Fluorescence endoscopy is emerging for guiding biopsy and early cancer detection in the gastrointestinal tract. A multimodal scanning fiber endoscope (mmSFE) with 2 fluorescence labeled peptides is designed to image overexpressed biomarkers associated with esophageal adenocarcinoma (EAC) and high-grade dysplasia (HGD), thus detecting early neoplasia. Quantification of multiplexed fluorescence images is critical, which ‘red-flags’ suspicious regions and supports diagnosis. The Target/Background (T/B) ratio is calculated to quantitatively evaluate fluorescence images. However T/B ratios are based on fluorescence intensities alone, so adding morphological features can be critical to providing evidence for diagnosis. Moreover, currently the T/B ratio is calculated for a single fluorescence channel. A protocol for multiplexed fluorescence quantification is needed.
Materials and Methods: Peptides targeting EGFR and ErbB2 are labeled with NIR fluorescence Cy5 and IRdye800, respectively. A mmSFE with 2.4mm flexible shaft and wide-field forward-view imaging is designed to image these two near-infrared fluorophores with an additional reflectance channel for anatomical identification. In first-in-human clinical trials the two peptides are topically sprayed, briefly incubated, and then rinsed in subjects at high risk of EAC. Both fluorescence channels were captured simultaneously with the co-registered reflectance channel at 30Hz. After removing artifacts, frames were manually selected using morphological features. T/B ratios were then calculated for all fluorescence channels in selected frames.
Results and Conclusions: T/B ratios for HGD subjects are greater than for healthy subjects in at least one of the fluorescence channels. Future work will design algorithms to automatically select suspicious regions based on morphological features. More analysis will be performed based on co-registered fluorescence channels.
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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