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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 18, Iss. 4 — Feb. 15, 2010
  • pp: 3840–3849
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Time- and Spectral-resolved two-photon imaging of healthy bladder mucosa and carcinoma in situ

Riccardo Cicchi, Alfonso Crisci, Alessandro Cosci, Gabriella Nesi, Dimitrios Kapsokalyvas, Saverio Giancane, Marco Carini, and Francesco S. Pavone  »View Author Affiliations


Optics Express, Vol. 18, Issue 4, pp. 3840-3849 (2010)
http://dx.doi.org/10.1364/OE.18.003840


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Abstract

Combined non-linear imaging techniques were used to deeply image human ex-vivo fresh biopsies of bladder as well as to discriminate between healthy bladder mucosa and carcinoma in situ. Morphological examination by two-photon excited fluorescence and second-harmonic generation has shown a good agreement with corresponding common routine histology performed on the same samples. Tumor cells appeared slightly different in shape and with a smaller cellular-to-nuclear dimension ratio with respect to corresponding normal cells. Further differences between the two tissue types were found in both spectral emission and fluorescence lifetime distribution by performing temporal- and spectral- resolved analysis of fluorescence. This method may represent a promising tool to be used in a multi-photon endoscope, in a confocal endoscope or in a spectroscopic probe for in-vivo optical diagnosis of bladder cancer.

© 2010 OSA

1. Introduction

Bladder cancer is the fifth most common cancer in U.S [1

1. ACS, (2006), http://www.cancer.org/downloads/STT/CAFF2006PWSecured.pdf, Cancer Facts & Figs. (2006).

]. In general, it is curable when detected and treated early. A more accurate early diagnosis of bladder cancer would be a suitable aim for both detection and treatment. Diagnostic methods used are different, even if a non-invasive early detection of bladder cancer is still a challenge. Very often, symptomatic patients are visually inspected through white light cystoscopy, which is the most diffused endoscopic technique for bladder cancer detection in the clinical routine. This simple and easy-to-use technique is able to visualize the urothelium surface. The diagnosis is demanded to the eye of an experienced MD. However, cystoscopy is not able to assess bladder cancer in early stage but just lesions in a developed stage.

Sensitivity and specificity of cystoscopy can be significantly improved by means of fluorescence coming from photosensitizers used as contrast agents [2

2. J. C. Kah, W. K. Lau, P. H. Tan, C. J. Sheppard, and M. Olivo, “Endoscopic image analysis of photosensitizer fluorescence as a promising noninvasive approach for pathological grading of bladder cancer in situ,” J. Biomed. Opt. 13(5), 054022 (2008). [CrossRef] [PubMed]

5

5. D. Jocham, F. Witjes, S. Wagner, B. Zeylemaker, J. van Moorselaar, M. O. Grimm, R. Muschter, G. Popken, F. König, R. Knüchel, and K. H. Kurth, “Improved detection and treatment of bladder cancer using hexaminolevulinate imaging: a prospective, phase III multicenter study,” J. Urol. 174(3), 862–866, discussion 866 (2005). [CrossRef] [PubMed]

]. Various compounds as such methyl-aminolevulinate can be used to enhance cancer margins contrast. This technique has the big advantage of being performed with the same cystoscope used for common inspection (under UV or blue-illuminaton) as well as of providing better sensitivity (up to 96%) with respect to white light cystoscopy (up to 77%). Nevertheless its specificity is still far from being optimal (up to 60-70%), resulting in a high percentage of false positives. Specificity can be improved by means of tissue autofluorescence spectroscopy [6

6. N. Ramanujam, “Fluorescence spectroscopy of neoplastic and non-neoplastic tissues,” Neoplasia 2(1/2), 89–117 (2000). [CrossRef] [PubMed]

,7

7. M. Anidjar, O. Cussenot, S. Avrillier, D. Ettori, P. Teillac, and A. Le Duc, “The role of laser-induced autofluorescence spectroscopy in bladder tumor detection. Dependence on the excitation wavelength,” Ann. N. Y. Acad. Sci. 838(1 ADVANCES IN O), 130–141 (1998). [CrossRef] [PubMed]

] which is mainly performed by means of a fiber-probe inserted in the service channel of a cystoscope. Such a technique can be used combined with white light cystoscopy [8

8. F. Koenig, F. J. McGovern, A. F. Althausen, T. F. Deutsch, and K. T. Schomacker, “Laser induced autofluorescence diagnosis of bladder cancer,” J. Urol. 156(5), 1597–1601 (1996). [CrossRef] [PubMed]

], or also with photosensitizers and fluorescence cystoscopy [9

9. D. Zaak, H. Stepp, R. Baumgartner, P. Schneede, R. Waidelich, D. Frimberger, A. Hartmann, R. Künchel, A. Hofstetter, and A. Hohla, “Ultraviolet-excited (308 nm) autofluorescence for bladder cancer detection,” Urology 60(6), 1029–1033 (2002). [CrossRef] [PubMed]

,10

10. W. W. Chin, P. S. P. Thong, R. Bhuvaneswari, K. C. Soo, P. W. S. Heng, and M. Olivo, “In-vivo optical detection of cancer using chlorin e6-polyvinylpyrrolidone induced fluorescence imaging and spectroscopy,” BMC Med. Imaging 9(1), 1–8 (2009). [CrossRef] [PubMed]

]. Fluorescence emission spectrum measurement gives additional information helpful in discriminating pathologic conditions. Further, coupled with cystoscopy, this technique allows to target only visually ambiguous lesions, helping in diagnosing when clinical eye fails.

Among non-linear imaging techniques used, two-photon excitation fluorescence (TPEF) microscopy [24

24. W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science 248(4951), 73–76 (1990). [CrossRef] [PubMed]

] is providing high-resolution deep tissue imaging [17

17. B. R. Masters, P. T. C. So, and E. Gratton, “Optical biopsy of in vivo human skin: multi-photon excitation microscopy,” Lasers Med. Sci. 13(3), 196–203 (1998). [CrossRef]

20

20. K. König and I. Riemann, “High-resolution multiphoton tomography of human skin with subcellular spatial resolution and picosecond time resolution,” J. Biomed. Opt. 8(3), 432–439 (2003). [CrossRef] [PubMed]

]. Since both cells and extracellular matrix intrinsically contain several fluorescent molecules with absorption in the UV range (NADH, tryptophan, keratins, melanin, elastin, cholecalciferol and others), biological tissues can be imaged by TPEF microscopy without any exogenously added probe [25

25. W. R. Zipfel, R. M. Williams, and W. W. Webb, “Nonlinear magic: multiphoton microscopy in the biosciences,” Nat. Biotechnol. 21(11), 1369–1377 (2003). [CrossRef] [PubMed]

27

27. W. R. Zipfel, R. M. Williams, R. Christie, A. Y. Nikitin, B. T. Hyman, and W. W. Webb, “Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation,” Proc. Natl. Acad. Sci. U.S.A. 100(12), 7075–7080 (2003). [CrossRef] [PubMed]

]. Second-harmonic generation (SHG) is a well suited microscopy technique to analyze connective tissues due to the significant second order non-linear susceptibility of collagen [28

28. P. J. Campagnola and L. M. Loew, “Second-harmonic imaging microscopy for visualizing biomolecular arrays in cells, tissues and organisms,” Nat. Biotechnol. 21(11), 1356–1360 (2003). [CrossRef] [PubMed]

,29

29. E. Brown, T. McKee, E. diTomaso, A. Pluen, B. Seed, Y. Boucher, and R. K. Jain, “Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation,” Nat. Med. 9(6), 796–801 (2003). [CrossRef] [PubMed]

]. SHG signal has been used to discriminate cancerous tissue [29

29. E. Brown, T. McKee, E. diTomaso, A. Pluen, B. Seed, Y. Boucher, and R. K. Jain, “Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation,” Nat. Med. 9(6), 796–801 (2003). [CrossRef] [PubMed]

] as well as collagen modifications in the peri-tumoral stroma [30

30. P. P. Provenzano, K. W. Eliceiri, J. M. Campbell, D. R. Inman, J. G. White, and P. J. Keely, “Collagen reorganization at the tumor-stromal interface facilitates local invasion,” BMC Med. 4(1), 38 (2006). [CrossRef] [PubMed]

,31

31. R. Cicchi, S. Sestini, V. De Giorgi, D. Massi, T. Lotti, and F. S. Pavone, “Non-linear laser imaging of skin lesions,” J. Biophoton. 1(1), 62–73 (2008). [CrossRef]

]. Multispectral two-photon (MTPE) imaging, performed by detecting the emission spectrum of endogenous fluorescence, offers functional information about the relative quantities of fluorescent molecules, which correlate with tissue structure in physiological and pathological states [32

32. L. H. Laiho, S. Pelet, T. M. Hancewicz, P. D. Kaplan, and P. T. C. So, “Two-photon 3-D mapping of ex vivo human skin endogenous fluorescence species based on fluorescence emission spectra,” J. Biomed. Opt. 10(2), 024016 (2005). [CrossRef] [PubMed]

]. Fluorescence lifetime imaging microscopy (FLIM) is an additional non-invasive microscopy technique enabling the identification of endogenous fluorescence species by measuring the decay rate of their fluorescent emission [33

33. P. J. Tadrous, “Methods for imaging the structure and function of living tissues and cells: 2. Fluorescence lifetime imaging,” J. Pathol. 191(3), 229–234 (2000). [CrossRef] [PubMed]

,34

34. P. J. Tadrous, J. Siegel, P. M. W. French, S. Shousha, N. Lalani, and G. W. H. Stamp, “Fluorescence lifetime imaging of unstained tissues: early results in human breast cancer,” J. Pathol. 199(3), 309–317 (2003). [CrossRef] [PubMed]

]. FLIM is useful to study protein localization [35

35. Y. Chen and A. Periasamy, “Characterization of two-photon excitation fluorescence lifetime imaging microscopy for protein localization,” Microsc. Res. Tech. 63(1), 72–80 (2004). [CrossRef]

] and fluorescent molecular environment [36

36. S. Y. Breusegem, M. Levi, and N. P. Barry, “Fluorescence correlation spectroscopy and fluorescence lifetime imaging microscopy,” Nephron, Exp. Nephrol. 103(2), e41–e49 (2006). [CrossRef]

].

In this work we used a multidimensional analysis [37

37. R. Cicchi, D. Massi, S. Sestini, P. Carli, V. De Giorgi, T. Lotti, and F. S. Pavone, “Multidimensional non-linear laser imaging of Basal Cell Carcinoma,” Opt. Express 15(16), 10135–10148 (2007). [CrossRef] [PubMed]

] for bladder tissue characterization by combining all the non-linear microscopy techniques described above. In particular, we performed a morphological analysis of bladder urothelium by using TPEF and SHG on fresh biopsies. Compared to healthy mucosa (HM), carcinoma in situ (CIS) showed differences in morphology, measured in terms of cellular-to-nuclear dimension ratio. MTPE analysis of fluorescence signals showed similar emission spectra but with a different SHG contribution. Deeper analysis and discrimination was performed by measuring the SHG-to-autofluorescence signal ratio through a normalized index. Further characterization was obtained by the use of spectral- and time-resolved detection of endogenous NADH and FAD fluorescence. First, by selecting spectral channels corresponding to NADH and FAD emission, a different fluorescent intensity ratio was found between HM and CIS. Then, by a double-component lifetime analysis of FLIM images, differences in the lifetime components ratio between the two tissues were highlighted. Even if a more significant statistics on a large number of samples, including mild- and low-grade bladder cancers, would be helpful to give more indication on the diagnostic sensitivity and specificity of the method, this multidimensional analysis may represent a powerful tool, if combined with multi-photon endoscopy, with confocal endoscopy or with fluorescence fiber-based spectroscopy, for the early diagnosis of bladder cancer.

2. Materials and methods

2.1 Samples

Two sets of cold-cup bladder biopsies of healthy mucosa and white light cystoscopy pattern suspected of CIS were taken in 5 patients with positive urine cytology during transurethral resection of the bladder. One set of the specimens were sent for pathology and the other stored in a wet environment with few drops of normal saline and sent for two-photon imaging within 1 hour. Pathology report confirmed CIS in all the samples.

Fresh relaxed biopsies were sandwiched between a microscope slide and a 170 μm glass coverslip. A fat silicon ring was used to both create a chamber for the sample and to prevent unwanted movements of the coverslip. Some droplets of PBS were added to the sample to maintain natural osmolarity. Samples were imaged with two-photon microscopy within one hour from excision, always using “en-face” optical sectioning geometry.

2.2 Non-linear microscopy system

The experimental setup consisted of a custom-made upright non-linear microscope able to perform combined TPEF-SHG by detecting emitted photons in proportional regime, and FLIM-MTPE by working in single-photon counting regime. Detailed description of this microscope, including acquisition and control, are given in [38

38. R. Cicchi, L. Sacconi, A. Jasaitis, R. P. O’Connor, D. Massi, S. Sestini, V. De Giorgi, T. Lotti, and F. S. Pavone, “Multidimensional custom-made non-linear microscope: from ex-vivo to in-vivo imaging,” Appl. Phys. B 92(3), 359–365 (2008). [CrossRef]

].

2.3 Image acquisition and analysis

2.3.1 Morphological analysis (TPEF and SHG)

The excitation was done by using a wavelength of 740 nm for TPEF and 840 nm for SHG, and a mean laser power at the sample between 10 and 40 mW, depending on the depth of recording. TPEF and SHG images were acquired with 1024 × 1024 pixels spatial resolution, from 100 μm to 200 μm field of view dimension, using a pixel dwell time of 5 μs. Image processing was performed by using ImageJ (NIH, Bethesda, Maryland, US). Acquired 8-bit TPEF and SHG images were merged in RGB images (color-code: green for TPEF and blue for SHG) to be presented together with histological images. Further processing was done on TPEF images. A threshold was applied to images of cells to remove background, enhancing both cellular and nuclear borders. Then the borders were visually selected and the inner area measured in pixel2 units. Finally the cellular-to-nuclear area ratio was calculated. This analysis was performed on approximately 10 cells per sample, on images taken at a depth in the 20-30 μm range.

2.3.2 Spectral-resolved analysis (MTPE)

Two excitation wavelengths were used: 740 nm for exciting NADH, and 890 nm for FAD, and a mean laser power of approximately 15 mW. MTPE images were acquired in blocks of 16 spectral images (420 nm - 620 nm spectral range) with 32 × 32 pixels spatial resolution, 20 μm field of view dimension, using a pixel dwell time of 0.2 ms and an integration time of approximately 160 s per image block. Acquired files were exported in three-dimensional matrixes representing the number of detected photons N=N(x,y,λ) as a function of position and wavelength by using SPC-Image 2.8 (Becker-Hickl GmbH, Berlin, Germany) and processed by using a custom routine developed under LabView 7.1 (National Instruments, Austin, TX, US). Two normalized ratio-based methods were used for spectral analysis of images acquired at the two depths of 20 μm to 30 μm, and of 50 μm to 60 μm, respectively corresponding to mid-urothelium and to urothelium-lamina propria border in HM. Measurements were performed at corresponding depths in both HM and CIS samples. For deeper images the following normalized ratio, known as SHG-to-autofluorescence ageing index of dermis [39

39. S. J. Lin, R. J. Wu, H. Y. Tan, W. Lo, W. C. Lin, T. H. Young, C. J. Hsu, J. S. Chen, S. H. Jee, and C. Y. Dong, “Evaluating cutaneous photoaging by use of multiphoton fluorescence and second-harmonic generation microscopy,” Opt. Lett. 30(17), 2275–2277 (2005). [CrossRef] [PubMed]

] (SAAID), was used as a score:

SAAID=SHGTPEFSHG+TPEF.
(1)

In SAAID scoring at 890 nm excitation wavelength, SHG image is the sum of all channels in the 420 nm – 460 nm spectral range, whereas TPEF is the sum of all channels in the 475 nm – 620 nm spectral range. Images taken at a depth of 20-30 μm were used for Red-Ox ratio scoring. In this analysis NADH-image is intended as the image acquired on a single channel (460 nm – 473 nm) at 740 nm excitation wavelength, whereas FAD-image is intended as the image acquired on a single channel (508 nm – 521 nm) at 890 nm excitation wavelength. Numbers of detected photons were corrected for detector spectral response and to the square of the excitation power measured at the objective aperture. Red-Ox ratio was calculated by using the following relationship:

ROx=FADNADHFAD+NADH.
(2)

Both SAAID and ROx scoring results are presented in color-coded maps as well as histogram distribution of the raw calculated values, together with the corresponding look-up table of the map superimposed.

2.3.3 Time-resolved analysis (FLIM)

Two excitation wavelengths were used and two corresponding spectral bands for detection: 740 nm for exciting NADH (430 nm - 490 nm detection) and 890 nm for FAD (470 nm – 550 nm detection). FLIM images were acquired with a mean laser power of approximately 15 mW, 128 × 128 pixels spatial resolution, 100 μm field of view dimension, using a pixel dwell time of 0.2 ms, an integration time of approximately 40 s per image and a temporal binning of 256 bins over a 12.5 ns TAC range. System response de-convolution and fluorescence decay fits on image pixels were done by using a double-exponential decay model in SPC-Image 2.8 (Becker-Hickl GmbH, Berlin, Germany), which also allows to present data as a fit parameter map. Graphs and histograms were prepared by using Microcal Origin Pro 8.0 (OriginLab Corporation, Northampton, MA, US).

3. Results and discussion

3.1 Tissue morphology (TPEF-SHG)

Morphological features of bladder urothelium can be highlighted on fresh biopsies by taking advantage of NADH autofluorescence, which is still present inside a fresh biopsy after excision [27

27. W. R. Zipfel, R. M. Williams, R. Christie, A. Y. Nikitin, B. T. Hyman, and W. W. Webb, “Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation,” Proc. Natl. Acad. Sci. U.S.A. 100(12), 7075–7080 (2003). [CrossRef] [PubMed]

,32

32. L. H. Laiho, S. Pelet, T. M. Hancewicz, P. D. Kaplan, and P. T. C. So, “Two-photon 3-D mapping of ex vivo human skin endogenous fluorescence species based on fluorescence emission spectra,” J. Biomed. Opt. 10(2), 024016 (2005). [CrossRef] [PubMed]

]. Both HM bladder cells and CIS cells give a high fluorescent signal if imaged within 2-3 hours from excision (see Fig. 1
Fig. 1 Combined TPEF (green-coded) and SHG (blue-coded) images taken from human ex-vivo fresh biopsies of bladder and the corresponding histological images taken after H&E staining of the same sample. On the left: an optical section of healthy mucosa acquired at 25 μm depth (a), and the corresponding histological image (b); an optical section of HM / connective tissue border acquired at 55 μm depth (c) and the corresponding histological image (d). On the right: an optical section of CIS acquired at 25 μm depth (e), and the corresponding histological image (f); an optical section of CIS / connective tissue border acquired at 55 μm depth (g) and the corresponding histological image (h). Scale bars: 10 μm.
). In these measurements we used an excitation wavelength of 740 nm for TPEF and of 840 nm for SHG, which are adequate to excite NADH fluorescence and collagen SHG, respectively. Both TPEF and SHG allow sub-diffraction limit spatial resolution, enabling bladder urothelium imaging at the sub-cellular level. A good agreement was found between TPEF-SHG images and the corresponding histological images taken after histological examination of the same samples (Fig. 1).

An additional morphological feature noted by researchers during measurement sessions is in average a higher SHG signal coming from HM with respect to CIS. This finding was confirmed by MTPE measurements, described below.

3.2 Tissue spectral features (MTPE - SAAID and ROx scoring)

3.3 Fluorescence lifetime of NADH-FAD couple (FLIM)

4. Conclusions

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P. J. Tadrous, “Methods for imaging the structure and function of living tissues and cells: 2. Fluorescence lifetime imaging,” J. Pathol. 191(3), 229–234 (2000). [CrossRef] [PubMed]

34.

P. J. Tadrous, J. Siegel, P. M. W. French, S. Shousha, N. Lalani, and G. W. H. Stamp, “Fluorescence lifetime imaging of unstained tissues: early results in human breast cancer,” J. Pathol. 199(3), 309–317 (2003). [CrossRef] [PubMed]

35.

Y. Chen and A. Periasamy, “Characterization of two-photon excitation fluorescence lifetime imaging microscopy for protein localization,” Microsc. Res. Tech. 63(1), 72–80 (2004). [CrossRef]

36.

S. Y. Breusegem, M. Levi, and N. P. Barry, “Fluorescence correlation spectroscopy and fluorescence lifetime imaging microscopy,” Nephron, Exp. Nephrol. 103(2), e41–e49 (2006). [CrossRef]

37.

R. Cicchi, D. Massi, S. Sestini, P. Carli, V. De Giorgi, T. Lotti, and F. S. Pavone, “Multidimensional non-linear laser imaging of Basal Cell Carcinoma,” Opt. Express 15(16), 10135–10148 (2007). [CrossRef] [PubMed]

38.

R. Cicchi, L. Sacconi, A. Jasaitis, R. P. O’Connor, D. Massi, S. Sestini, V. De Giorgi, T. Lotti, and F. S. Pavone, “Multidimensional custom-made non-linear microscope: from ex-vivo to in-vivo imaging,” Appl. Phys. B 92(3), 359–365 (2008). [CrossRef]

39.

S. J. Lin, R. J. Wu, H. Y. Tan, W. Lo, W. C. Lin, T. H. Young, C. J. Hsu, J. S. Chen, S. H. Jee, and C. Y. Dong, “Evaluating cutaneous photoaging by use of multiphoton fluorescence and second-harmonic generation microscopy,” Opt. Lett. 30(17), 2275–2277 (2005). [CrossRef] [PubMed]

40.

J. Paoli, M. Smedh, A. M. Wennberg, and M. B. Ericson, “Multiphoton laser scanning microscopy on non-melanoma skin cancer: morphologic features for future non-invasive diagnostics,” J. Invest. Dermatol. 128(5), 1248–1255 (2008). [CrossRef]

41.

O. Warburg, “The metabolism of tumors,” Constabel, London (1930).

42.

M. C. Skala, K. M. Riching, D. K. Bird, A. Gendron-Fitzpatrick, J. Eickhoff, K. W. Eliceiri, P. J. Keely, and N. Ramanujam, “In vivo multiphoton fluorescence lifetime imaging of protein-bound and free nicotinamide adenine dinucleotide in normal and precancerous epithelia,” J. Biomed. Opt. 12(2), 024014 (2007). [CrossRef] [PubMed]

43.

D. K. Bird, L. Yan, K. M. Vrotsos, K. W. Eliceiri, E. M. Vaughan, P. J. Keely, J. G. White, and N. Ramanujam, “Metabolic mapping of MCF10A human breast cells via multiphoton fluorescence lifetime imaging of the coenzyme NADH,” Cancer Res. 65(19), 8766–8773 (2005). [CrossRef] [PubMed]

44.

M. C. Skala, K. M. Riching, A. Gendron-Fitzpatrick, J. Eickhoff, K. W. Eliceiri, J. G. White, and N. Ramanujam, “In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia,” Proc. Natl. Acad. Sci. U.S.A. 104(49), 19494–19499 (2007). [CrossRef] [PubMed]

OCIS Codes
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(180.4315) Microscopy : Nonlinear microscopy

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: November 18, 2009
Revised Manuscript: January 26, 2010
Manuscript Accepted: January 28, 2010
Published: February 11, 2010

Virtual Issues
Vol. 5, Iss. 5 Virtual Journal for Biomedical Optics

Citation
Riccardo Cicchi, Alfonso Crisci, Alessandro Cosci, Gabriella Nesi, Dimitrios Kapsokalyvas, Saverio Giancane, Marco Carini, and Francesco S. Pavone, "Time- and Spectral-resolved two-photon imaging of healthy bladder mucosa and carcinoma in situ," Opt. Express 18, 3840-3849 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-4-3840


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