound or magnetic resonance, and in such an embodiment, a standard image correlation technique is used to compare an image taken at this time with a reference image, to test for proper orientation of the fiber.

If the parabola fits test indicates a good fit, then the program proceeds to step 126; otherwise, the program branches to step 110.

Step 126: Test for blood absorption.

Blood has a strong absorption feature in the wavelength range of the tissue fluorescence feature used to discriminate tissue types, as discussed above and as shown in graph 90 of Figure 5. Therefore, blood alters the tissue fluorescence spectrum. There are some types of tissue which have hemoglobin absorption in them. The purpose of this step is to determine if the spectrum being analyzed is altered by a factor such as blood. This step may be referred to as the heme test, because the absorp¬ tion feature of blood is due to the heme portion of hemo¬ globin.

The test for blood absorption first involves the determination of a number derived from a composite of normal tissue spectra obtained from .in vivo diagnostic cases. This number, which may be referred to as a standard normal composite, thus represents an empirically- determined factor which is based upon past data and is used in a given instance to determine how likely it is that the tissue being tested is normal.

The value for the standard normal composite depends on the system used to take the spectra because, as explained above, different systems may obtain different appearing spectra from the same source due, for instance, to equipment specification differences. Typically, standard normal spectra which have been developed are constructed from about 50 spectra^'obtained from about 20 patients . The spectra used to compute a standard normal composite appear quite similar and show little blood absorption. First, the spectra are aligned by the posi¬ tions of their peaks and summed together to form a preliminary composite reference spectrum. Next, each normal spectrum is shifted with respect to the reference spectrum until a least square residual is found. Using the position where the best least square fit occurred, the spectra are summed to form the standard normal composite. The center of the blood absorption feature usu¬ ally occurs at about 412 nm. This can be seen in the graph of Figure 5 , which shows an absorption dip on the left side, which begins rising sharply at about the 70th pixel (which is about the expected value, since 1.9 pix/nm times (412-375=37) nm equals 70.3).

The ratio used to test for blood absorption is given by the ratio of: (1) the data peak intensity divided by the data value at 412 nm for the tissue being tested, to (2) the standard normal peak intensity divided by the standard normal value at 412 nm. If this ratio is above a threshold ratio, then there is blood absorption in the spectrum which the method must take into account. If blood absorption is indicated, then the program branches to step 132; if not, then it branches to step 128.

The details of the method which tests for blood 'may be different from those described in this test, but in general will have the feature ^' in common that the presence of the strong absorption by blood at about 412 nm is detected. Also, in alternative embodiments tests for other error-introducing factors may be introduced, such as for the presence of compounds which may be present that influence the fluorescence spectrum, or for any other fac- tors which may affect the accuracy of the spectrum detected from the patient.

As an additional portion of this test, a spectrum variations test may be employed. In this test, each test tissue spectrum (except the first one generated in a given procedure) is compared with the preceding test tissue spectrum, to see if there is a great variation between the two. The comparison may be done by a least- squares analysis, by taking a ratio of the two spectra, or by other equivalent methods of detecting variations. If a variation is found and is higher than a certain pre¬ determined threshold (which is empirically determined), this is an indication that blood has come into the field of view of the optical fiber, and the program branches to Step 132. Alternatively, a high variation may' cause the program to branch back to Step 110 (not separately shown in Figure 8) .

Step 128: Peak position test (no blood present).

This step tests for whether the detected peak for the test tissue is in an empirically-determined normal range. The range chosen should be based upon the study of many normal tissue spectra. Applicants have determined that a range of approximately the 140th pixel to the 180th pixel is to be expected for normal tissue, as reflected in graph 92 of Figure 5. This corresponds approximately to a wavelength range of (140x1.9 + 375) to (180x1.9 + 375) nm, or about 638 nm to 727 nm. There are thus two peak posi¬ tion threshold^'s, one at the lower boundary for normal tis¬ sue and one at the upper boundary.

As explained in Step 100, a parabola is fitted to the spectrum and the peak of the parabola is used as the spectrum peak, because the true peak shape is more sensitive to the effects of noise. Materials whose spectra have peaks outside the range found for normal tis¬ sue are ablated by the treatment laser.

If the detected peak is outside the normal range, then the program branches to step 136, and the laser is caused to fire at the tissue. If the detected peak is in the normal range, this still does not necessar¬ ily mean that the test tissue is normal, and the program branches to step 130 for the tissue index test, discussed below.

Variations on this step may be implemented. For instance, it may be found that a certain type of abnormal tissue typically has a peak which is higher than the normal range, but rarely or never has a peak which is lower than the normal range. If it is desired that only this particular type of tissue be removed (and other ab¬ normal tissues, having lower-than-normal peaks, be allowed to remain) , then the program can be adjusted to test not only whether the peak is in the normal range, but also whether it is on the high side or the low side. If it is on the high side, then the program would branch to step 136 as before; but if it is on the low side, then the program would branch to step 130.

Step 130: Tissue index test (no blood present).

This step tests how closely the shape of the spectrum for the test tissue matches the shape of the standard normal spectrum. This is done by generating a 'value which may be referred to as the tissue index, which is a least-squares residual, for the tissue being tested. The tissue index value is based upon the least-square deviation of the test tissue spectrum from the normal tis¬ sue spectrum.

The tissue index test, which may also be referred to as the standard normal test (since it tests for deviation from the standard normal spectrum) , involves several types of parameters, including: (1) the tissue index threshold; (2) the cursor or pixel positions used to make the calculations; and (3) shift alignment factors. These are discussed below.

Figure 6 explains part of the tissue index test procedure. A, B, C and D in Figure 6 are pixel positions, and the fixed curve is the standard normal curve which is compared with the data. The standard normal curve to be used is the composite spectrum generated as shown in the flow chart of Figure 3 above, and preferably numerous spectra (on the order of 100) are utilized in generating the composite spectrum.

The test tissue data changes every time the detector is read. The formula used to compute the least square residual (tissue index) is given. The greater the difference between the data and the fixed (standard normal) curve, the greater the likelihood that the data is a spectrum of diseased tissue.

The tissue index threshold is calculated by the formula shown in Figure 10, as follows. First, the test tissue data is normalized by dividing the entire set of data by the value found for the peak intensity for the test tissue spectrum. Then, the numerical differences between the test tissue spectrum and the standard normal spectrum are found at five predetermined pixel locations, the five pixel locations being chosen such that the numerical differences may be expected to be maximized. This is done by observing many sample spectra of the type of abnormal tissue being treated (such as plaque) from numerous patients, and by observation, averaging techniques or other statistical analysis, determining the frequencies (and hence the pixel locations) at which the test tissue spectra differ most from the normal spectrum. These pixel values are stored in the memory of the computer.

In one implementation of the invention, the pixel positions (referred to in Figure 10 by the variable Dl.) are not stored as absolute pixel positions; rather, they are stored as differences between the pixel position of the peak of the curve in question and the desired pixel position. For instance, if the peak for the normal spectrum is at pixel 170, and one of the empirically- determined maximum curve differentials (between the curves for abnormal tissue and normal tissue) is at 70, then Dl

1 (i.e. Dl. where i=l) is stored as -100. Likewise, if the other four pixel locations which maximize the curve dif¬ ferentials are found to be 80, 250, 310 and 370, for example, then the values of Dl. through Dl_. are -90, 80, 140 and 200, respectively. The variable Dl may be referred to as a pixel differential variable.

Although for the sake of illustration only two pixel locations (A and C) other than the peaks (B and D) are shown in Figure 6 for maximizing the curve dif¬ ferentials, in the preferred embodiment, as discussed above, five- such pixel locations are chosen. Other numbers of curve differential-maximizing pixel locations may be chosen, either more or fewer, depending upon how the operator determines that the choice of such pixel locations affects the reliability of the tissue tests. For instance, for a given type of tissue it may be found that there are three particular pixel locations relative to the peak intensity where the test tissue spectra reli¬ ably differ by a large amount from the normal tissue spectrum. In that case, those three pixel locations alone would be utilized. On the other hand, it may be found that there is a broad range over which the test tissue spectra differ from the normal tissue spectrum, in which case a larger number of relative pixel locations may be chosen for the tissue index test.

In the preferred embodiment, two pixel positions on the left side of the spectrum and three pixel positions on the right side of the spectrum are used to compute the least-square residual. In the formula of Figure 10, therefore, N=5 for the preferred embodiment.

Once the pixel differential variables are empirically chosen, they are stored in the computer for use whenever tissue ablation is conducted on the type of- tissue from which the pixel differential variables were determined. Another set of pixel differential variables,

D2. , where j runs from 1 to 7 in the preferred embodiment, _ must also be chosen. These are preferably, small numbers, such as - . , -4, -2,^' 0-, 2, 4 and 6, and each tissue index value TI . is^" determined for one such value .of j. Thus, seven values for TI .are generated (TI, through TI_) by the formula of Figure 10. The use of the variable D2, which may be referred to as the fine shift adjustment variable, compensates for possible misalignments between the peaks of the test tissue spectrum and th ^' standard normal spectrum. The- program then chooses the smallest TI . value of these seven, and this is stored as the value for the tissue index of the test tissue under treatment. The reason for choosing the smallest TI value is, to minimize the possibility that normal tissue will be ablated"as ab¬ normal tissue.

One method for selecting a set of values for each of the pixel differential variables is to first generate a composite normal spectrum, as discussed relative to Figure 3 above, and then to compare successive abnormal tissue spectra with the composite spectrum, either physically or mathematically, and arrive at one, several or many sets of pixel differential variables . A tissue index value can then be generated, using these

between the tissue indices of the normal and abnormal tis¬ sue. Thus, the likelihood is minimized that, for a given tissue, erroneously large TI values will lead to ablation of normal tissue.

Each of the differential variables D1--D1,. and D2--D2-. is determined in advance of actually carrying out an operation on a patient. With experience, the operator may wish to alter the values of these variables for a given type of abnormal tissue, in which case the tissue index threshold (given as 0.005 in the above example) will have to be altered accordingly. The details of this step may also need to be altered if the optics of the system are altered.

Step 132: Peak test (blood present)

In the case of the peak test of this step, where blood has been determined to be present in the field, the larger of the two peak thresholds is set to a slightly higher value than the threshold for^" spectra having no blood absorption. Otherwise, this step is identical to step 128, which is the peak test where no blood is present. Thus, instead of an expected pixel range of 140 to 180 for the normal peak, the upper threshold is raised to 185; and this may be adjusted as normal-tissue data may indicate. The upper threshold is raised because it has been found that the presence of the blood absorption dip (as in graph 92 of Figure 5) skews the peak slightly to the right, such that it appears to be occurring at higher frequencies, corresponding to higher pixel numbers.

If the test tissue peak is within the prescribed range, in this case from the 140th to the 185th pixel, then the program branches to step 134. If the test tissue peak is outside this range, the program branches to step 136 for ablation by the laser. Step 134: Tissue index test (blood present) .

Step 134 is identical to Step 130, except that the tissue index value is generated only for data on the right side of the graphs of Figure 5, i.e. to the right of the peak for the spectrum of the test tissue, because the blood absorption dip distorts the data corresponding to the lower pixel numbers. It will be appreciated that in this case, the values of the curve differential variables

Dl. and D2. are only positive. The tissue index test is thus modified in this way to account for the effect of blood absorption on the spectrum, and may be otherwise modified as necessary or empirically determined to avoid misleading factors in the data. If the tissue index test yields a tissue index value for the test- tissue which is outside the range for normal tissue, then the program branches to Step 136 (as was the case with the tissue index test of Step 130) . Otherwise, the program branches to Step 110.

Step 136: Open treatment laser shutter and fire.

At this time, the shutter 34, which may be car¬ ried in the cavity of the treatment laser 17, must be opened before it can be fired. The shutter 34 serves as a safety feature, so that the treatment laser does not fire if the laser is accidentally triggered. Also, the shutter prevents contamination of the diagnostic signal by light which may be emitted by the treatment laser flashlamp even when the laser is not firing. In a preferred embodiment, the laser output energy is also adjusted; in the case of a pulsed laser, the total energy or the power of each pulse may be adjusted, depending on the depth of ablation desired, the intensity of the abnormal tissue spectra be- ing detected, and other factors. The treatment laser is fired after any such adjustments are made.

The above method is carried out repeatedly and quickly, as controlled by the computer, for a pre¬ determined amount of time or number of cycles. Thus, if method is carried out, for example, 50 times and then stops, the operator is given an opportunity to assess the results before beginning treatment again.

When the iterative method of the invention is utilized, each step in the iteration (such as Steps 124, 126, 128/132, 130/134, etc.) increases the probability that the determination made by the computer as to whether the tissue is normal or abnormal will be correct. As mentioned above, the thresholds are preferably chosen such that substantially all normal tissue is correctly identi¬ fied as such, and these thresholds result in a given percentage of abnormal tissue (usually less than 100%) being correctly identified in each of the tests represented by the above steps.,

By way of example, assume that Step 132 yields a 70% correct discrimination rate for plaque (i.e. , identi¬ fies plaque correctly as such 70% of the time) , and that Step 134 yields a 50% discrimination rate for plaque. In carrying out Step 132, then, 70% of the time that plaque is under observation the program will branch to Step 136, and the other 30% of the time the program will branch to Step 134. When the program branches to Step 134, if plaque is present then 50% of the time the program will then branch to Step 136, and the other 50% of the time it will branch to Step 110; thus, half of the plaque which escaped Step 136 will be caught by Step 134. The total percentage of plaque caught by either Step 134 or 136 (and thus treated due to Step 136) will therefore be 70% -¹- (50% of 30%) = 85%, a 15% improvement over the test of Step 132

composite spectrum, the abnormal tissue spectra, the pixel differential variables, and so on.

Step 158 relates to the generation of a process for the utilization of the data generated in Step 154. A given technique is first introduced (as indicated by Step 164), and the data generated in Step 154 is then utilized to develop a method for implementing the technique. For instance, if it is determined to be advantageous to standardize test tissue spectra to the spectra generated from normal tissue (a new technique), for the purpose of identifying atheromatous tissue, then a particular curve- fitting formula or method for generating pixel dif¬ ferential variables may be developed for implementing the technique.

Once the method for the given task is developed, it is tested to determine whether it is adequate to make the decisions necessary for the situation, as represented in Step 166. , In the above example, the end result is the proper or improper determination of whether the test tis¬ sue is normal. If the chosen method leads to incorrect results, it must then be inspected and perhaps modified and retested to determine whether it is even capable of yielding adequate discrimination ^' etween the decisions necessary to be made. Thus, if inadequate discrimination is found, the method of Figure 9 branches to step 156, wherein it is inspected whether an adequate new (or revised) method can be developed. If not, then the method branches to step 150, which requires the development of 'new hardware; if so, then step 158 is again reached, to introduce a new technique or develop a new method for the task.

Once the method is found to yield reliable results, the method reaches step 168, wherein the new method is implemented (and new thresholds, in the case of the above example) . Then, in step 170 the method calls for the determination of whether there are any new hardware control parameters which can or should be im¬ plemented, which is accomplished in step 172 if that is the case. This may relate, for example, to the utiliza¬ tion of different laser pulse energies.

At step 174, the actual clinical case is reached, and the method and hardware parameters chosen are put to the test. In the example at hand, the laser is fired if so indicated, and in other examples, other ac¬ tions may be taken. Step 176 questions whether the outcome was satisfactory; if, for example, the physician finds that all of the abnormal tissue in a patient has been ablated, without the ablation of an undue amount of normal tissue, then he may decide that the operation has been successful, and step 178 (finish) is reached.

If the method developed in Step 158 is found to be unsatisfactory in practice, then Step 180 is reached, at which it is determined whether a change in the_. hardware control will suffice to solve the inadequacy. If so, then Step 172 is reached for such 'a change. If not, then the clinical data generated in step 176 is analyzed, the method branches to Step 158, and a new technique is introduced as indicated by Step 164. The method is then repeated until satisfactory results are achieved.

The foregoing shows that the particular method of the invention relating to laser angioplasty has implications in a broader sense, such as to clinical treatment of medical problems in general, where actions must be taken—particularly in the area of surgery—based upon the collection and analysis of data relating to the patient. Other variations on the foregoing are possible to accommodate different types of tasks .

Although the invention has been described in terms of the preferred and alternative embodiments described herein, those skilled in the art will appreciate other modifications which could be made without departing from the true spirit and scope of the invention. All such modifications are intended to be included within the scope of the claims appended hereto.

O 90/05563

Clinical Cardiology: Laser and Radio Frequency Angioplasty

In Vivo Coronary Plaque Recognition by Laser-Induced Fluorescence Spectroscopy.

AL Bartorelli, Y Almagor, LG Prevosti, JA Swain, CL Mclntosch, PD Smith, RF Bonner, MB Leon. NHLBI, Bethesda, MD

Previously, in 48 pts, we have shown that laser (L)- induced fluorescence (F) spectroscopy can differentiate atheroma (A) from normal (n) sites. To establish recognition parameters for F guided L coronary (C) angioplasty, we studied 11 additional C pts (48+^13 yrs) in the operating room using a HeCd L (325nm @ 3mW) for F excitation with optical multichannel F analysis. Excitation and F light was transmitted via a 200u optical fiber to and from C sites, labelled either N or A based upon visual inspection. F spectra analysis included peak position (PP), spectra shape index (SI) and normalized intensity (NI) .

PP(nm) SI NI

N (n-29) 462+2 0.7+0. 358+125

++ non-Ca

(n-15) 466+4* 6.7+3.7- 230+82-

Ca^+ (n-7)456+8^ 2.2+1. α*-*- 175+93*

4-+

*p<.001 vs N, **p<.01 vs p<.05 vs A-Ca^" . Using an advanced algorithm (A detection criteria-453<PP>465 or SI>2, and NK380), the specificity and sensitivity for a recognition was 100. and 91%. A sites not detected were always from Ca lesions. We conclude that in vivo F spectroscopy of C discriminates A from N tissue with high specificity and sensitivity and can be utilized for real-time guidance during L angioplasty.

APPENDIX A

Claims

05563

laser light to the tissue generating said fluorescent return light if the comparison of said heme stain factor to said heme stain factor threshold indicates that the fluorescent return light may have originated from healthy tissue.

7. An apparatus for ablating diseased tissue in the body by irradiation with laser light, comprising: means for exciting to fluorescence tissue in a body by irradiation by laser light; means for comparing the spectral characteristics of the fluorescent return light to compare the peak intensity, peak wavelength and spectral shape to known standards and for determining whether or not to fire a treatment laser at the tissue which emitted said fluorescent return light; and control means in said comparison means for controlling a treatment laser to emit light energy when a decision to fire said treatment laser is made.

8. The apparatus of claim 7, wherein said means for comparing includes means for storing a composite fluorescent light reference spectrum for healthy tissue computed as the average of a plurality of fluorescent light spectra of healthy tissue which have been normalized to said composite reference spectrum peak intensity and shifted to the position of best fit as indicated by the smallest least squares residual. ■

9. The apparatus of claim 8, wherein said means for comparing includes means for storing predetermined upper and lower intensity threshold values and means for finding the peak intensity value. 10. The apparatus of claim 9, wherein said means for comparing includes means for determining the wavelength of peak intensity for said fluorescent return light by fitting a parabola to the spectrum of said fluorescent return light, and wherein said means for stor¬ ing includes means for storing the range of wavelengths encompassing all the peak intensity values of said individual healthy tissue fluorescent spectra which were averaged to compute said composite reference spectrum for healthy tissue, said means for comparing including means for determining if the wavelength at the peak intensity of said return light spectrum is within the range of wavelengths in which all the peak intensities of said individual healthy tissue spectra were found and means for causing said control means to' prevent said treatment laser from being fired if said peak of the return light spectrum is found to be within the wavelength range of peaks for the healthy tissue spectra.

11. The apparatus of claim 10, wherein said means for storing includes means for storing a shape threshold defining the worst fit of any of said healthy tissue spectra averaged to form said composite healthy tissue reference spectrum, and wherein said means for comparing includes means for computing the least squares residual for the best fit between the fluorescent return light spectrum and said composite reference spectrum and for comparing the least squares residual so computed to said shape threshold and for causing said control means to fire said treatment laser if the best fit between said fluorescent return light spectrum and said composite reference spectrum is worse than the worst fit of a healthy tissue spectrum used to compute said composite reference spectrum. /05563

12. The apparatus of claim 11, further compris¬ ing means in said means for comparing to determine the ratio of intensity at a predetermined wavelength less than the wavelength of the peak intensity to the intensity at the peak for said fluorescent return light and to determine the same ratio for said composite reference spectrum and for comparing said ratios to each other and to a predetermined heme stain threshold and for causing said control means to prevent said treatment laser from firing if said comparison of ratios indicates that the tissue emitting said fluorescent return light may be healthy tissue with heme stain absorption.

13. An apparatus for discriminating between normal tissue and diseased tissue and for firing a laser pulse at tissue deemed to be diseased tissue, comprising: excitation means for guiding excitation light to a site of a surgical procedure and for guiding fluorescent light caused by said excitation light to a return light output; first means coupled to said light output for comparing a peak fluorescent intensity and a wavelength at said peak intensity for said return light from said surgi- cal procedure site to predetermined criteria; second means coupled to said first means for comparing a shape of a fluorescent light spectrum of said return light to a shape of a composite healthy tissue spectrum to determine if the shapes resemble each other within a predetermined degree of similarity, If said first means determines that said predetermined criteria are met; and means for guiding treatment laser light to said surgical procedure site if said first and second means determine that said predetermined criteria are met and that said shapes do not match each other within said pre¬ determined degree of similarity.

14. A method of generating reference data for use in making discrimination decisions for control of a treatment laser in firing at diseased tissue but not at healthy tissue, comprising the steps of: exciting a plurality of samples of healthy tis¬ sue to fluorescence with excitation light; detecting the intensity spectrum of fluorescent light emitted from each said sample of said healthy tissue at a plurality of frequencies; finding the peak intensity of each said spectrum; assigning one said spectrum as an initial composite reference spectrum; normalizing each said spectrum to the peak intensity of said initial composite reference spectrum; computing a plurality of least squares residuals for each spectrum at a corresponding plurality of shifted wavelength positions for each spectrum to find the best fit between each said spectrum and said initial composite reference spectrum; shifting each said spectrum to the position of its best fit; and averaging all of the spectra with said initial composite reference spectrum to derive a final composite reference spectrum.

15. The method of claim 14, wherein the step of finding the peak intensity of each said spectrum comprises the step of fitting a parabola to each said spectrum using the least squares residual method. 16. The method of claim 14, further comprising the step of determining the range of wavelengths which includes all the wavelengths at which peak intensities occurred for the spectra used to form said final composite reference spectrum and storing said range as peak position range.

17. The method of claim 14, further comprising the step of determining the minimum least squares residual for the best fit of the worst fitting spectrum used to compute said final composite reference spectrum and stor-. ing same as a shape threshold.

18. The method of claim 14, further comprising the steps of computing the ratio of intensity at 425 nm to the peak intensity at .the peak for .said final composite reference spectrum and computing the same ratio for heme stained normal tissue and comparing the two ratios mathematically to derive a heme stain threshold.

19. A method of distinguishing between healthy tissue and diseased tissue, comprising the steps of: illuminating the tissue to be distinguished with excitation light; detecting the fluorescent return light spectrum; comparing the peak intensity, peak wavelength and shape of the fluorescent light spectrum to pre¬ determined reference data; and guiding treatment laser light to said tissue if said comparison indicates that diseased tissue caused said fluorescent return light.

20. A method of distinguishing between healthy tissue and diseased tissue, comprising the steps of: (1) guiding excitation light to illuminate the tissue to be distinguished;

(2) guiding fluorescent return light resulting from said excitation light to a detector;

(3) determining the fluorescent intensity spectrum for said return light at a plurality of wavelengths;

(4) determining the peak intensity and the wavelength at said peak intensity for said fluorescent return light spectrum;

(5) comparing the peak intensity to a^' pre¬ determined intensity range;

(6) if said peak intensity is within said pre¬ determined intensity range, comparing the wavelength at said peak to a predetermined range of wavelengths, and, if said peak intensity is not within said predetermined intensity range, returning to step 1;

(7) if^■ said peak wavelength is within said pre¬ determined range of wavelengths, comparing the shape of said fluorescent return light spectrum to a composite reference spectrum for healthy tissue to generate a shape similarity factor and comparing this shape similarity fac¬ tor to a shape threshold, and, if said peak wavelength is not within said predetermined range of wavelengths, guid¬ ing treatment laser light to ablate the tissue causing said fluorescent return light;

(8) if the shape of said return light spectrum fits the shape of the composite reference light spectrum such that said shape similarity factor is within said shape threshold, returning to step 1, and, if the shape threshold is exceeded, guiding treatment laser light to ablate the tissue causing said fluorescent light.

21. The method of claim 20, wherein steps 1 and 2 are carried out by guiding both said excitation light and said return light, respectively, over a single optical fiber.

22. The method of claim 20, wherein the step of determining the peak fluorescent intensity of said return light comprises the step of fitting a parabola to said fluorescent return light spectrum by a least squares residual method.

L0

23. The method of claim 22, wherein step 5 comprises comparing the peak intensity of said fluorescent return light to determine if a minimum intensity threshold, set to ensure adequate signal-to-noise ratio,

15 is exceeded and comparing the peak intensity of said fluorescent return light to determine if the peak intensity is less than or equal to a maximum intensity threshold, set to ensure that fluorescent return light from healthy tissue, which is normally of greater

20 intensity than fluorescent return light from diseased tis¬ sue, is not mistaken for diseased tissue and ablated.

24. The method of claim 23, wherein step 6 comprises the steps of comparing the wavelength at the

25 peak for said fluorescent return light to a range of wavelengths including wavelengths at the peaks of a plurality of healthy tissue fluorescent spectra, which are averaged after normalization, and curve fitting to form said composite reference spectrum.

30

25. The method of claim 24, wherein step 8 comprises normalizing said fluorescent return light spectrum to said composite reference spectrum and finding the best fit between the two spectra using a least squares

35 residual method and comparing the minimum least square residual to a curve shape threshold, said curve shape threshold being indicative of the worst fit between any of the normal tissue spectra used to compute said composite reference spectrum and said composite reference spectrum.

26. A method for optimizing clinical treatment of a patient suspected of having a given condition, comprising the steps of: collecting from the patient diagnostic data expected to relate to the given condition; selecting a first technique for treatment of the given condition; analyzing the data and developing therefrom a process for clinical treatment based upon the technique selected; applying the process to the diagnostic data and obtaining a first analysis result; ^• comparing results of the step of applying the process to known cases .of the condition for determining whether the process discriminates between presence and absence of the condition; if the comparing step indicates insufficient discrimination, altering the process such that satisfac¬ tory discrimination is achieved.

27. The method of claim 26, wherein the diagnostic data includes data relating to both presence and absence of the condition in actual clinical tests.

28. The method of claim 27, including, before the step of collecting diagnostic data, the step of selecting hardware for the treatment.

29. The method of claim 28, including, before the step of collecting diagnostic data and after the step of selecting hardware, the step of testing whether the /05563

selected hardware requires manipulation of the diagnostic data, and if so, manipulating the data to compensate for biasing of the data due to the selected hardware.

30. The method of claim 26, including, after the comparing step and before the process altering step, the step of altering hardware parameters for resolving the insufficient discrimination.

31. A method for the ablation of abnormal tis¬ sue in a patient, comprising the steps of:

(1) irradiating normal tissue with a first diagnostic medium for producing first return light from the normal tissue;

(2) generating a first spectrum from' the first return light;

(3) irradiating a sample of tissue with the first diagnostic medium for producing second return light from the sample tissue;

(4) generating a second spectrum from the second return light;

(5) standardizing the second spectrum to the first spectrum; (6) comparing the shapes of the first and second spectra, for generating a first variable relating to how closely the shapes coincide;

(7) comparing the first variable with a pre- ' determined first threshold; > (8) based on step 7, determining whether the tissue sample is normal; and

(9) if the tissue sample Is determined to be abnormal, ablating at least a portion of the sample.

32. The method of claim 31, Including, after step 5 and before step 6, the step of: (10) comparing at least a portion of the first and second spectra for determining whether blood is present with the tissue sample.

33. The method of claim 32, wherein, if blood is determined to be present with the tissue sample in step 10, step 6 comprises comparing the first and second spectra at wavelength ranges of the spectra where influ¬ ence to their respective shapes due to the presence of blood is minimized.

34. The method of claim 31, including, after step 2 and before step 3, the step of:

(11) normalizing the first spectrum by determin¬ ing a peak position value for the first spectrum and dividing each value in the spectrum by the peak position value.

35. The method of claim 31, wherein step 5 includes the step of: ,

(12) normalizing the second spectrum to the first spectrum by determining a first peak position value for the first spectrum, determining a second peak position value for the second spectrum, and multiplying each value in the second spectrum by the ratio of the first peak position value to the second peak position value.

36. The method of claim 35, including, after step 6 and before step 7, the step of:

(13) shifting the second spectrum along an axis representing frequency of the return light.

37. The method of claim 36, including, after step 13 and before step 7, .the steps of: (14) repeating each of steps 6 and 13 for a pre¬ determined number of times, each time shifting the second spectrum by a different amount and each time generating a new value for the first variable; and

(15) determining which of the values of the first variable so generated is smallest of all the gener¬ ated values; and

( 16 ) shifting the second spectrum by the amount represented by the smallest generated first variable.

38. The apparatus of claim 9, wherein: said finding means is for generating a parabola fitted to said return light spectrum for accurately determining said peak intensity value; said comparing means includes means for compar¬ ing said peak intensity value to a range defined by said upper and lower intensity threshold values and for preventing said control means from firing said treatment laser if the peak intensity of said return light is either less than said lower intensity threshold or greater than said upper intensity threshold.

39. The apparatus of claim 38, wherein said finding means includes means for generating said parabola by a least squares residual method of curve fitting.

40. The method of claim 20, wherein steps 1 and 2 are carried out by guiding said excitation light over at least a first optical fiber and by guiding said return light over at least a second optical fiber, respectively.

41. The method of claim 33, wherein said wavelength ranges of the spectra are at wavelengths substantially different from approximately 412 nm. 42. The method of claim 33, wherein said wavelength ranges of the spectra are at wavelengths substantially greater than approximately 412 nm.

43. A method for ablating abnormal tissue at a treatment site within a patient, including the steps of:

(1) illuminating a first sample of normal tissue with first laser light at a first wavelength;

(2) detecting first return light from said first sample;

(3) generating a first normal tissue spectrum from said first return light;

(4) repeating steps 1-3 for each of a plurality of samples of normal tissue, for generating additional normal tissue spectra;

(5) generating a first sum of all of said normal tissue spectra generated in steps 1-4;

(6) dividing said first sum by the total number of normal tissue spectra summed for generating a composite spectrum;

(7) generating an acceptable peak wavelength range for said composite spectrum;

(8) generating an acceptable signal intensity range for values in said normal tissue spectrum, including generating a minimum acceptable intensity and a maximum acceptable intensity;

(9) determining a heme stain. threshold relating to the effect of the presence of blood on a return light spectrum from given tissue;

(10) illuminating an unknown tissue sample at said treatment site with said laser light at said first wavelength;

(11) detecting second return light from said unknown tissue sample; (12) generating a sample tissue spectrum from said second return light;

(13) determining an Intensity of a peak of said sample tissue spectrum;

(14) determining a sample tissue peak wavelength at which said sample tissue spectrum tissue peak intensity occurs;

(15) determining whether said sample tissue spectrum peak intensity is within said acceptable signal intensity range, and if not, then proceeding to step 21;

(16) generating a heme stain factor for sample tissue spectrum;

(17) comparing said heme stain factor with said heme stain threshold for determining whether blood is present with said unknown tissue sample, and if blood is present, then compensating therefor in each of steps 18 through 19 below;

(18) determining whether said sample tissue peak wavelength is within said acceptable peak wavelength range, and if it is not, then irradiating said treatment site with second laser light at a second wavelength;

(19) generating a tissue index relating to how closely said sample tissue spectrum matches said composite spectrum;

(20) comparing said tissue index with a pre-

„ determined normal tissue index, and if said tissue index is outside a normal range as indicated,by said normal tis¬ sue index, then irradiating said treatment site with said laser light at said second wavelength; and

(21) storing a cumulative number of times said treatment site was irradiated with said laser light at said second wavelength.

44. The method of claim 43, wherein said first wavelength is approximately 325 nm. 45. The method of claim 43, wherein said first wavelength is approximately 337 nm.

46. The method of claim 43, wherein at least some of said samples of normal tissue are in vitro.

47. The method of claim 46, wherein said composite spectrum is compensated for effects of the pres¬ ence of blood in said i.n vitro samples of said normal tis¬ sue and for effects of aging of said in vitro samples.

48. The method of claim 43, wherein at least some of said samples of normal tissue are in vivo.

49. The method of claim 48, wherein at least some of said in vivo samples are from the patient under treatment .

50. The method of claim 43, wherein said first return light includes fluorescent lignt.

51. The method of claim 43, wherein said first return light includes reflected light.

52. The method of claim 43, wherein step 3 includes the step of guiding said return light into a spectrometer for generating said first. normal tissue spectrum. '

53. The method of claim 43, wherein step 3 further includes the step of:

(22) detecting an intensity value of said return light at each of a plurality of wavelengths. 54. The method of claim 53, wherein step 3 further includes the step of normalizing said first normal tissue spectrum, said normalizing step including the steps of:

(23) determining a peak intensity value for said first normal tissue spectrum; and

(24) dividing each of said intensity values by said peak intensity value.

55. The method of claim 54, including, after step 22 and before step 23, the step of fitting said first normal tissue spectrum to a parabola.

56. The method of claim 55, wherein said fit¬ ting step is carried out using a least squares curve fit¬ ting method.

57. The method of claim 54, further including, after step 4 and before step 5, the steps of:

(25) determining a peak wavelength value for each of said normal tissue index spectra, each said peak wavelength value corresponding to said peak intensity value for one said normal tissue index spectrum; and

(26) shifting each normal tissue index spectrum such that each said peak wavelength value substantially coincides with the peak wavelength value of said first normal tissue spectrum.

58. The method of claim 57, wherein step 26 is accomplished by a least squares method.

59. The method of claim 57, wherein: step 26 includes the step of determining, for each of several values for j, the smallest value for R(j₎ in the equation R(j) = Sum over i of (I(i+j) - C(i))2, where i= a wavelength, and goes from the lowest wavelength to the highest wavelength for a given spectrum, j= an offset for wavelength i, I(i+j)= the intensity of the spectrum being shifted at wavelength (i+j), and 0 C(i)= the intensity of the first normal index spectrum at wavelength (j ) ; and ■ step 5 is carried out using said smallest value of R(j) for each said normal tissue index spectrum.

-5 60. The method of claim 59, further including, after step 6 and before step 7, the step of compensating for biasing of said composite spectrum due to use of a given normal tissue spectrum as said first normal tissue spectrum. 0

61. The method of claim 60, wherein said compensating step includes the steps of:

(27) repeating each of steps 1 through 4, 25, 26, 5 and 6 a plurality of times, wherein for each repeti¬ 5 tion a different one of said additional normal tissue spectra is utilized in place of said first normal tissue spectrum, thus generating a plurality of composite spectra;

(28) averaging all of the composite spectra so 0 generated for generating an averaged composite spectrum, and in subsequent steps utilizing said averaged composite spectrum as said composite spectrum.

62. The method of claim 61, wherein step 27 is 5 carried out with each said additional normal tissue spectrum being used once in place of said first normal tissue spectrum.

63. The method of claim 43, wherein step 7 is carried out by determining a lowest wavelength value and a highest wavelength value at which peaks occur in said normal tissue spectra used to generate said composite spectrum.

^■64. The method of claim 43, wherein the minimum acceptable intensity has a signal to noise ratio above a predetermined minimum signal to noise ratio.

65. The method of claim 43, wherein the maximum acceptable intensity is below a predetermined saturation intensity.

66. The method of claim 43, wherein said second, return light includes fluorescent light.

67. The method of claim 43, wherein said second return liglit includes reflected light.

68. The method of claim 43, wherein step 12 Includes the step of guiding said return light into a spectrometer for generating said sample tissue spectrum.

69. The method of claim 68, wherein each of steps 3 and 12 includes the step of compensating for a background signal.

70. The method of claim 69, wherein said compensating step includes the step of subtracting from said normal tissue spectra and said sample tissue spectrum, respectively, a signal detected by said spectrometer when return light from tissue is prevented from entering said spectrometer.

71. The method of claim 43, wherein, if in step 15 it is determined that said sample tissue spectrum peak intensity is not within said acceptable range, step 15 further includes, before proceeding to step 21, the steps of:

(29) determining whether summing a predetermined number of adjacent values in said sample tissue spectrum will result in summed intensities which are within said acceptable signal intensity range;

(30) if the determination in step 29 is af¬ firmative, then so summing said predetermined number of adjacent values for a plurality of blocks of values in said sample tissue spectrum, and substituting said summed values for the values originally in said sample tissue spectrum; and

(31) if the determination in step 29 is negative, then proceeding to step 21. ^•

72. The method of claim 71, wherein said pre¬ determined number of adjacent values is any one of 2, 4 and 8.

73. The method of claim 55, further including, after step 15 and before step 16, the steps of:

(32) determining the accuracy of fit of said first normal tissue spectrum to said parabola;

(33) if said accuracy is below a predetermined threshold, then proceeding to step 21; and

(34) if said accuracy is not below said pre¬ determined threshold, then proceeding to step 16. 74. The method of claim 43, wherein said heme stain factor comprises a ratio of: the peak intensity value for said sample tissue spectrum, divided by the intensity value of said sample tissue spectrum at a third wavelength to the peak intensity value of said composite spectrum, divided by the intensity value of said composite spectrum at said third wavelength.

75. The method of claim 74, wherein said third wavelength is approximately 412 nm.

76. The method of claim 43, wherein said compensating step of step 17 includes, for step 18, utilizing an expanded peak wavelength range which is slightly larger than said acceptable peak wavelength range which is used when no blood is determined to be present.

77., The method of claim 43, wherein said compensating step of step 17 includes, in step 19, generating said tissue index only for wavelengths of said sample tissue spectrum which are substantially different from wavelengths affected by the presence of blood.

78. The method of claim 43, wherein said tissue index is generated only .for waveleng^'t s greater, than said sample tissue peak wavelength.

79. The method of claim 43, wherein said ir¬ radiating step of step 18 includes adjusting an output of said second laser light for accommodating particular types of tissue to be ablated. 80. The method of claim 43, wherein said first and second wavelengths are substantially equal.

81. The method of claim 43, wherein said tissue index is generated according to the formula:

82. The method of claim 43, further including the step of repeating each of steps 1 through 21 for a predetermined number of times.

83. The method of claim 43, further including the step of repeating each of steps 1 through 21 until an operator halts the method.

84. The method of claim 24, wherein said range of wavelengths encompasses substantially all of said wavelengths at which said peaks of said plurality of healthy tissue fluorescent spectra occurred.

85. The method of claim 31, wherein the first diagnostic medium is also a treatment medium, such that step 3 comprises the step of treating the sample of tissue by irradiation with the first diagnostic medium.

86. The method of claim 40, wherein step 1 is carried out by guiding said excitation light over an opti¬ cal fiber.

87. The method of claim 40, wherein step 2 is carried out by guiding said return light over a plurality of optical fibers .

88. The method of claim 20, wherein steps 1 and 2 are carried out by guiding said excitation light over a plurality of first optical fibers and by guiding said return light over a plurality of second optical fibers, respectively.

89. The method of claim 43, including, after step 13, the step of adjusting the maximum acceptable intensity such that it is no greater than approximately twice the intensity of the peak of the sample tissue spectrum.

90. The method of claim 69, wherein the compensating step includes the step of compensating for electromagnetic background radiation.

91. The method of claim 69, wherein the compensating step includes the step of compensating for optical background radiation.

92. The method of claim 43, wherein step 8 includes the step of selecting the minimum acceptable intensity in an intensity range wherein contrast of images is within a predetermined contrast range.

93. The method of claim 43, wherein step 8 includes the step of selecting the maximum acceptable intensity in an intensity range wherein contrast of images is within a predetermined contrast range.

94. The method of claim 20, wherein step 2 includes the step of modifying the fluorescent intensity spectrum according to calibration data relating to a standard light source.

95. The method of claim 31, wherein the first diagnostic medium comprises a broadband source of light, and wherein the first return light and the second return light include reflected light.

⁵ 96. The method of claim 95, wherein the broadband source of light comprises white light.

97. A method for the ablation of abnormal tis¬ sue in a patient, comprising the steps of:

(1) exposing normal tissue to a first diagnostic medium for producing a first return signal from the normal tissue;

(2) generating first data from the first return signal; c

(3) exposing a sample of tissue to the first diagnostic medium for producing a second return signal from the sample.tissue;

(4) generating second data from the second

^• return signal; 0 (5) standardizing the second data to the first data;

(6) comparing the shapes of the first and second data, generating a first variable relating to how closely the shapes coincide; 5 (7) comparing the first variable with a pre¬ determined first threshold;

(8) based on step 7, determining whether the tissue sample is normal; and

(9) if the tissue sample is determined to be 0 abnormal, ablating at least a portion of the sample.

98. The method of claim 97, wherein the first diagnostic medium includes electromagnetic radiation.

5 99. The method of claim 97, wherein the first diagnostic medium includes laser light. 100. The method of claim 97, wherein the first diagnostic medium includes white light.

101. The method of claim 97, wherein the first diagnostic medium includes an ultrasonic signal.

102. The method of claim 97, wherein the first and second data comprise magnetic resonance signals.

103. The method of claim 98, wherein the first diagnostic medium also includes an ultrasonic signal, for generating return data from the sample of tissue over a wide angle field- utilizing the ultrasonic- signal and for generating return data from the sample of tissue over a relatively narrow angle field utilizing the electro¬ magnetic signal.

104. The method of claim 103, wherein the first and second return data comprise fluorescent electro¬ magnetic data.

105. The method of claim 31, including, before step 3, the steps of: positioning a means for transmitting the first diagnostic medium near the sample of tissue; and generating an image of the transmitting means for ensuring proper placement thereo^'f. ,

106. The method of claim 105, wherein the image is generated by ultrasound.

107. The method of claim 105, wherein the Image is generated by magnetic resonance. 108. The method of claim 97, wherein each of steps 1 and 2 includes the step of controlling at least one characteristic of the first diagnostic medium for producing return signals within a predetermined intensity range.

109. The method of claim 108, wherein the controlling step includes controlling a period of exposure of the first diagnostic medium.

110. The. method of claim 108, wherein the first diagnostic medium is applied in a pulsed fashion, and the controlling step includes controlling pulse widths of the first diagnostic medium.

111. The method of claim 108, wherein the first diagnostic medium is applied in a pulsed fashion, and the controlling step includes controlling a pulse rate of the first diagnostic medium.

112. The method of claim 97, wherein step 9 includes the step of ablating the portion of the sample by application of a treatment medium.

113. The method of claim 112, including controlling at least one characteristic of the treatment medium for adjusting the amount of ablation of the sample.

114. The method of claim 113, wherein the treatment medium is characterized at least in part by a wavelength, and the controlling step includes the step of controlling the wavelength.

115. The method of claim 113, wherein the treatment medium is applied in a pulsed fashion, and the controlling step includes the step of controlling pulse widths of the treatment medium.

116. The method of claim 113, wherein the treatment medium is applied in a pulsed fashion, and the controlling step includes the step of controlling a pulse rate of the treatment medium.

117. The method of claim 113, wherein the treatment medium is applied in a pulsed fashion, and the controlling step includes the step of controlling pulse energies of the treatment medium.

118. The apparatus of claim 13, further includ¬ ing: a shutter positioned between said excitation means and said surgical procedure site; and means for opening said shutter for passing said excitation light to said site and for passing fluorescent light to said return light output, and for closing said shutter while said treatment laser light is guided to said surgical procedure site.

119. The method of claim 31, wherein step 9 is carried out using a treatment medium, and further includ¬ ing: before step 1, the steps of (10) preventing pas¬ sage of the treatment medium to the sample and (11) allow¬ ing unobstructed passage of the diagnostic medium to the sample;

(12) after step 3, the step of preventing pas¬ sage of the diagnostic medium to the sample; and

(13) before step 9, the step of allowing unobstructed passage of the treatment medium to the sample. 120. The method of claim 119, wherein: step 10 includes the step of positioning a first shutter between the treatment medium and the sample; step 12 includes the step of positioning a second shutter between the diagnostic medium and the sample; step 11 includes the step of removing the second shutter from its position between the diagnostic medium and the sample; and step 13 includes the step of removing the first shutter from its position between the treatment medium and the sample.

121. The method of claim 31, including, before step 1, the steps of: generating a spectrum from a reference material; and comparing the spectrum generated from the refer¬ ence material with a predetermined spectrum fro . the reference material, for determining whether apparatus used in carrying out the method are operating within pre¬ determined quality control criteria.

122. The method of claim 121, wherein the reference material is phosphor.

123. The method of claim ^'31, including, after step 5 and before step 6, the step of displaying the second spectrum.

124. The method of claim 31, including the step of repeating steps 3 through 9 for a plurality of times.

125. The method of claim 124, wherein the plurality of times is a predetermined number of times. 126. The method of claim 124, wherein the repeating step is carried out until the second spectrum -^> generated in step 4 indicates the presence of normal tis¬ sue.

127. The method of claim 124, wherein the repeating step is carried out automatically by treatment 0 apparatus until an operator of the apparatus interrupts the method.

128. The method of claim 124, further includ¬ ing, after at least one repetition of steps 3 through 9, -' the step of comparing the second spectra generated in each ^• of two successive cycles of carrying out steps 3 through 9 for determining an amount of variation between the succes¬ sive second spectra.

0 129. The method of claim 128, wherein-the comparing step includes the step of generating a least squares analysis of the successive second spectra.

130. The method of claim 128, wherein the 5 comparing step includes the step of generating a ratio of the two successive spectra.

_

131. The method of claim ^'128, including, after the step of comparing the two successive second spectra, 0 'the step of halting the method if the variation is outside a predetermined acceptable range.

132. The method of claim 31, wherein step 6 includes the step of comparing ratios of the first and

35 second spectra. 133. The method of claim 31, wherein step 6 includes the step of comparing widths of the first and second spectra.

134. The method of claim 31, wherein step 6 includes the step of comparing slopes of portions of the first and second spectra.

135. The method of claim 31, wherein step 6 includes the step of comparing areas defined by graphic representations of the first and second spectra.

136. The method of claim 31, wherein step 6 includes the step of comparing intensities of the first and second spectra.

137. The method of claim 31, including, after step 6 and before step 7, the step of shifting the second spectrum along an axis representing frequency of the return light.

138. The method of claim 137, including, after step 6 and before the shifting step, the step of generat¬ ing a shifting distance for the second spectrum by compar¬ ing curve-fitted peaks of the first and second spectra, respectively.

139. The method of claim 137, including, after step 6 and before the shifting step, the step of generat¬ ing a shifting distance for the second spectrum by compar¬ ing true peaks of the first and second spectra, respectively.

140. The method of claim 137, including, after step 6 and before the shifting step, the step of generat- ing a shifting distance for the second spectrum by compar¬ ing centroids of the first and second spectra, respectively.

141. The method of claim 97, further including the steps of:

(10) after step 2 and before step 3, positioning a means for transmitting an imaging medium near the sample of tissue; and, after step 10 and before step 9:

(11) exposing a field of view to the imaging medium;

(12) generating an image of the field of view; and

(13) determining whether the position of the imaging medium has changed by more than a predetermined amount.

142. The method of claim 141, further includ¬ ing, after step 13 and before step 10, the step of: if the determination of step 13 is affirmative, skipping^' step 9 of the method.

143. The method of claim 142, wherein the imag¬ ing medium comprises ultrasound, and the transmitting means includes an ultrasound transducer.

144. The method of claim^"142, wherein the imag¬ ing medium comprises magnetic resonance, and the transmit¬ ting means includes a magnetic resonance transducer.

145. The method of claim 142, wherein the imag¬ ing medium comprises an optical signal, and the transmit¬ ting means includes a lens . 146. The apparatus of claim 13, further includ¬ ing: means for transmitting an imaging medium to said site of said surgical procedure; means, coupled to said transmitting means, for generating an image of a field of view of said site by means of said imaging medium; means, coupled to said image generating means, for determining whether said field of view has changed; and means, coupled to said determining means, for preventing said laser light from firing, if said field of view has changed.

147. The apparatus of claim 146, wherein said imaging medium is ultrasound.

148. The apparatus of claim 146, wherein said image generating means includes a sonic transducer.

149. The .apparatus of claim 146, wherein said imaging medium is magnetic resonance.

150. The apparatus of claim 146, wherein said image generating means includes a magnetic resonance transducer.

151. The apparatus of claim 146, wherein said imaging medium is an optical signal.

152. The apparatus of claim 146, wherein said image generating means includes an optical transducer.

153. The apparatus of claim 146, wherein said transmission means is attached to said excitation means. 154. The method of claim 100, wherein the first diagnostic medium also includes laser light.

155. The method of claim 154, wherein step 3 comprises the step of alternately exposing the sample of tissue to the white light and to the laser light.

156. The apparatus of claim 13, wherein said excitation light includes both laser light and white light.

157. The apparatus of claim 156, wherein said excitation means is for guiding said laser light and said white light to said site in an alternating manner.

158. The method of claim 31, including, before step 3, the steps of: positioning a means for transmitting the first diagnostic medium near the sample of tissue; and generating a spectrum of the transmitting means for ensuring proper placement thereof.

159. The apparatus of claim 13, further includ¬ ing means for displaying said fluorescent light spectrum and said healthy tissue spectrum.

160. The apparatus of claim.146, further including means, coupled to said image generating means, for displaying an image of said field of view.

161. The apparatus of claim 160, wherein said displaying means is also for displaying said fluorescent light spectrum and said healthy tissue spectrum. 162. The apparatus of claim 13, further includ¬ ing a shutter removably positioned for preventing light from reaching said first and second comparing means .

163. The apparatus of claim 13, further includ¬ ing: a detector for receiving said light output and for generating said fluorescent light spectrum from said return light.

164. The apparatus of claim 163, further including a shutter removably positioned near said detec¬ tor for preventing light from reaching said detector.

165. The apparatus of claim 13, further includ¬ ing a shutter removably positioned between said excitation means and said site of said surgical procedure.

166. The method of claim 31, further including the steps of:

(10) after step 3 and before step 4, receiving the second return light in a detector; and

(11) during steps other than step 10, preventing light from reaching the detector.

167. The method of claim 166, wherein step 11 includes the step of positioning a shutter near the detec¬ tor.

168. The method of claim 31, wherein step 8 includes the step of determining whether the tissue sample is thrombus . 169. The method of claim 168, wherein the determining step is carried out by determining whether the second spectrum is a double-peaked spectrum.

170. The method of claim 113, wherein the treatment medium is characterized at least in part by a power, and the controlling step includes the step of controlling the power.

171. The method of claim 170, wherein: step 8 includes determining whether the tissue sample includes soft diseased material; and the controlling step includes lowering the power of the treatment medium if it is determined that the tis¬ sue sample includes thrombus.

172.- The method of claim 171, wherein step 8 includes determining whether the second spectrum is double peaked.

173. An apparatus for discriminating between normal tissue and diseased tissue and for firing a laser pulse at tissue deemed to be diseased tissue, comprising: excitation means for guiding a first diagnostic medium to a site for a surgical procedure and for guiding a return signal generated by said excitation light to a return signal output; first means coupled to said output for comparing a peak intensity of said return signal and a position of said peak Intensity to predetermined criteria; second means coupled to said first means for comparing a shape of said return signal a shape of a signal obtained from healthy tissue for determining whether said shapes resemble each other within a pre- determined degree of similarity, if said first means determines that said predetermined criteria are met; and means for guiding a treatment medium to said surgical procedure site if said first and second means determine that said predetermined criteria are met and that said shapes do not match each other within said pre¬ determined degree of similarity.