PURPOSE

To build computed tomography enterography (CTE)-based multiregional radiomics model for distinguishing Crohn's disease (CD) from intestinal tuberculosis (ITB).

MATERIALS AND METHODS

A total of 105 patients with CD and ITB who underwent CTE were retrospectively enrolled. Volume of interest segmentation were performed on CTE and radiomic features were obtained separately from the intestinal wall of lesion, the largest lymph node (LN), and region surrounding the lesion in the ileocecal region. The most valuable radiomic features was selected by the selection operator and least absolute shrinkage. We established nomogram combining clinical factors, endoscopy results, CTE features, and radiomic score through multivariate logistic regression analysis. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the prediction performance. DeLong test was applied to compare the performance of the models.

RESULTS

The clinical-radiomic combined model comprised of four variables including one radiomic signature from intestinal wall, one radiomic signature from LN, involved bowel segments on CTE, and longitudinal ulcer on endoscopy. The combined model showed good diagnostic performance with an area under the ROC curve (AUC) of 0.975 (95% CI 0.953-0.998) in the training cohort and 0.958 (95% CI 0.925-0.991) in the validation cohort. The combined model showed higher AUC than that of the clinical model in cross-validation set (0.958 vs. 0.878, P = 0.004). The DCA showed the highest benefit for the combined model.

CONCLUSION

Clinical-radiomic combined model constructed by combining CTE-based radiomics from the intestinal wall of lesion and LN, endoscopy results, and CTE features can accurately distinguish CD from ITB.