Computer-Aided Diagnosis

Toward real-time quantification of fluorescence molecular probes using target/background ratio for guiding biopsy and endoscopic therapy of esophageal neoplasia

[+] Author Affiliations
Yang Jiang

University of Washington, Department of Bioengineering, Human Photonics Lab, Seattle, Washington, United States

Yuanzheng Gong, Eric J. Seibel

University of Washington, Department of Mechanical Engineering, Human Photonics Lab, Seattle, Washington, United States

Joel H. Rubenstein

University of Michigan, Division of Gastroenterology, Department of Internal Medicine, Ann Arbor, Michigan, United States

Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan, United States

Thomas D. Wang

University of Michigan, Division of Gastroenterology, Department of Internal Medicine, Ann Arbor, Michigan, United States

J. Med. Imag. 4(2), 024502 (May 24, 2017). doi:10.1117/1.JMI.4.2.024502
History: Received February 17, 2017; Accepted April 24, 2017
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Abstract.  Multimodal endoscopy using fluorescence molecular probes is a promising method of surveying the entire esophagus to detect cancer progression. Using the fluorescence ratio of a target compared to a surrounding background, a quantitative value is diagnostic for progression from Barrett’s esophagus to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC). However, current quantification of fluorescent images is done only after the endoscopic procedure. We developed a Chan–Vese-based algorithm to segment fluorescence targets, and subsequent morphological operations to generate background, thus calculating target/background (T/B) ratios, potentially to provide real-time guidance for biopsy and endoscopic therapy. With an initial processing speed of 2 fps and by calculating the T/B ratio for each frame, our method provides quasireal-time quantification of the molecular probe labeling to the endoscopist. Furthermore, an automatic computer-aided diagnosis algorithm can be applied to the recorded endoscopic video, and the overall T/B ratio is calculated for each patient. The receiver operating characteristic curve was employed to determine the threshold for classification of HGD/EAC using leave-one-out cross-validation. With 92% sensitivity and 75% specificity to classify HGD/EAC, our automatic algorithm shows promising results for a surveillance procedure to help manage esophageal cancer and other cancers inspected by endoscopy.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Yang Jiang ; Yuanzheng Gong ; Joel H. Rubenstein ; Thomas D. Wang and Eric J. Seibel
"Toward real-time quantification of fluorescence molecular probes using target/background ratio for guiding biopsy and endoscopic therapy of esophageal neoplasia", J. Med. Imag. 4(2), 024502 (May 24, 2017). ; http://dx.doi.org/10.1117/1.JMI.4.2.024502


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