Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Detection of tumorigenesis in urinary bladder with optical coherence tomography: optical characterization of morphological changes

Open Access Open Access

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

Full Article  |  PDF Article
More Like This
Enhancing early bladder cancer detection with fluorescence-guided endoscopic optical coherent tomography

Y. T. Pan, T. Q. Xie, C. W. Du, S. Bastacky, S. Meyers, and M. L. Zeidel
Opt. Lett. 28(24) 2485-2487 (2003)

Endoscopic optical coherence tomography with a modified microelectromechanical systems mirror for detection of bladder cancers

Tuqiang Xie, Huikai Xie, Gary K. Fedder, and Yingtian Pan
Appl. Opt. 42(31) 6422-6426 (2003)

Differential diagnosis of human bladder mucosa pathologies in vivo with cross-polarization optical coherence tomography

Elena Kiseleva, Mikhail Kirillin, Felix Feldchtein, Alex Vitkin, Ekaterina Sergeeva, Elena Zagaynova, Olga Streltzova, Boris Shakhov, Ekaterina Gubarkova, and Natalia Gladkova
Biomed. Opt. Express 6(4) 1464-1476 (2015)

Cited By

Optica participates in Crossref's Cited-By Linking service. Citing articles from Optica Publishing Group journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (6)

Fig. 1.
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.
Fig. 2.
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.
Fig. 3.
Fig. 3. Histologic pictures of normal, hyperplastic, dysplastic, and neoplastic urothelial cells.
Fig. 4.
Fig. 4. Calculated results of backscattering changes as a function of nuclear morphology (e.g., size, density depicted in Fig. 3).
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.
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.

Tables (1)

Tables Icon

Table 1: Histological evaluations of nuclear morphology

Equations (5)

Equations on this page are rendered with MathJax. Learn more.

Δ z = L C = ( 2 ln 2 π ) · ( λ ¯ 2 Δ λ )
Δ r = 2 λ 0 πNA = 4 λ 0 f πϕ
ρ v = 1.33 ρ s 3 2
I ˜ d ( L r ) = 2 I s I r · [ R ( L s ) C ( L s ) ]
I ˜ d ( z ) = k I 0 μ b e μ S z Δ L L C e 4 ( Δ L L c ) 2 cos k ¯ Δ L
Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.