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Approximately 13%–40% of patients with Crohn's disease (CD) show a primary loss of response to infliximab (IFX) therapy. Therefore, differentiating potential responders from primary nonresponders is clinically important. In this double‐center study, we developed and validated a computed tomography enterography (CTE)‐based radiomic signature (RS) for identification of CD patients at high risk of primary nonresponse (PNR) to IFX therapy, and demonstrated its incremental value to the clinical model. A total of 244 patients (training cohort, n = 119; test cohort 1, n = 51; test cohort 2, n = 74) were retrospectively recruited. Their clinical data and pretreatment CTE were retrieved and analyzed. All patients underwent IFX induction therapy. Reliability of clinical factors and radiomic‐based features were assessed with the area under the receiver operating characteristic curve (AUC). In all, 1130 radiomic features were extracted from the whole inflamed gut in CTE images. In training cohort and test cohorts 1 and 2, the RS that discriminated PNR to IFX therapy yielded AUCs of 0.848, 0.789, and 0.789, respectively (all p < 0.05). By combining the clinical predictors (C‐reactive protein, albumin, and body mass index) and RS, the radiomic‐clinical model showed an increase in predicting performance (AUCs: 0.864, 0.794, and 0.791, respectively; all p < 0.05). Decision curve analysis and net reclassification improvement demonstrated the clinical usefulness of the radiomic‐clinical model. In this study, the proposed RS showed potential as a clinical aid for the accurate identification of CD patients at high risk of PNR to IFX therapy before treatment. A combination of the RS and existing clinical factors might enable a step forward precise medicine.

Background: While the grading of intestinal fibrosis is closely related to the therapeutic strategy of patients with Crohn’s disease (CD), it has not yet been well resolved. Mesenteric abnormalities are inextricably linked to intestinal fibrosis. Objectives: We aimed to establish an optimal model for assessing intestinal fibrosis using computed tomography enterography (CTE) and clinical markers. Design: A total of 174 patients with CD between January 2014 and June 2020 were included in this retrospective multicentre study. Methods: All patients underwent CTE within 3 months prior to surgery. Intestinal fibrosis was pathologically scored as non-mild or moderate-to-severe. Selected imaging of the intestinal walls and mesentery and/or clinical factors were used to develop the diagnostic models. The area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the discrimination performance of the models. A decision curve analysis was performed to evaluate the clinical usefulness of the models. Results: One-, two-, and three-variable models were identified as possible diagnostic models. Model 1 [mesenteric creeping fat index (MCFI)], Model 2 (mesenteric oedema and MCFI), and Model 3 (mesenteric oedema, MCFI, and disease duration) were established. The AUCs of Model 1 in training and test cohorts 1 and 2 were 0.799, 0.859, and 0.693, respectively; Model 2 was 0.851, 0.833, and 0.757, respectively; and Model 3 was 0.832, 0.821, and 0.850, respectively. We did not observe any significant difference in diagnostic performance between the training and total test cohorts in any model (all p > 0.05). The decision curves showed that Model 3 had the highest net clinical benefit in test cohort 2. The nomogram of this optimal model was constructed by considering the favourable and robust performance of Model 3. Conclusion: A nomogram integrating mesenteric abnormalities on CTE with a clinical marker was optimal for differentiating between non-mild and moderate-to-severe fibrosis in patients with CD.

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