Development and Validation of a Novel Computed-Tomography Enterography Radiomic Approach for Characterization of Intestinal Fibrosis in Crohn’s Disease

Background & Aims 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 characterizing intestinal fibrosis in CD. Methods This retrospective multicenter study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at 1 of the 3 tertiary referral centers 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 3 centers. The diagnostic performance of RM was compared with 2 radiologists’ visual interpretation of CTE using receiver operating characteristic (ROC) curve analysis. Results 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 3 centers 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 (radiologist 1, AUC = 0.554; radiologist 2, AUC = 0.598; both, P < .001) in the test cohort. Decision curve analysis showed that the RM provided a better net benefit to predicting intestinal fibrosis than the radiologists. Conclusions A CTE-based RM allows for accurate characterization of intestinal fibrosis in CD. 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 characterizing intestinal fibrosis in CD. This retrospective multicenter study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at 1 of the 3 tertiary referral centers 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 3 centers. The diagnostic performance of RM was compared with 2 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 3 centers 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 (radiologist 1, AUC = 0.554; radiologist 2, AUC = 0.598; both, P < .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 characterization of intestinal fibrosis in CD.