Predicting biliary stricture after liver transplantation based on CT imaging features combined with clinicopathological factors.

Objective: To investigate the value of computed tomography imaging features combined with clinicopathological factors in predicting patients' biliary stricture (BS) after liver transplantation and to identify patients at a high risk for BS.

Methods: The imaging data and clinicopathological factors of 178 recipients who underwent liver transplantation at the First People's Hospital of Kunming, were collected. The patients were randomly divided into training and validation set, patients were divided into BS (n = 46) and non-BS groups (n = 132). Independent risk factors to establish models were screened using logistic regression analysis. Predictive efficacy of the models was evaluated using the area under the receiver operating characteristic curve (AUC).

Results: BS occurred in 46 of 178 liver transplant recipients. Univariate analysis revealed that postoperative cholangitis, postoperative biliary calculi, and abdominal aorta and branch plaques were significant risk factors for biliary stricture after liver transplantation (p < 0.05). Further multivariate analysis showed that postoperative cholangitis (OR = 19.450, 95% CI: 2.150-176.010), postoperative biliary calculi (OR = 15.340, 95% CI: 1.530-154.060), and abdominal aorta and branch plaques (OR = 4.360, 95% CI: 1.760-10.810) were independent risk factors for biliary stricture after liver transplantation (p < 0.05). The prediction model constructed based on these risk factors revealed AUC values of 0.745 and 0.738 for the training and validation sets, respectively. The calibration curve demonstrated consistency between the predicted and actual values, and the decision curve highlighted the clinical benefit.

Conclusion: The nomogram based on independent risk factors effectively identified patients at high risk of BS post-liver transplantation.