(Circulation. 1999;100:1236-1241.)
© 1999 American Heart Association, Inc.
Basic Science Reports |
New Method for Detection of Heart Allograft Rejection
Validation of Sensitivity and Reliability in a Rat Heterotopic Allograft Model
From Biomax Technologies, Inc, Vancouver, BC (D.C.M., P.S.G., P.D.W., C.R.T.); Department of Pathology and Laboratory Medicine, St. Paul's Hospital–University of British Columbia, Vancouver, BC (J.E.W., J.A.K., C.D., B.M.M.); Cancer Imaging, BC Cancer Agency, Vancouver, BC (C.E.M., N.B.M., H.Z.); and Division of Cardiology, St. Paul's Hospital, University of British Columbia, Vancouver, BC (C.R.T.).
Correspondence to Bruce M. McManus, MD, PhD, St. Paul's Hospital–University of British Columbia, 1081 Burrard St, Vancouver, BC V6Z 1Y6. E-mail mcmanus{at}interchange.ubc.ca
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Abstract |
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Background—Patients with inflammatory heart muscle diseases would benefit from a safe, convenient, rapidly performed diagnostic technique with real-time results not involving tissue removal. We have performed a detailed evaluation of detection of heart allograft rejection by autofluorescence in a heterotopic abdominal rat heart allograft model ex vivo.
Methods and Results—Recipient rats with allograft (Lewis to Fisher 344; n=71) and isograft (Lewis to Lewis; n=33) hearts, treated with cyclosporine or untreated, were killed at days 2, 4, 7, 14, 21, 28, and 56 after transplant. Nontransplant controls with (n=24) or without (n=24) immunosuppressive therapy were also studied. When the rats were killed, autofluorescence spectra were acquired under blue-light excitation from midtransverse ventricular sections of native and transplanted hearts. Corresponding sections were then evaluated pathologically by a modified International Society for Heart and Lung Transplantation (ISHLT) grading schema. The spectral differences between rejecting and nonrejecting hearts were quantified by linear discriminant functions, producing scores that decreased progressively with increasing severity of tissue rejection. Mean±SD discriminant function scores were 2.9±1.6, 1.8±2.2, -0.1±2.8, -1.2±2.3, and -2.3±3.0 for isografts and allograft ISHLT grades 0, I, II, and III, respectively (Spearman rank-order correlation -0.6; P<0.001, test for trend). Cyclosporine had no detectable effect on the spectra.
Conclusions—The correlation between changes in autofluorescence spectra and ISHLT rejection grade strongly supports the possibility of catheter-based, fluorescence-guided surveillance of rejection.
Key Words: transplantation • rejection • biopsy • spectroscopy
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Introduction |
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Amajor challenge in cardiac transplantation is prevention and surveillance of acute graft rejection.1 Maintenance of immunosuppression at the appropriate level to protect an allograft from the alloimmune response requires a reliable method for allograft surveillance and early recognition of acute rejection. Histological grading of the rejection process in endomyocardial biopsy specimens2 3 currently guides antirejection therapy. Many centers perform routine surveillance biopsies up to 18 times in the first year and annually thereafter, in addition to biopsies for clinically suspected rejection. Methods that provide immediate, accurate results with limited invasiveness, reduced risks, and less inconvenience to the patient would be attractive alternatives to the endomyocardial biopsy.4 5 To date, surface and intracardiac ECGs,6 7 echocardiographic parameters including 2D and Doppler measures of systolic and diastolic function,8 9 10 11 and radionuclide imaging including ventriculography and antimyosin imaging,12 13 14 MRI,15 and cytoimmunological monitoring16 17 18 have demonstrated limited predictive accuracy or practicability for monitoring transplant rejection.
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Autofluorescence |
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Spectroscopy typically involves placing a probe in contact with or near a tissue surface and obtaining fluorescence spectra for that single location. Typical biological fluorophores (molecules, cells, or tissue structures that give off fluorescent light when appropriately excited), with specific fluorescence signatures, include tryptophan, NADH, flavins (FAD), collagens, collagen cross-links, elastins, and porphyrins. Autofluorescence spectra obtained from tissue reflect both the spectra of the individual fluorophores present and their modification by adsorptive and dispersive tissue factors.19 20
Excitation wavelength (
) selection depends both on the efficacy
achievable for an intended purpose and on safety.
Autofluorescence spectroscopy has been applied in
characterization of pathological changes in the lung, gastrointestinal
tract, larynx, cervix, skin, and eye,21 22 and tissue
autofluorescence induced by blue-light excitation has been
effective in the early diagnosis of a variety of
cancers.23 24 25 26 27 Characterization of heart and vascular
tissue has been attempted mainly with UV excitation, including
identification of the sinoatrial and atrioventricular
nodal conduction tissue,28 detection of myocardial
ischemia,29 monitoring of myocardial redox
status,30 and localization of atherosclerotic
plaque.31 32 33 Nilsson et al34 used both
near-infrared spectroscopy and laser-induced fluorescence to
identify various types of cardiac tissue, and Perk et al35
studied fibrosis of the endocardium and myocardium. Two
important changes that occur in acutely rejecting tissue are edema and
the infiltration of leukocytes. Increased protein-rich
interstitial fluid could cause changes in the
autofluorescence response of heart tissue. The
autofluorescence properties of most leukocytes under blue-light
excitation are not well understood. Eosinophils have a characteristic
autofluorescence signature when excited by blue light,
primarily due to FAD,36 37 although their role in tissue
rejection remains unclear. The absorptive and light-scattering
properties of any infiltrating cells should be different from in situ
myocytes and would probably affect the autofluorescence
signature of heart tissue. Similarly, necrotic or markedly damaged
myocytes will likely have different absorptive and scattering
properties than viable myocytes.
To the best of our knowledge, a systematic investigation of the autofluorescence properties of tissue inflammation in heart rejection or of the diagnostic potential of autofluorescence spectra in this regard has not been reported. We now present evidence that autofluorescence under blue-light excitation may be useful in grading acute rejection based on studies ex vivo in a heterotopic abdominal rat heart allograft model.38 39
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Methods |
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Rat Heart Transplant Model
With Lewis-to–Fisher 344 allografts and Lewis-to-Lewis isografts, the native heart of the rat receiving the transplant serves as an internal control for the systemic immune environment. Allograft recipients and isograft recipients, as well as nontransplant controls, were treated with cyclosporine (2.5 mg · kg-1 · d-1) via subcutaneous injection for 7 days or left untreated (Table
). All animal experiments
were approved by the University of British Columbia Committee on Animal
Care (protocol number A96-0322) in accordance with the Canadian Council
on Animal Care. All rats were acclimatized for 1 week and weighed 200
to 225 g at the time of surgery. The technical details of the
transplant procedure are well described elsewhere.38 39
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Euthanasia and Tissue Triage Protocol
Rats were killed by carbon dioxide narcosis, and the
native and transplanted hearts were removed, sectioned, and processed.
A first most-basal ventricular bread-loaf section (2
mm thick) was frozen in OCT embedding medium. A second
ventricular bread-loaf section (4 to 6 mm thick) was
removed, the ventricles were opened anteriorly, and
autofluorescence spectra were acquired every 5 mm along
all endocardial and epicardial surfaces. The autofluorescence
probe was placed perpendicular to the endocardial or epicardial surface
to mimic the way tissue is taken with an
endomyocardial bioptome. Once all
autofluorescence measurements were completed on a given
bread-loaf section, it was processed for histopathological review.
Spectral Measurements
The optical probe and spectroscopy systems used to acquire the
autofluorescence spectra are represented in Figure 1. The 200-µm-diameter fiber in the
center of the probe tip illuminated the tissue with 442-nm excitation
light from an HeCd laser. Autofluorescence light emitted by the
tissue was collected by six 200-µm-diameter optical fibers
surrounding the central excitation fiber. Signals from the collection
fibers were first filtered (475-nm long-pass filter) to remove any
reflected excitation light and then relayed to a spectrometer. The
resulting autofluorescence spectra were calibrated for the
light response of the system, normalized to 1 at their maximum
intensity, and then binned into 2-nm-wavelength intervals in the range
of 480 to 800 nm.
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A contour plot based on a Monte Carlo simulation of the sensitivity of
the probe to the tissue area (1000 µm diameter, 650 µm
depth) near its tip is shown in Figure 2A; the illumination fiber is at the
origin. The optical properties used for these
simulations40 were estimated on the basis of dog
myocardium41 values. The contour plot shows
that the largest contribution comes from an area centered at
200 µm in depth and extending radially, 75 µm from
the center of the probe. The dashed boxes represent the tissue
regions that account for 50% and 90% of the signal. The 90% box is
roughly 700 µm in diameter and extends 550 µm below
the tissue surface. A breakdown of the contribution to the total signal
from various depths in 50-µm increments demonstrates that the largest
contributions come from the 150-to-200 µm and
200-to-250-µm-deep regions (Figure 2B).
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Histopathological Evaluation
For each rat, 5-µm sections from the native and transplant
hearts were cut perpendicular to the endocardium/epicardium, placed on
a single glass slide, stained with hematoxylin and eosin, marked to
identify the sites of optical measurements, and scored at these sites
by use of a modified International Society for Heart and Lung
Transplantation (ISHLT) grading system.2 The graders were
blinded as to the precise nature of the heart (native, isograft, or
allograft), time interval from transplant to euthanasia, treatment
group, and spectroscopic results. The modified ISHLT grading system
included scores as follows: 0, no rejection; I, IA, and IB, mild; II,
moderate; and IIIA, IIIB, and IV, severe. ISHLT grade IA and IB spectra
were amalgamated into the single grade I and grade IIIA and IIIB
spectra were similarly combined because the A and B designations refer
to focal (or multifocal) and diffuse inflammation, respectively, and
not to a difference in severity at a given numerical grade. In
utilizing these slight modifications of the ISHLT grading system, we
also recognize the difference in evaluating human heart biopsy samples
versus whole rat hearts.
Data Analysis
To discriminate between 2 groups of autofluorescence
spectra on the basis of spectral shape, a full, forward, and backward
stepwise linear discriminant function (DF)
analysis42 43 was performed. This analysis
was designed to pick an optimal set of points along the spectral curve
that, when combined as a linear weighted sum, generate a score that
distinguishes between the groups:
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i) is the
autofluorescence intensity at wavelength
i. In the present report, we will refer to
the foregoing process as "training" a linear DF. The DF is then
used to score (or test) any other spectra. The first step was to remove from the analysis set in an unbiased fashion those spectra (n=118) that had clearly identifiable spectral features related to artifacts or blood absorption by use of a linear DF analysis. The remaining spectra (n=1354), largely free of blood absorption effects, were then grouped and analyzed by linear DF analysis to assess the correlation between the histopathological grades and spectral changes.
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Results |
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Photomicrographs from a control heart and representative transplant hearts with modified ISHLT grades 0, I, II, and III rejection and correspondent autofluorescence spectra are shown in Figure 3
. Rejection caused a shift of the main
peak to longer wavelengths, as well as an increase in spectral
intensity of longer wavelengths relative to the intensity of the main
peak. In addition, the distinct "bump" at 600 nm in the control
spectrum disappeared in rejecting hearts.
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There was no statistical difference between the average spectra of
nontransplant controls treated or not treated with
cyclosporine (Figure 4).
Thus, cyclosporine itself did not contribute to heart
tissue autofluorescence and had no apparent effect that could
obscure spectral changes of interest, those associated with
inflammation or injury due to rejection.
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To correlate autofluorescence spectra with tissue rejection
severity, the spectra were separated into groups corresponding to
modified ISHLT grades 0 (n=180), I (n=223), II (n=69), and III (n=29).
DF analysis was performed with grade 0 and grade III used as
the training set, and a DF with wavelength values of 480, 496, 504,
518, and 522 nm was generated. These wavelengths encompass the visually
apparent position and shape changes in the main peak of the
autofluorescence spectra. This DF was then used to score
spectra from native (n=618) and control hearts (n=236), as well as
those grafts with a full range of rejection grades (Figure 5). Increasing tissue rejection severity
was accompanied by a clear progression of decreasing DF scores. Each
successive modified ISHLT grade (0, I, and II) is different
(Student-Newman-Keuls [SNK] test, P<0.01). The mean DF
score for modified ISHLT grade II rejection was higher than that of
grade III (SNK test, P=0.06). To test the strength of
correlation between the modified ISHLT grade and DF score, we
calculated the Spearman rank-order correlation coefficient,
RS, based on all grade 0 spectra (including
both allograft and isograft) being assigned a value of 0 and grades I,
II, and III being assigned values of 1, 2, and 3, respectively. The
result was RS=-0.6, reflecting a highly
significant correlation (P<0.001). It should be emphasised
that the DF was trained only on hearts with ISHLT grade 0 and grade
III. Thus, control hearts, native hearts, and grade I and II groups
provided genuine tests of the DF performance.
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Discussion |
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The differences between DF scores derived from autofluorescence spectra of tissue with different grades of rejection are very encouraging. If a mean rejection score of 0.5 is used as the dividing line between grade 0 and grade III, 95% of the grade III spectra can be classified correctly, while only 20% of the grade 0 scores will be misclassified. Subtle differences in DF scores for the various nonrejecting tissue groups are also interesting and have implications for interpretation of the results. None of the sites probed for fluorescence or examined histologically were confounded by perioperative infarcts.
As expected, the DF does not discriminate between controls (unoperated) and native hearts of animals with an isograft (n=88), wherein there is little or no immune response. We categorized native hearts of allograft animals as those from animals whose transplanted hearts had ISHLT grade 0 or only a few grade I sites (n=194) and those whose allografts had sites with ISHLT grades II and III (n=336). The significant difference between the spectra of the native hearts of animals with an isograft and the native hearts of animals with an allograft suggests that the immune response to the allograft has a detectable remote effect on the autofluorescence of the native heart. Moreover, the difference in the native heart DF scores of the 2 allograft groups implies that this immune response is progressive and linked to increasing severity of tissue rejection in the transplanted heart. The spectral difference between ISHLT grade 0 in the isografts (n=85) and native heart of the isograft group is arguably a direct measure of the effect of the unnatural position and surgical manipulation of the abdominal heart. However, there is little or no visible immune response in animals in either of these groups.
The mean DF score of the allograft grade 0 group is slightly below that of the isograft grade 0 group, which is also consistent with a systemic response that affects tissue beyond the rejecting heart. In addition, any imprecision in matching the tissue sampled by the optical probe with that graded by the pathologist could allow tissue samples in the allograft grade 0 group to be influenced by neighboring tissue with slight rejection. Such "neighborhood" effects would slightly alter the average fluorescence score.
It is widely appreciated that rejection, as defined histopathologically, is a very diffuse process. Thus, the likelihood of detecting rejection, when present, has been shown to be 95% when 3 pieces of bioptome-acquired tissue are evaluated microscopically, whereas the likelihood rises to 98% with 4 pieces of tissue.44 45 The grade of rejection in a given biopsy specimen may not reflect the average rejection grade for an entire heart or chamber; however, the potential virtue of the optical interrogative approach is the ability to sample perhaps 4 times as many sites as conventionally sampled by endomyocardial biopsy in a small fraction of the time. Such a larger representation of ventricular myocardium offers a potentially significant advantage in acquiring an accurate mean score of ongoing rejection in a particular heart.
To date, no particular information exists on the discrimination of different types of inflammation in the heart with the optical bioptome. The differentiation of rejection from infection and the injury or inflammation associated with either process also requires more evaluation. Myocardial infections are relatively rare in contemporary patients; however, we will need to know their differentiating optical features. The large number of sampling sites envisaged with the optical bioptome will help to differentiate a more focal inflammatory infectious process from diffuse organ allogenicity. We intend to address these issues in the future in a swine allograft model using dual tissue and optical biopsy sampling. The swine study has already shown the feasibility of obtaining meaningful spectra in a beating heart.
In conclusion, the autofluorescence spectra from rat heart tissue excited by blue light changes consistently as the hearts undergo transplant rejection, and linear DF analysis can distinguish spectra corresponding to the degrees of tissue rejection. ISHLT grade 0 is readily distinguishable by autofluorescence from grade III and is different from grades I and II. Coupled with its capability of extensive and rapid interrogation of the ventricular endomyocardium, the optical method may facilitate a better understanding of the rejection process and may allow targeting of biopsy sites to increase the diagnostic efficiency of endomyocardial biopsy. Identification of human heart allograft rejection currently remains bound to histopathological evaluation; however, the strong relationship between autofluorescence spectra and modified ISHLT rejection grades we have observed thus far in rat allografts suggests a role for fluorescence-based surveillance of rejection. No insurmountable challenges are anticipated with this technique in orthotopic allografts; indeed, fewer difficulties are likely than in the heterotopic swine model.
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Acknowledgments |
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The authors gratefully acknowledge Biomax Technologies, Inc, for support for this work and recognize grant support from the Heart and Stroke Foundation of British Columbia and Yukon (Dr McManus) and the British Columbia Transplant Society (Dr McManus). The authors thank Dean English, Diane Minshall, and Dr Shuxin Zheng (technical assistance), Anson Chang (database), and Shelley Wood and Josh King (editorial assistance).
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Footnotes |
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The prototype device and analysis system used in this study was developed by Biomax Technologies, Inc. Drs McManus and MacAulay are consultants to Biomax Technologies, Inc, which also provided financial support for this study.
Received October 19, 1998; revision received May 4, 1999; accepted May 5, 1999.
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References |
|---|
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|---|
1. Balk AH, Zondervan PE, van der Meer P, van Gelder T, Mochtar B, Simoons ML, Weimar W. Effect of adopting a new histological grading system of acute rejection after heart transplantation. Heart.. 1997;78:603–607.
2. Billingham ME, Cary NR, Hammond ME, Kemnitz J, Marboe C, McCallister HA, Snovar DC, Winters GL, Zerbe A. A working formulation for the standardization of nomenclature in the diagnosis of heart and lung rejection: Heart Rejection Study Group: the International Society for Heart Transplantation. J Heart Transplant.. 1990;9:587–593.[Medline] [Order article via Infotrieve]
3. Winters GL, McManus BM. Consistencies and controversies in the application of the International Society for Heart and Lung Transplantation working formulation for heart transplant biopsy specimens: Rapamycin Cardiac Rejection Treatment Trial Pathologists. J Heart Lung Transplant.. 1996;15:728–735.[Medline] [Order article via Infotrieve]
4. Winters GL. The challenge of endomyocardial biopsy interpretation in assessing cardiac allograft rejection. Curr Opin Cardiol.. 1997;12:146–152.[Medline] [Order article via Infotrieve]
5. Carrier M. Noninvasive assessment of cardiac transplant rejection: a critical look at the approach to acute rejection. Can J Surg.. 1991;34:569–572.[Medline] [Order article via Infotrieve]
6. Warnecke H, Schuler S, Goetze HJ, Matheis G, Suthoff U, Muller J, Tietze U, Hetzer R. Noninvasive monitoring of cardiac allograft rejection by intramyocardial electrogram recordings. Circulation. 1986;74(suppl 5, pt 2): III-72–III-76.
7.
Everett JE, Palmer MN, Jessurun J, Shumway SJ.
Noninvasive diagnosis of cardiac allograft rejection in an orthotopic
canine model. Ann Thorac Surg. 1996;62:1337–1340;
discussion 1340–1341.
8. Popp RL, Schroeder JS, Stinson EB, Shumway NE, Harrison DC. Ultrasonic studies for the early detection of acute cardiac rejection. Transplantation.. 1971;11:543–550.[Medline] [Order article via Infotrieve]
9. Mannaerts HF, Simoons ML, Balk AH, Tijssen J, van der Borden SG, Zondervan PE, Mochtar B, Weimar W, Roelandt JR. Pulsed-wave transmitral Doppler do not diagnose moderate acute rejection after heart transplantation. J Heart Lung Transplant.. 1993;12:411–421.[Medline] [Order article via Infotrieve]
10. Ciliberto GR, Mascarello M, Gronda E, Bonacina E, Anjos MC, Danzi G, Colombo P, Frigerio M, Alberti A, De Vita C. Acute rejection after heart transplantation: noninvasive echocardiographic evaluation. J Am Coll Cardiol.. 1994;23:1156–1161.[Abstract]
11. Vion-Dury J, Mouly-Bandini A, Viout P, Sciaky M, Confort-Gouny S, Monties JR, Cozzone P. Early detection of heart transplant rejection using cardiac echography combined with the assay of glycosylated residues in plasma by proton NMR spectroscopy. C R Acad Sci III. 1992;315:479–484.[Medline] [Order article via Infotrieve]
12. Mullins PA, Schofield PM, Dunning J, Scott J, Aravot D, Large S, Cary N, Wallwork J, Stone D. The use of exercise technetium-99m 2-methoxy-isobutyl-isonitrile (99mTc-Sestamibi) perfusion scanning in the detection of acute rejection after cardiac transplantation. J Nucl Biol Med.. 1992;36:2–6.
13. Frist W, Yasuda T, Segall G, Khaw BA, Strauss HW, Gold H, Stinson E, Oyer P, Baldwin J, Billingham M. Noninvasive detection of human cardiac transplant rejection with In-111 antimyosin (FAB) imaging. Circulation. 1987;76(pt II):V-81–V-85.
14. Bocchi EA, Mocelin AO, de Moraes AV, Menegheti C, de Lourdes Higuchi M, Bacal F, Stolf N, Bellotti G, Pileggi F. Comparison between two strategies for rejection detection after heart transplantation: routine endomyocardial biopsy versus gallium-67 cardiac imaging. Transplant Proc.. 1997;29:586–588.[Medline] [Order article via Infotrieve]
15. Doornbos J, Verwey H, Essed CE, Balk AH, de Roos A. MR imaging in assessment of cardiac transplant rejection in humans. J Comput Assist Tomogr.. 1990;14:77–81.[Medline] [Order article via Infotrieve]
16. Grant SC, Lamb WR, Hutchinson IV, Brenchley PE. Serum soluble adhesion molecules and cytokines in cardiac allograft rejection: the Manchester Transplant Cytokine Group. Transpl Immunol.. 1994;2:321–325.[Medline] [Order article via Infotrieve]
17. Fisher PE, Suciu-Foca N, Ho E, Michler RE, Rose EA, Mancini D. Additive value of immunologic monitoring to histologic grading of heart allograft biopsy specimens: implications for therapy. J Heart Lung Transplant.. 1995;14:1156–1161.[Medline] [Order article via Infotrieve]
18. Tugulea S, Ciubotariu R, Colovai AI, Liu Z, Itescu S, Schulman LL, Fisher PE, Hardy MA, Rose EA, Michler RE, Cortesini R, Suciu-Foca N. New strategies for early diagnosis of heart allograft rejection. Transplantation.. 1997;64:842–847.[Medline] [Order article via Infotrieve]
19. Schomacker KT, Frisoli JK, Compton CC, Flotte TJ, Richter JM, Nishioka NS, Deutsch TF. Ultraviolet laser-induced fluorescence of colonic tissue: basic biology and diagnostic potential. Lasers Surg Med.. 1992;12:63–78.[Medline] [Order article via Infotrieve]
20. Zonios GI, Cothren RM, Arendt JT, Wu J, Van Dam J, Crawford JM, Manoharan R, Feld MS. Morphological model of human colon tissue fluorescence [published erratum appears in IEEE Trans Biomed Eng. 1996;43:437]. IEEE Trans Biomed Eng. 1996;43:113–122.
21. Bigio IJ, Mourant JR. Ultraviolet and visible spectroscopies for tissue diagnostics: fluorescence spectroscopy and elastic-scattering spectroscopy. Phys Med Biol.. 1997;42:803–814.[Medline] [Order article via Infotrieve]
22. Alfano R, Katz A. Fluorescence and raman spectroscopy for tissue diagnosis and characterization. In: Kohen E, Hirschberg J, eds. Analytical Use of Fluorescent Probes in Oncology. New York, NY: Plenum Press; 1996:81–89.
23. Palcic B, MacAulay C, Shlien S, Treurniet W, Tezcan H, Anderson G. Comparison of three different methods for automated classification of cervical cells. Anal Cell Pathol.. 1992;4:429–441.[Medline] [Order article via Infotrieve]
24. Lam S, MacAulay C, Hung J, Le Riche J, Profio AE, Palcic B. Detection of dysplasia and carcinoma in situ with a lung imaging fluorescence endoscope device. J Thorac Cardiovasc Surg.. 1993;105:1035–1040.[Abstract]
25. Zeng H, MacAulay C, McLean DI, Palcic B. Reconstruction of in vivo skin autofluorescence spectrum from microscopic properties by Monte Carlo simulation. J Photochem Photobiol B.. 1997;38:234–240.[Medline] [Order article via Infotrieve]
26. Qu J, MacAulay C, Lam S, Palcic B. Optical properties of normal and carcinoma bronchial tissue. Applied Optics.. 1994;33:7397–7405.
27. Panjehpour M, Overholt BF, Vo-Dinh T, Haggitt RC, Edwards DH, Buckley FPR. Endoscopic fluorescence detection of high-grade dysplasia in Barrett's esophagus. Gastroenterology.. 1996;111:93–101.[Medline] [Order article via Infotrieve]
28. Perk M, Flynn GJ, Gulamhusein S, Wen Y, Smith C, Bathgate B, Tulip J, Parfrey NA, Lucas A. Laser induced fluorescence identification of sinoatrial and atrioventricular nodal conduction tissue. Pacing Clin Electrophysiol. 1993;16:1701–1712.[Medline] [Order article via Infotrieve]
29.
Horvath KA, Schomacker KT, Lee CC, Cohn LH.
Intraoperative myocardial ischemia detection with laser-induced
fluorescence. J Thorac Cardiovasc Surg.. 1994;107:220–225.
30. Renault G, Muffat-Joly M, Polianski J, Hardy RI, Boutineau JL, Duvent JL, Pocidalo JJ. NADH in situ laser fluorimetry: effect of pentobarbital on continuously monitored myocardial redox state. Lasers Surg Med.. 1987;7:339–346.[Medline] [Order article via Infotrieve]
31. Yan WD, Perk M, Chagpar A, Wen Y, Stratoff S, Schneider WJ, Jugdutt BI, Tulip J, Lucas A. Laser-induced fluorescence, III: quantitative analysis of atherosclerotic plaque content. Lasers Surg Med.. 1995;16:164–178.[Medline] [Order article via Infotrieve]
32. Baraga JJ, Rava RP, Taroni P, Kittrell C, Fitzmaurice M, Feld MS. Laser induced fluorescence spectroscopy of normal and atherosclerotic human aorta using 306–310 nm excitation. Lasers Surg Med.. 1990;10:245–261.[Medline] [Order article via Infotrieve]
33. Chaudhry HW, Richards-Kortum R, Kolubayev T, Kittrell C, Partovi F, Kramer JR, Feld MS. Alteration of spectral characteristics of human artery wall caused by 476-nm laser irradiation. Lasers Surg Med.. 1989;9:572–580.[Medline] [Order article via Infotrieve]
34. Nilsson AM, Heinrich D, Olajos J, Andersson-Engels S. Near infrared diffuse reflection and laser-induced fluorescence spectroscopy for myocardial tissue characterisation. Spectrochim Acta A Mol Biomol Spectrosc. 1997;53A:1901–1912.
35. Perk M, Flynn GJ, Smith C, Bathgate B, Tulip J, Yue W, Lucas A. Laser-induced fluorescence emission, I: the spectroscopic identification of fibrotic endocardium and myocardium. Lasers Surg Med.. 1991;11:523–534.[Medline] [Order article via Infotrieve]
36.
Weil GJ, Chused TM. Eosinophil autofluorescence
and its use in isolation and analysis of human eosinophils
using flow microfluorometry. Blood.. 1981;57:1099–1104.
37. Mayeno AN, Hamann KJ, Gleich GJ. Granule-associated flavin adenine dinucleotide (FAD) is responsible for eosinophil autofluorescence. J Leukoc Biol.. 1992;51:172–175.[Abstract]
38. Adams DH, Tilney NL, Collins JJ Jr, Karnovsky MJ. Experimental graft arteriosclerosis, I: the Lewis-to-F-344 allograft model. Transplantation.. 1992;53:1115–1119.[Medline] [Order article via Infotrieve]
39. Ono K, Lindsey ES. Improved technique of heart transplantation in rats. J Thorac Cardiovasc Surg.. 1969;57:225–229.[Medline] [Order article via Infotrieve]
40. Wang L, Jacques S. Monte Carlo Modeling of Light Transport in Multi-Layered Tissue in Standard C. Houston, Tex: University of Texas, MD Anderson Cancer Center; 1992.
41. Pickering J, Bosman S, Posthumus P, Blokland P, Beek J, van Gemert M. Changes in the optical properties (at 632.8 nm) of slowly heated myocardium. Appl Opt.. 1993;32:367–371.
42. Tatsuoka M. Techniques for Education and Psychological Research. Toronto, Canada: John Wiley & Sons; 1971:157–242.
43. James M. Classification Algorithms. London, UK: William Collins Sons & Co; 1985;127–148.
44. Spiegelhalter DJ, Stovin PGI. An analysis of repeated biopsies following cardiac transplantation. Stat Med.. 1983;2:33–40.[Medline] [Order article via Infotrieve]
45. Zerbe TR, Arena V. Diagnostic reliability of endomyocardial biopsy for assessment of cardiac allograft rejection. Hum Pathol.. 1988;19:1307–1314.[Medline] [Order article via Infotrieve]
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