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Optical Coherence Tomography in Urology

  • E. V. Zagaynova
  • N. D. Gladkova
  • O. S. Streltsova
  • G. V. Gelikonov
  • N. Tresser
  • F. I. Feldchtein
  • M. J. Manyak
  • N. M. Shakhova
Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)
Optical coherence tomography (OCT) has been used to evaluate tissue in nearly every genitourinary structure including the kidney, adrenal gland, ureter, bladder, seminal vesicle, prostate, urethra, testicle, and vas deferens. The most common urologic cancers, those of the prostate, kidney, and bladder, account for about 300,000 new cases of cancer per year in men with another 32,000 new renal and bladder cancer cases arising in women [1, 2]. The first OCT images of human urologic tissue ex vivo were demonstrated in 1997 paper [3] while the first in vivo OCT studies in urology were performed on the bladder urothelium in 1997 [4, 5]. Since then, a number of papers have been published exploring OCT for urological clinical applications. In brief, the spectrum of potential clinical use includes:
  • Differential diagnosis of urinary bladder conditions

  • Early detection of bladder neoplasia, including visualization of carcinoma in situ (Tis)

  • Preoperative planning and intraoperative guidance of surgery for adequate resection with maximal bladder preservation

  • Differentiation of fluorescent bladder lesions

  • Identification and preservation of neurovascular tissue during prostatectomy

  • Detection of capsular penetration of prostate cancer during prostatectomy

  • Preservation of retroperitoneal nerves during lymph node dissection for testicular cancer

  • Identification of dilated seminiferous tubules in evaluation of male infertility

  • Differentiation of renal tumors

Keywords

Bladder Cancer Optical Coherence Tomography Lamina Propria Optical Coherence Tomography Image Squamous Metaplasia 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • E. V. Zagaynova
  • N. D. Gladkova
  • O. S. Streltsova
  • G. V. Gelikonov
  • N. Tresser
  • F. I. Feldchtein
  • M. J. Manyak
  • N. M. Shakhova

There are no affiliations available

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