Post written by Ryosuke Sato, MD, and Kazuyuki Matsumoto, MD, PhD, from the Department of Gastroenterology and Hepatology, Okayama University Hospital, Okayama, Japan.

Our study focused on developing and evaluating a novel imaging technique that combines artificial intelligence with peroral cholangioscopy to improve visualization of biliary strictures. We used cycle-consistent adversarial network (CycleGAN) technology to convert standard white-light imaging (WLI) into virtual indigo carmine chromoendoscopy (VICI) images, providing enhanced visualization of surface structures and lesion margins without the need for actual dye spraying.

It is crucial to accurately diagnose biliary strictures and determine lesion margins for proper surgical planning and better patient outcomes. Although peroral cholangioscopy has improved our ability to visualize these lesions, challenges remain in clearly identifying surface structures and lesion boundaries. Traditional indigo carmine spraying, which is helpful in GI endoscopy, is difficult to implement in the bile duct. We wanted to bridge this gap by developing a virtual alternative that could offer similar benefits.
Our study demonstrates that VICI provided superior visualization of surface structures and lesion margins compared with WLI and narrow-band imaging. The diagnostic accuracy improved when combining WLI with VICI (87.5%) compared with WLI alone (72.5%). These results suggest that VICI could serve as a valuable complementary tool alongside existing imaging modalities for evaluating biliary lesions. The technology shows particular promise in helping determine lesion extent, which is crucial for achieving complete surgical resection.
This technology represents a significant step forward in bringing advanced imaging capabilities to biliary endoscopy. Although further validation through prospective multicenter studies is needed, we believe VICI has the potential to become an essential tool in evaluation of biliary strictures, complementing existing modalities such as narrow-band imaging.

Graphical abstract
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