Radiomics to Detect Inflammation and Fibrosis on Magnetic Resonance Enterography in Stricturing Crohn’s Disease

Abstract Background and Aims Non-invasive cross-sectional imaging via magnetic resonance enterography MRE offers excellent accuracy for the diagnosis of stricturing complications in Crohn’s disease CD but is limited in determining the degrees of fibrosis and inflammation within a stricture. We developed and validated a radiomics-based machine-learning model for separately characterizing the degree of histopathological inflammation and fibrosis in CD strictures and compared it to centrally read visual radiologist scoring of MRE. Methods This single-centre, cross-sectional study included 51 CD patients n = 34 for discovery; n = 17 for validation with terminal ileal strictures confirmed on diagnostic MRE within 15 weeks of resection. Histopathological specimens were scored for inflammation and fibrosis and spatially linked with corresponding pre-surgical MRE sequences. Annotated stricture regions on MRE were scored visually by radiologists as well as underwent 3D radiomics-based machine learning analysis; both were evaluated against histopathology. Results Two distinct sets of radiomic features capturing textural heterogeneity within strictures were linked with each of severe inflammation or severe fibrosis across both the discovery (area under the curve AUC = 0.69, 0.83 and validation AUC = 0.67, 0.78 cohorts. Radiologist visual scoring had an AUC = 0.67 for identifying severe inflammation and AUC = 0.35 for severe fibrosis. Use of combined radiomics and radiologist scoring robustly augmented identification of severe inflammation AUC = 0.79 and modestly improved assessment of severe fibrosis AUC = 0.79 for severe fibrosis over individual approaches. Conclusions Radiomic features of CD strictures on MRE can accurately identify severe histopathological inflammation and severe histopathological fibrosis, as well as augment performance of the radiologist visual scoring in stricture characterization.