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Optics Express

Optics Express

  • Editor: Michael Duncan
  • Vol. 10, Iss. 24 — Dec. 2, 2002
  • pp: 1431–1443
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Detection of tumorigenesis in urinary bladder with optical coherence tomography: optical characterization of morphological changes

T. -Q. Xie, M. L. Zeidel, and Y. -T. Pan  »View Author Affiliations


Optics Express, Vol. 10, Issue 24, pp. 1431-1443 (2002)
http://dx.doi.org/10.1364/OE.10.001431


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Abstract

Most transitional cell tumorigenesis involves three stages of subcellular morphological changes: hyperplasia, dysplasia and neoplasia. Previous studies demonstrated that owing to its high spatial resolution and intermediate penetration depth, current OCT technology including endoscopic OCT could delineate the urothelium, submucosa and the upper muscular layers of the bladder wall. In this paper, we will discuss the sensitivity and limitations of OCT in diagnosing and staging bladder cancer. Based on histomorphometric evaluations of nuclear morphology, we modeled the resultant backscattering changes and the characteristic changes in OCT image contrast. In the theoretical modeling, we assumed that nuclei were the primary sources of scattering and were uniformly distributed in the uroepithelium, and compared with the results of the corresponding prior OCT measurements. According to our theoretical modeling, normal bladder shows a thin, uniform and low scattering urothelium, so does an inflammatory lesion except thickening in the submucosa. Compared with a normal bladder, a hyperplastic lesion exhibits a thickened, low scattering urothelium whereas a neoplastic lesion shows a thickened urothelium with increased backscattering. These results support our previous animal study that OCT has the potential to differentiate inflammation, hyperplasia, and neoplasia by quantifying the changes in urothelial thickening and backscattering. The results also suggest that OCT might not have the sensitivity to differentiate the subtle morphological changes between hyperplasia and dysplasia based on minor backscattering differences.

© 2002 Optical Society of America

1. Introduction

Clinical statistics indicate that bladder cancer is the fifth most common cancer and the twelfth leading cause of cancer death in the US1

1. http://www.cancernews.com/category.asp?cat=28&aid=235, “Diagnosis and Treatment of Bladder Cancer.”

. Bladder cancer is curable if detected and treated prior to invasion in the underlying bladder wall. Therefore, an earlier and more precise diagnosis of bladder cancer is critical to eradicating the disease, and understanding the pathological mutation of the disease on the microscopic level could lead to a better diagnosis because bladder carcinoma originates in the thin (20–200 μm) basal cell layer of the uroepithelium. Staging the spread or extent of invasion of cancerous urothelial cells into the underlying bladder wall is also important in helping the urologists to design the best treatment strategy. However, because of limitations of resolution, current detection methods, e.g., urine cytology, intravenous x-ray, MRI, and ultrasound fail to provide sufficient sensitivity or specificity2–6

2. J. M. Schmitt, “Optical Coherence Tomography (OCT): A Review,” IEEE J. Sel. Top. Quantum Electron. 5, 1205–1215 (1999). [CrossRef]

in predicting the prognosis of early bladder cancers and staging their invasions. Cystoscopy, although commonly used in urological examination of superficial tumors (e.g., carcinomas in situ), is always followed by random biopsy for a conclusive diagnosis because of lacks of depth resolution. Accordingly, new approaches that can instantaneously provide cross-sectional images of bladder morphologies and their alternations (e.g., tumorigenesis) at close to cellular resolution would substantially enhance the diagnostic sensitivity and specificity of current cystoscopic approaches and result in significant therapeutic benefits.

Since its first introduction to imaging the eye in early 19903

3. A. F. Fercher, K. Mengedoht, and W. Werner, “Eye length measurement by interferometry with partially coherent light,” Opt. Lett. 13, 186–188 (1988). [CrossRef] [PubMed]

,4

4. D. Huang, E. A. Swanson, and C. P. Lin, et al., “Optical coherence tomography,” Science 254, 1178–1181 (1991). [CrossRef] [PubMed]

, optical coherence tomography (OCT) has found widespread applications in diagnosing diseases in various biological tissues7

7. C. A. Puliafito, M. R. Hee, J. S. Schuman, and J. G. Fujimoto, Optical Coherence Tomography of Ocular Diseases (SLACK, Thorofare, NJ, 1996).

such as human skin8

8. A. M. Sergeev, V. M. Gelikonov, G. V. Gelikonov, F. I. Feldchtein, K. I. Pravdenko, D. V. Shabanov, N. D. Gladkova, V. V. Pochinko, V. A. Zhegalov, G. I. Dmitriev, I. R. Vazina, G. A. Petrova, and N. K. Nikulin, “In vivo optical coherence tomography of human skin microstructure,” Proc. SPIE 2328, 144–150 (1994). [CrossRef]

, 9

9. J. Welzel, “Optical coherence tomography in dermatology: a review,” Skin Research and Technology 7, 1–9 (2001). [CrossRef] [PubMed]

, tooth10

10. B. W. Colston, U. S. Sathyam, L. B. DaSilva, M. J. Everett, P. Stroeve, and L. L. Otis, “Dental OCT,” Opt. Express 3, 230–238 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-230. [CrossRef] [PubMed]

, blood vessels, gastrointestinal tracts, respiratory tracts, and genitourinary tracts11

11. G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography,” Science 276, 2037–2039 (1997). [CrossRef] [PubMed]

, 12

12. A. M. Sergeev, V. M. Gelikonov, G. V. Gelikonov, F. I. Feldchtein, R. V. Kuranov, N. D. Gladkova, N. M. Shakhova, L. B. Snopova, A. V. Shakhov, I. A. Kuznetzova, A. N. Denisenko, V. V. Pochinko, Yu. P. Chumakov, and O. S. Streltzova, “In vivo endoscopic OCT imaging of precancer and cancer states of human mucosa,” Opt. Express 1, 432–440 (1997), http://epubs.osa.org/oearchive/source/2788.htm. [CrossRef] [PubMed]

. In recent years, significant technological advances including polarization-sensitive OCT13

13. Johannes F. de Boer, Shyam M. Srinivas, Arash Malekafzali, Zhongping Chen, and J. Stuart Nelson, “Imaging thermally damaged tissue by polarization sensitive optical coherence tomography,” Opt. Express 3, 212–218 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-212. [CrossRef] [PubMed]

, 14

14. Gang Yao and Lihong Wang, “Propagation of polarized light in turbid media: simulated animation sequences”, Opt. Express 7, 198–203 (2000), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-7-5-198. [CrossRef] [PubMed]

, spectral OCT15

15. M. Wojtkowski, A. Kowalczyk, R. Leitgeb, and A. F. Fercher, “Full range complex spectral optical coherence tomography technique in eye imaging,” Opt. Lett. 27, 1415–1417 (2002). [CrossRef]

, ultra-high-resolution OCT16

16. W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, “In vivo ultrahigh-resolution optical coherence tomography”, Opt. Lett. 24, 1221–1223 (1999). [CrossRef]

, and Doppler OCT17

17. Volker Westphal, Siavash Yazdanfar, Andrew M. Rollins, and Joseph A. Izatt “Real-time, high velocity-resolution color Doppler optical coherence tomography”, Opt. Lett. 27, 34–36 (2002). [CrossRef]

, have been made to improve image resolution and provide more specific diagnosis of physiological and functional information of biological tissue. Furthermore, because OCT is a fiber optically based light scanning imaging technique it can be integrated with endoscopic catheters to allow for noninvasive or minimally invasive in vivo imaging diagnosis of intraluminal tracts. Implementations of real-time endoscopic OCT using a rotary joint, a PZT transducer and a MEMS micromirror have been reported11

11. G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography,” Science 276, 2037–2039 (1997). [CrossRef] [PubMed]

, 18–20

18. F. I. Feldchtein, V. M. Gelikonov, G. V. Gelikonov, A. M. Sergeev, N. D. Gladkova, A. V. Shakhov, N. M. Shakhova, L. B. Snopova, A. B. Terent’eva, E. V. Zagainova, Y. P. Chumakov, and I. A. Kuznetzova, “Endoscopic applications of optical coherence tomography,” Opt. Express 3, 257–270 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-257. [CrossRef] [PubMed]

, showing a great promise to leverage the diagnostic capability of current endoscopic modalities.

2. Methods

2.1 High-Performance OCT Imaging System

The principle of OCT is similar to that of ultrasound imaging. A schematic diagram of our OCT system used to perform 2D cross-sectional images presented in this study is shown in Fig. 1, which is based on a fiber-optic Michelson interferometer. This technique performs high-resolution optical ranging or tomographic measurement by taking advantage of the short temporal coherence of a broadband light source. A high-brightness, broadband light source was used for illumination. Its pigtailed output power I is 13mW, central wavelength λ̄ is 1320nm, and half-maximum-full-width (HMFW) spectral bandwidth Δλ. is 77nm, thus yielding a coherence length LC of roughly 10μm2

2. J. M. Schmitt, “Optical Coherence Tomography (OCT): A Review,” IEEE J. Sel. Top. Quantum Electron. 5, 1205–1215 (1999). [CrossRef]

,23

23. Yingtian Pan, Reginald Birngruber, Jurgen Rosperich, and Ralf Engelhardt, “Low-coherence optical tomography in turbid tissue: theoretical analysis,” Appl. Opt. 34, 6564–6574 (1995). [CrossRef] [PubMed]

. The broadband light was split equally into the reference and the sample arms of the fiberoptic Michelson interferometer. Because a low-coherence source was used, the recombined light in the detection fiber only coherently interfered when the pathlengths in the sample and reference arms were matched to within the short coherence length, Lc≈10μm. Thus, moving the reference mirror permitted tomographic determination of the pathlength-resolved distribution of the interference modulation of light from the reflecting interfaces within the biological tissue placed in the sample arm. This offers a unique advantage of OCT over any other optical imaging modality in that it circumvents the need to scan a bulky microscopic lens to accomplish high-resolution imaging. The axial reflectance profile, i.e., the envelope of the interferometric signal was detected at high sensitivity by using optical heterodyne detection, locking in the Doppler frequency shifted signal (fD = 2v/λ, v is the speed for reference mirror scan). This signal was bandpass filtered and envelope demodulated prior to feeding to a PC for image display. Scanning the reference mirror at stable and high speed yields a constant Doppler frequency for optical heterodyne detection, and is thus critical to real-time high-fidelity OCT imaging. In our system, this was accomplished by using a double-pass grating-lens based optical delay line, a techniques used for fs laser Fourier-transform pulse shaping22

22. Andrew Rollins, Joseph Izatt, Manish Kulkarni, Siavash Yazdanfar, and Rujchai Ung-arunyawee, “In vivo video rate optical coherence tomography”, Opt. Express 3, 219–229 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-219. [CrossRef] [PubMed]

. With proper settings of all the components, optical ranging up to 3mm was achieved at over 1kHz, thus allowing 2D OCT imaging at almost 4–8 frames/s.

In the sample arm, the light beam existing the fiber was collimated, deflected by a two-axis servo scanner, and then focused on the tissue specimen under examination with a microscopic objective (4x, NA0.1). A red laser diode (λ = 670 nm) along with a color camera was used to align the lateral position of the tissue specimen under examination; whereas the axial focusing of the incident beam was adjusted by the preset reference mirror position as precisely as less than 5 micrometers, taking advantage of the short source coherence length. A 2D cross-sectional image was produced by scanning the incident light beam across the tissue with a lateral servo scanner each time after the sequential reflectivity profile in the longitudinal direction was taken. The axial (Δz) and lateral (Δr) resolutions of the OCT system are determined by the coherence length and the microscopic lens used in the probe beam, respectively. The axial resolution (Δz) is 23

23. Yingtian Pan, Reginald Birngruber, Jurgen Rosperich, and Ralf Engelhardt, “Low-coherence optical tomography in turbid tissue: theoretical analysis,” Appl. Opt. 34, 6564–6574 (1995). [CrossRef] [PubMed]

,24

24. M. E. Brezinski and J. G. Fujimoto, “Optical Coherence Tomography: High-Resolution Imaging in Nontransparent Tissue,” IEEE J. Sel. Top. Quantum Electron. 5, 1185–1192 (1999). [CrossRef]

Δz=LC=(2ln2π)·(λ¯2Δλ)
(1)

The lateral or transverse resolution is determined by the focused spot size in analogy with conventional microscopy and is

Δr=2λ0πNA=4λ0fπϕ
(2)

where NA = ϕ/2f is the numerical aperture of the microscopic lens, f is the focal length of the microscopic lens and ϕ is the spot size of the light beams exiting the fiber optic collimator. For the OCT setup used in this study, they were roughly 10μm, respectively.

Fig. 1. Schematic diagram of the fiber optic OCT system. BBS: broadband light source; LD: aiming laser diode; PD: photo diode; CM: fiber-optic collimator. High-speed reference mirror scanning is grating-lens delay line.

2.2 Optical modeling

To characterize OCT with histology for micro morphological changes induced by tumorigenesis, a controllable bladder tumor model was used by way of instillation of proper doses of a chemical carcinogen, MNU, into the bladder of Fisher rats. At different time points, e.g., at week 20, 24, 30, 36, the intact rat bladders were harvested, properly stretched and mounted onto ϕ10mm ring holders filled with 37°C modified Ringer's buffer solution. The apical or urothelial side of the bladder was faced up for cystoscope-like surface imaging, OCT, and H&E stained histology. The lateral positions of the OCT scan were precisely tattooed in Indian ink with the help of a red aiming laser and color CCD camera to guide later histological sectioning and light microscopy.

For the simulation study of different types of bladder inflammatory lesions, 3 groups of a total of 9 fresh normal rat bladder samples were mounted on ring holders to allow OCT imaging and the section scanned by OCT were pinned by a pair of 32 gauge needles as landmarks. Then, for group 1 and group 2, approximately 5 μl 0.9% saline and fresh whole blood previously taken from the same animal were injected into the submucosal layer of the sections previously scanned by OCT to simulate edema and severe edema with vasodilation, respectively. For group 3, the same amount of 10% intralipid was injected into submucosa to simulate accumulated inflammatory cells and other types of inflammatory infiltrate (e.g., necrosis, fibrosis) with increased scattering. Microinjection was performed under a stereo dissecting microscope using 32 gauge needles. A comparison between OCT images prior to and post microinjection allowed us to characterize OCT images for the changes of submucosal morphology and the resultant optical properties of bladder inflammatory lesions.

Unfortunately, complicated wave optical effects (e.g. multiple scattering and speckle effects) in random medium such as biological tissue have hindered theoretical modeling of OCT; presently, there is no analytical or numerical model that can effectively analyze the OCT image contrast with respect to the histological evaluations. To tackle the challenge, we explored this complicated problem by combining analytical modeling with experimental measurements. For each tumor sample, multiple OCT scans were performed and followed by histological sections on the same areas. The H&E stained histological sections were photographed by a 4k×3k-pixel color digital CCD camera. Once hyperplastic, dysplastic and neoplastic lesions in these samples were identified, image processing was applied to the areas of the urothelium with pathological alternations. In the optical modeling of cellular scattering, we neglected the contributions of other scattering sources, e.g., mitochondria, cytoplastic contents and intercellular boundaries, and assumed that nuclei were the primary scattering sources of urothelial cells. Then, the urothelium was optically simplified as a 2D matrix consisting of scattering centers (nuclei) with refractive index of nN = 1.52 surrounded by a nonscattering solution with nC=1.38. The nuclei were assumed to be spherical and their sizes were counted to yield the mean nuclear size (dN) and ‘2D’ volumetric density ρs for scattering calculation. For mathematic simplicity, we further assumed all scattering centers were uniformly distributed, and the simplified urothelial model became a uniform 3D scattering matrix with equal particle size of dN and refractive index of nN. The 3D volumetric particle density ρv were calculated according to the relation,

ρv=1.33ρs32
(3)

I˜d(Lr)=2IsIr·[R(Ls)C(Ls)]
(4)

where Ir is light intensity in the reference arm, IS is the light incident on the biological tissue. C(LS) =exp ⌊- 4(Ls/Lc)2⌋cos k̄Ls is low-coherence function, and R(LS) is the pathlength-resolved reflectance. Urothelium is a thin and relatively low-scattering tissue (except large papillary neoplastic lesions). Assuming that light scattering within the urothelial layer is homogeneous and within the single scattering regime; then, we could approximate the relations, LS = 2ncz (z is geometric depth), R(LS) ≅ μbe-μs2z. Thus, Eq.(4) can be simplified as

I˜d(z)=kI0μbeμSzΔLLCe4(ΔLLc)2cosk¯ΔL
(5)

The modular term relates to the speckle effect, i.e., the summation of the backscattered light fields from a local volume (ΔL≤Lc) containing a large collection of particles (nuclei), each of which has a probability of scattering light at different angles, polarization directions, and at different delays or phase shifts depending on the geometric distribution. Therefore, we can neglect the speckle effects and characterize the ‘speckle-free’ OCT image contrast changes on lesions during tumorigenesis by evaluating the first term √μb esz base on the measured histological distribution and the model analysis stated above.

3. Results

Fig. 2. OCT images of a normal rabbit bladder (A) and rabbit bladder samples injected with saline (B), blood (C) and intralipid (D). U: urothelium, SM: submucosa, M: muscular layers.

Panel A is the OCT image of a normal rat bladder. The three layers were clearly delineated based on their scattering difference and structural characteristics: the loosely stretched urothelium (U) is shown as a low scattering thin layer (~55μm thick), the submucosa (SM) is shown as a homogeneous high scattering layer (~190μm thick). Because of scattering induced light lose, the ~240μm thick muscular layers (M) is shown as less bright than SM but can be identified by the boundaries of bifurcated collagen bundles. Panel B is the OCT image following ~5μl 0.9% saline injection to simulate early edema with fluid buildup. Because of low viscosity, some saline might flow out of the bladder wall through the injection hole; however, minor swelling in SM is clearly visible (~280μm thick). In addition to the dark stripes filled with saline, the overall SM is slightly less scattering than that the normal SM in Panel A possibly resulted from saline perfusion. Like Panel A, the underlying bladder wall is clearly visible. Panel C is the OCT image following ~5μl whole bladder injection to simulate SM edema with vasodilation. The injection hole is not shown in the cross section; however, moderate swelling in SM is clearly visible (~350μm thick). Compared with Panels A and B, a substantial decrease of backscattering in SM is observed following microinjection of blood; and as a result, the underlying bladder morphology disappears. Panel D is the OCT image following ~5μl 10% intralipid injection to simulate accumulated inflammatory cells and other types of inflammatory lesions in SM resulting in increased scattering (e.g., necrosis fibrosis). Swelling in SM is detected (~310μm thick). Compared with Panel C, a localized increase of backscattering in the injected SM is observed following microinjection of intralipid. As a result, the underlying bladder morphology became less clear than Panels A and B.

Fig. 3. Histologic pictures of normal, hyperplastic, dysplastic, and neoplastic urothelial cells.

Figure 3 shows a group of H&E stained histological pictures of rat bladders at four critical stages of tumorigenesis: Panels A-D are normal, hyperplastic, dysplastic and neoplastic urothelia, respectively. By comparing the nuclear morphology, we can see that the hyperplastic lesion (B) depicts a similar distribution to that of normal urothelium (A) except the increase in cell layers or depth; whereas the dysplastic and neoplastic lesions (C and D) show not only increase in urothelial thickness but also increase in nuclear density and loss of polarity. In addition, Panel D also depicts heavy vascularization, which is typical for transitional cell cancers. Further image analysis of nuclear morphology in these pictures leads to the size of nuclei and their volumetric distributions as presented in Table 1.

Table 1 reveals that from normal to neoplastic urothelia, the nuclear size decreases slightly from 7.25 μm to 6.14 μm whereas the nuclear density increases drastically from 0.0011/μm to 0.0025/μm resulting in an increased nuclear to cytoplastic ratio. Using the measured data Table 1 we can calculate the corresponding backscattering and scattering coefficients μb and μs according Mie theory of scattering and the resultant OCT signals using Eq. (5).

Table 1:. Histological evaluations of nuclear morphology

table-icon
View This Table

Fig. 4. Calculated results of backscattering changes as a function of nuclear morphology (e.g., size, density depicted in Fig. 3).

Figure 5 presents a pair of 2D OCT images of a hyperplastic lesion and a neoplastic lesion along with their histological pictures to validate the theoretical modeling. Two bladder samples were obtained at weeks 28 and 36 following MNU instillation. Although the bladder samples might have shrunk during histological processing, the overall micro morphology, e.g., U, SM and M provided by OCT correlates well with the histology. The thickened urothelia are indicated by U’. Normal urothelia under stretch were roughly 40–45μm thick. The hyperplastic lesion U’ in Panel A was 250μm or about 5 times thicker than the normal urothelium and the neoplastic lesion U’ in panel B was 900 μm or almost 20 times thicker the normal urothelium, both of which were substantially thickened. It is also demonstrated that the backscattering increases slightly from normal to hyperplasia (≤25%) but noticeably from hyperplasia to neoplasia (≥70%) in Fig. 5.

Fig. 5. Comparisons of hyperplastic and neoplastic rat bladders imaged by OCT with histology. U: normal urothelium, SM: submucosa, M: muscular layer, U’: diseased urothelium.

Fig. 6. A-scans on the normal, hyperplastic and neoplastic regions acquired from the OCT images in Fig. 5. Consecutive A-scans were averaged to reduce speckle noises.

4. Discussion

Our theoretical model was semi-analytical and relied on histomorphometric evaluations as input, which is not readily available in most cases. It was mathematically simplified based on assumptions that nuclei were the primary scattering contributors, and were spherical, homogeneously distributed and in the single-scattering regime. Nevertheless, the results revealed that this model provided useful explanations to analyze the effects of subcellular morphological changes of tumorigenesis on the resultant OCT signature or contrast as a result of backscattering changes. Further improvement of the theoretical model will consider the heterogeneous nature of the urothelium (e.g., umbrella, intermediate and basal cell layers), loss of polarity (e.g., orientation of elongated nuclei), blood scattering and absorption due to microvascularization in the neoplastic urothelium to provide more precise analyses of these changes on OCT contrast.

The experiments presented in this study were ex vivo because rats, the only controllable animal model to generate transitional cell cancers by MNU installation, are too small to perform cystoscopy. However, we have developed and refined OCT endoscopes based on microelectromechanical system (MEMS) technology19

19. Y. Pan, H. Xie, and G. K. Fedder, “Endoscopic optical coherence tomography based on a microelectromechanical mirror,” Opt. Lett. 26, 1966–1968 (2001). [CrossRef]

, 21

21. Tuqiang Xie, Zhigang Li, Mark L. Zeidel, and Yingtian Pan, “Optical imaging diagnostics of bladder tissue with optical coherence tomography”, Proc. SPIE 4609, in print.

that have demonstrated image resolution and contrast close to the bench-top setup used in this study. We are in the process to launch in vivo study for the detection of TCCs and carcinomas in situ based on the expertise we have accumulated in the current systematical studies using this controllable animal tumor model. On the other hand, recent technological advances in ultra-broadband fs laser technology have permitted subcellular OCT at 1–3μm resolution16

16. W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, “In vivo ultrahigh-resolution optical coherence tomography”, Opt. Lett. 24, 1221–1223 (1999). [CrossRef]

, 24

24. M. E. Brezinski and J. G. Fujimoto, “Optical Coherence Tomography: High-Resolution Imaging in Nontransparent Tissue,” IEEE J. Sel. Top. Quantum Electron. 5, 1185–1192 (1999). [CrossRef]

, thus immensely enhancing the sensitivity and specificity of OCT for the diagnoses of bladder cancers and other types of epithelial cancers. These OCT technological developments and clinical applications have demonstrated the potential of endoscopic OCT for noninvasive or minimally invasive and instantaneous ‘optical biopsy’ or ‘optically guided biopsy’ to diagnose and stage early-stage cancers. Recent studies have showed that 5-aminolevulinic acid (5-ALA) induced fluorescence endoscopy has demonstrated the potential to enhance the diagnosis of malignant/dysplastic bladder lesions30–31

30. M. Kriegmair, R. Baumgartner, R. Knuechel, H. Stepp, F. Hofstaedter, and A. Hofstetter, “Detection of early bladder cancer by 5-aminolevulinic acid induced porphyrin fluorescence,” J. of Urology 155, 105–110 (1996). [CrossRef]

; and our recent ex vivo study suggests that a new systoscopic suite guiding OCT with a 5-ALA fluorescence scope can drastically enhance the diagnostic specificity for precancerous lesions and reduce the time needed to scan the entire bladder (submitted to J. of Urology).

5. Conclusions

In summary, OCT has demonstrated the capability to delineate urinary bladder morphology, e.g., urothelium, submucosa and upper muscular layers as evidenced by the corresponding histology. Our model study confirms that OCT may be able to identify different types of submucosal inflammatory lesions based on the difference of scattering and absorption patterns in these lesions. Based on histomorphometric evaluation of nuclear morphology, the proposed semi-analytical model predicts a minor difference (<25%) in backscattering between normal and hyperplastic urothelia and a substantial increase (70%) between hyperplastic and neoplastic urothelia, which is approximately in agreement with OCT measurements. These results demonstrate that OCT has the potential to differentiate normal bladder, inflammatory lesion, urothelial precancer and TCC by analyzing the location of the lesion, urothelial thickening and backscattering. Overall, OCT has the potential to serve as useful biopsy-guiding tool for noninvasive or minimally invasive diagnosis of bladder tumors to reduce random, negative biopsies.

Acknowledgements

This research was supported in part by grants from the Whitaker Foundation (Y. P.) and the National Institutes of Health (Y. P., M, Z.). Special thanks to Susan Meyers and R. Ramage in the Department of Medicine, University of Pittsburgh for handling the animal studies. Please address future correspondence to Y. -T. Pan by email at yingtian.pan@sunysb.edu.

References and links

1.

http://www.cancernews.com/category.asp?cat=28&aid=235, “Diagnosis and Treatment of Bladder Cancer.”

2.

J. M. Schmitt, “Optical Coherence Tomography (OCT): A Review,” IEEE J. Sel. Top. Quantum Electron. 5, 1205–1215 (1999). [CrossRef]

3.

A. F. Fercher, K. Mengedoht, and W. Werner, “Eye length measurement by interferometry with partially coherent light,” Opt. Lett. 13, 186–188 (1988). [CrossRef] [PubMed]

4.

D. Huang, E. A. Swanson, and C. P. Lin, et al., “Optical coherence tomography,” Science 254, 1178–1181 (1991). [CrossRef] [PubMed]

5.

Y. Pan, J. P. Lavelle, S. Meyers, G. Pirtskhalaishvili, M. L. Zeidel, and D. L. Frakas, “Detection of tumorigenesis in rat bladders with optical coherence tomography,” Med. Phys. 28, 2432–2440 (2001). [CrossRef]

6.

E. A. Swanson, J. A. Izatt, M. R. Hee, D. Huang, C. A. Puliafito, J. S. Schuman, and J. G. Fujimoto, “In vivo retinal imaging by optical coherence tomography,” Opt. Lett. 18, 1864 (1993). [CrossRef] [PubMed]

7.

C. A. Puliafito, M. R. Hee, J. S. Schuman, and J. G. Fujimoto, Optical Coherence Tomography of Ocular Diseases (SLACK, Thorofare, NJ, 1996).

8.

A. M. Sergeev, V. M. Gelikonov, G. V. Gelikonov, F. I. Feldchtein, K. I. Pravdenko, D. V. Shabanov, N. D. Gladkova, V. V. Pochinko, V. A. Zhegalov, G. I. Dmitriev, I. R. Vazina, G. A. Petrova, and N. K. Nikulin, “In vivo optical coherence tomography of human skin microstructure,” Proc. SPIE 2328, 144–150 (1994). [CrossRef]

9.

J. Welzel, “Optical coherence tomography in dermatology: a review,” Skin Research and Technology 7, 1–9 (2001). [CrossRef] [PubMed]

10.

B. W. Colston, U. S. Sathyam, L. B. DaSilva, M. J. Everett, P. Stroeve, and L. L. Otis, “Dental OCT,” Opt. Express 3, 230–238 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-230. [CrossRef] [PubMed]

11.

G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography,” Science 276, 2037–2039 (1997). [CrossRef] [PubMed]

12.

A. M. Sergeev, V. M. Gelikonov, G. V. Gelikonov, F. I. Feldchtein, R. V. Kuranov, N. D. Gladkova, N. M. Shakhova, L. B. Snopova, A. V. Shakhov, I. A. Kuznetzova, A. N. Denisenko, V. V. Pochinko, Yu. P. Chumakov, and O. S. Streltzova, “In vivo endoscopic OCT imaging of precancer and cancer states of human mucosa,” Opt. Express 1, 432–440 (1997), http://epubs.osa.org/oearchive/source/2788.htm. [CrossRef] [PubMed]

13.

Johannes F. de Boer, Shyam M. Srinivas, Arash Malekafzali, Zhongping Chen, and J. Stuart Nelson, “Imaging thermally damaged tissue by polarization sensitive optical coherence tomography,” Opt. Express 3, 212–218 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-212. [CrossRef] [PubMed]

14.

Gang Yao and Lihong Wang, “Propagation of polarized light in turbid media: simulated animation sequences”, Opt. Express 7, 198–203 (2000), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-7-5-198. [CrossRef] [PubMed]

15.

M. Wojtkowski, A. Kowalczyk, R. Leitgeb, and A. F. Fercher, “Full range complex spectral optical coherence tomography technique in eye imaging,” Opt. Lett. 27, 1415–1417 (2002). [CrossRef]

16.

W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, “In vivo ultrahigh-resolution optical coherence tomography”, Opt. Lett. 24, 1221–1223 (1999). [CrossRef]

17.

Volker Westphal, Siavash Yazdanfar, Andrew M. Rollins, and Joseph A. Izatt “Real-time, high velocity-resolution color Doppler optical coherence tomography”, Opt. Lett. 27, 34–36 (2002). [CrossRef]

18.

F. I. Feldchtein, V. M. Gelikonov, G. V. Gelikonov, A. M. Sergeev, N. D. Gladkova, A. V. Shakhov, N. M. Shakhova, L. B. Snopova, A. B. Terent’eva, E. V. Zagainova, Y. P. Chumakov, and I. A. Kuznetzova, “Endoscopic applications of optical coherence tomography,” Opt. Express 3, 257–270 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-257. [CrossRef] [PubMed]

19.

Y. Pan, H. Xie, and G. K. Fedder, “Endoscopic optical coherence tomography based on a microelectromechanical mirror,” Opt. Lett. 26, 1966–1968 (2001). [CrossRef]

20.

T. Xie, H. Xie, G. K. Fedder, M. Zeidel, and Y. Pan, “Endoscopic Optical Coherence Tomography with a Micromachined Mirror,” 2nd Annual International IEEE-EMBS, Madison, Wisconsin, USA, May 2–4, 208–211 (2002).

21.

Tuqiang Xie, Zhigang Li, Mark L. Zeidel, and Yingtian Pan, “Optical imaging diagnostics of bladder tissue with optical coherence tomography”, Proc. SPIE 4609, in print.

22.

Andrew Rollins, Joseph Izatt, Manish Kulkarni, Siavash Yazdanfar, and Rujchai Ung-arunyawee, “In vivo video rate optical coherence tomography”, Opt. Express 3, 219–229 (1998), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-219. [CrossRef] [PubMed]

23.

Yingtian Pan, Reginald Birngruber, Jurgen Rosperich, and Ralf Engelhardt, “Low-coherence optical tomography in turbid tissue: theoretical analysis,” Appl. Opt. 34, 6564–6574 (1995). [CrossRef] [PubMed]

24.

M. E. Brezinski and J. G. Fujimoto, “Optical Coherence Tomography: High-Resolution Imaging in Nontransparent Tissue,” IEEE J. Sel. Top. Quantum Electron. 5, 1185–1192 (1999). [CrossRef]

25.

William M. Murphy, Bruce Beckwith, and George M. FarrowTumors of the kidney, bladder and related urinary structures, Chapter 2 (Armed Forces Institute of Pathology, Washington, 1994).

26.

J M Schmitt, A Knuttel, M Yadlowsky, and M A Bckhause, “Optical-coherence tomography of a dense tissue: statistics of attention of backscattering,” Phys. Med. Biol. 39,1705–1720 (1993). [CrossRef]

27.

J. M. Schmitt and A. Knuttel, “Model of optical coherence tomography of heterogeneous tissue,” J. Opt. Soc. Am. A 14, 1231–1242 (1997). [CrossRef]

28.

M. Kowalevicz, T. Ko, I. Hartl, J. G. Fujimoto, M. Pollnau, and R. P. Salathe, “Ultrahigh resolution optical coherence tomography using a superluminescent light source,” Opt. Express 10, 349–353, 2002. [CrossRef] [PubMed]

29.

Gang Yao and Lihong V Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44, 2307–2320 (1999). [CrossRef] [PubMed]

30.

M. Kriegmair, R. Baumgartner, R. Knuechel, H. Stepp, F. Hofstaedter, and A. Hofstetter, “Detection of early bladder cancer by 5-aminolevulinic acid induced porphyrin fluorescence,” J. of Urology 155, 105–110 (1996). [CrossRef]

31.

F. Koenig, F. J. McGovern, R. Larne, H. Enquist, K. T. Schomacker, and T. F. Deutsch, “Diagnosis of bladder carcinoma using protoporphyrin IX fluorescence induced by 5-aminolaevulinic acid,” BJU International 83, 129–135 (1999). [CrossRef] [PubMed]

OCIS Codes
(110.4500) Imaging systems : Optical coherence tomography
(170.3880) Medical optics and biotechnology : Medical and biological imaging

ToC Category:
Research Papers

History
Original Manuscript: October 10, 2002
Revised Manuscript: November 21, 2002
Published: December 2, 2002

Citation
T. Xie, M. Zeidel, and Yingtian Pan, "Detection of tumorigenesis in urinary bladder with optical coherence tomography: optical characterization of morphological changes," Opt. Express 10, 1431-1443 (2002)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-10-24-1431


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References

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  11. G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, �??In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography,�?? Science 276, 2037-2039 (1997). [CrossRef] [PubMed]
  12. A. M. Sergeev, V. M. Gelikonov, G. V. Gelikonov, F. I. Feldchtein, R. V. Kuranov, N. D. Gladkova, N. M. Shakhova, L. B. Snopova, A. V. Shakhov, I. A. Kuznetzova, A. N. Denisenko, V. V. Pochinko, Yu. P. Chumakov, and O. S. Streltzova, "In vivo endoscopic OCT imaging of precancer and cancer states of human mucosa," Opt. Express 1, 432-440 (1997), <a href="http://epubs.osa.org/oearchive/source/2788.htm">http://epubs.osa.org/oearchive/source/2788.htm</a>. [CrossRef] [PubMed]
  13. Johannes F. de Boer, Shyam M. Srinivas, Arash Malekafzali, Zhongping Chen, and J. Stuart Nelson, �??Imaging thermally damaged tissue by polarization sensitive optical coherence tomography,�?? Opt. Express 3, 212-218 (1998), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-212">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-212</a>. [CrossRef] [PubMed]
  14. Gang Yao, Lihong Wang, �??Propagation of polarized light in turbid media: simulated animation sequences,�?? Opt. Express 7, 198-203 (2000), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-7-5-198">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-7-5-198</a>. [CrossRef] [PubMed]
  15. M. Wojtkowski, A. Kowalczyk, R. Leitgeb, A. F. Fercher, �??Full range complex spectral optical coherence tomography technique in eye imaging,�?? Opt. Lett. 27, 1415-1417 (2002). [CrossRef]
  16. W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, �??In vivo ultrahigh-resolution optical coherence tomography,�?? Opt. Lett. 24, 1221-1223 (1999). [CrossRef]
  17. Volker Westphal, Siavash Yazdanfar, Andrew M. Rollins, Joseph A. Izatt, �??Real-time, high velocityresolution color Doppler optical coherence tomography,�?? Opt. Lett. 27, 34-36 (2002). [CrossRef]
  18. F. I. Feldchtein, V. M. Gelikonov, G. V. Gelikonov, A. M. Sergeev, N. D. Gladkova, A. V. Shakhov, N. M. Shakhova, L. B. Snopova, A. B. Terent�??eva, E. V. Zagainova, Y. P. Chumakov, and I. A. Kuznetzova, �??Endoscopic applications of optical coherence tomography,�?? Opt. Express 3, 257- 270 (1998), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-257">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-257</a>. [CrossRef] [PubMed]
  19. Y. Pan, H. Xie, and G. K. Fedder, �??Endoscopic optical coherence tomography based on a microelectromechanical mirror,�?? Opt. Lett. 26, 1966-1968 (2001). [CrossRef]
  20. T. Xie, H. Xie, G. K. Fedder, M. Zeidel, and Y. Pan, �??Endoscopic Optical Coherence Tomography with a Micromachined Mirror,�?? 2nd Annual International IEEE-EMBS, Madison, Wisconsin, USA, May 2-4, 208-211 (2002).
  21. Tuqiang Xie, Zhigang Li, Mark L. Zeidel, Yingtian Pan, �??Optical imaging diagnostics of bladder tissue with optical coherence tomography,�?? Proc. SPIE 4609, in print.
  22. Andrew Rollins, Joseph Izatt, Manish Kulkarni, Siavash Yazdanfar, Rujchai Ung-arunyawee, �??In vivo video rate optical coherence tomography,�?? Opt. Express 3, 219-229 (1998), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-219">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-3-6-219</a>. [CrossRef] [PubMed]
  23. Yingtian Pan, Reginald Birngruber, Jurgen Rosperich, and Ralf Engelhardt, �??Low-coherence optical tomography in turbid tissue: theoretical analysis,�?? Appl. Opt. 34, 6564-6574 (1995). [CrossRef] [PubMed]
  24. M. E. Brezinski and J. G. Fujimoto, �??Optical Coherence Tomography: High-Resolution Imaging in Nontransparent Tissue,�?? IEEE J. Sel. Top. Quantum Electron. 5, 1185-1192 (1999). [CrossRef]
  25. William M. Murphy, Bruce Beckwith, George M. Farrow, Tumors of the kidney, bladder and related urinary structures, Chapter 2 (Armed Forces Institute of Pathology, Washington, 1994).
  26. J M Schmitt, A Knuttel, M Yadlowsky and M A Bckhause, �??Optical-coherence tomography of a dense tissue: statistics of attention of backscattering,�?? Phys. Med. Biol. 39, 1705-1720 (1993). [CrossRef]
  27. J. M. Schmitt and A. Knuttel, �??Model of optical coherence tomography of heterogeneous tissue,�?? J. Opt. Soc. Am. A 14, 1231-1242 (1997). [CrossRef]
  28. M. Kowalevicz, T. Ko, I. Hartl, J. G. Fujimoto, M. Pollnau, and R. P. Salathe, �??Ultrahigh resolution optical coherence tomography using a superluminescent light source,�?? Opt. Express 10, 349-353, 2002, <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-10-7-349">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-10-7-349</a>. [CrossRef] [PubMed]
  29. Gang Yao and Lihong V Wang, �??Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,�?? Phys. Med. Biol. 44, 2307-2320 (1999). [CrossRef] [PubMed]
  30. M. Kriegmair, R. Baumgartner, R. Knuechel, H. Stepp, F. Hofstaedter and A. Hofstetter, "Detection of early bladder cancer by 5-aminolevulinic acid induced porphyrin fluorescence," J. Urology 155, 105-110 (1996). [CrossRef]
  31. F. Koenig, F. J. McGovern, R. Larne, H. Enquist, K. T. Schomacker and T. F. Deutsch, "Diagnosis of bladder carcinoma using protoporphyrin IX fluorescence induced by 5-aminolaevulinic acid," BJU International 83, 129-135 (1999). [CrossRef] [PubMed]

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