No reliable method for evaluating intestinal fibrosis in Crohn’s disease (CD) exists; therefore, we developed a computed-tomography enterography (CTE)-based radiomic model (RM) for characterising intestinal fibrosis in CD.
This retrospective-multicentre study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at one of the three tertiary referral centres from January 2014 through June 2020. Bowel fibrosis was histologically classified as none-mild or moderate-severe. In the training cohort, 1454 radiomic features were extracted from venous-phase CTE, and a machine learning-based RM was developed based on the reproducible features using logistic regression. The RM was validated in an independent external test cohort recruited from three centres. The diagnostic performance of RM was compared with two radiologists’ visual interpretation of CTE using receiver operating characteristic (ROC) curve analysis.
In the training cohort, the area under the ROC curve (AUC) of RM for distinguishing moderate-severe from none-mild intestinal fibrosis was 0.888 (95% confidence interval [CI]: 0.818-0.957). In the test cohort, the RM showed robust performance across three centres with an AUC of 0.816 (95% CI: 0.706-0.926), 0.724 (95% CI: 0.526-0.923), and 0.750 (95% CI: 0.560-0.940), respectively. Moreover, the RM was more accurate than visual interpretations by either radiologist (#1 AUC=0.554; #2 AUC=0.598; both P<0.001) in the test cohort. Decision curve analysis showed that the RM provided a better net benefit to predicting intestinal fibrosis than the radiologists.
A CTE-based RM allows for accurate characterisation of intestinal fibrosis in CD.