Vascularity can distinguish neoplastic from non-neoplastic bile duct lesions during digital single-operator cholangioscopy

Abstract

Background and aims: Various macroscopic features are proposed for the diagnosis of biliary lesions during digital single-operator cholangioscopy (DSOC); however, neovasculature may be one of the most reliable features of neoplasia. We aimed to evaluate the detection of neovasculature during DSOC to distinguish neoplastic from non-neoplastic bile duct lesions.

Methods: A retrospective, single-center, cohort study was used. Neovasculature was defined as the presence of irregular or "spider" vascularity on bile duct lesions. The accuracy of detection of neovasculature for the identification of neoplastic lesions was estimated using the histologic results, surgical specimens, and/or 6-month follow-up as the criterion standard. Interobserver agreement analysis (kappa value) was performed between 2 expert endoscopists and 3 nonexpert physicians.

Results: Ninety-five patients were included; the median age was 65.6 years (range, 20-93 years), and 51 (53.7%) patients were female. Signs of neovasculature were observed in 65 of 95 (68.4%) patients. Histology confirmed neoplasia in 48 of 95 (50.5%) patients, and 6-month follow-up survival confirmed neoplasia in 52 of 95 (54.7%) patients. The use of vascularity for identifying neoplastic lesions achieved an accuracy of 80%, sensitivity of 94%, specificity of 63%, positive predictive value of 75%, negative predictive value of 90%, positive likelihood ratio of 2.53 (95% confidence interval, 1.71-3.76), and negative likelihood ratio of 0.09 (95% confidence interval, 0.03-0.28). The interobserver and intraobserver agreement were excellent (κ > 80%; P < .001) between expert endoscopists and nonexpert physicians.

Conclusion: Detection of irregular or spider vascularity on bile duct lesions during DSOC evaluations accurately identifies biliary neoplastic lesions. Prospective multicenter trials are required to evaluate neovasculature as a single factor for predicting neoplasia.