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Research Papers

Computer recognition of cancer in the urinary bladder using optical coherence tomography and texture analysis

[+] Author Affiliations
Colleen A. Lingley-Papadopoulos

The George Washington University, Department of Electrical and Computer Engineering, Staughton 107, 707 22nd Street NW, Washington, DC 20052

Murray H. Loew

The George Washington University, Department of Electrical and Computer Engineering, Staughton 101, 707 22nd Street NW, Washington, DC 20052

Michael J. Manyak

Cytogen Corporation, Suite 3100, 650 College Road East, Princeton, New Jersey 08540

Jason M. Zara

The George Washington University, Department of Electrical and Computer Engineering, Staughton 107, 707 22nd Street NW, Washington, DC 20052

J. Biomed. Opt. 13(2), 024003 (April 14, 2008). doi:10.1117/1.2904987
History: Received May 18, 2007; Revised November 02, 2007; Accepted November 10, 2007; Published April 14, 2008
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The vast majority of bladder cancers originate within 600μm of the tissue surface, making optical coherence tomography (OCT) a potentially powerful tool for recognizing cancers that are not easily visible with current techniques. OCT is a new technology, however, and surgeons are not familiar with the resulting images. Technology able to analyze and provide diagnoses based on OCT images would improve the clinical utility of OCT systems. We present an automated algorithm that uses texture analysis to detect bladder cancer from OCT images. Our algorithm was applied to 182 OCT images of bladder tissue, taken from 68 distinct areas and 21 patients, to classify the images as noncancerous, dysplasia, carcinoma in situ (CIS), or papillary lesions, and to determine tumor invasion. The results, when compared with the corresponding pathology, indicate that the algorithm is effective at differentiating cancerous from noncancerous tissue with a sensitivity of 92% and a specificity of 62%. With further research to improve discrimination between cancer types and recognition of false positives, it may be possible to use OCT to guide endoscopic biopsies toward tissue likely to contain cancer and to avoid unnecessary biopsies of normal tissue.

Figures in this Article
© 2008 Society of Photo-Optical Instrumentation Engineers

Citation

Colleen A. Lingley-Papadopoulos ; Murray H. Loew ; Michael J. Manyak and Jason M. Zara
"Computer recognition of cancer in the urinary bladder using optical coherence tomography and texture analysis", J. Biomed. Opt. 13(2), 024003 (April 14, 2008). ; http://dx.doi.org/10.1117/1.2904987


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