BackgroundEmerging　evidence　underscores　smooth　muscle　hyperplasia　and　hypertrophy,　rather　than　fibrosis,　as　the　defining　characteristics　of　fibrostenotic　lesions　in　Crohn　disease　(CD).　However,　non-invasive　methods　for　quantifying　these　muscular　changes　have　yet　to　be　fully　explored.AimsTo　explore　the　application　value　of　radiomics　based　on　magnetic　resonance　imaging　(MRI)　post-contrast　T1-weighted　images　to　identify　muscular　alteration　in　CD　lesions　with　significant　inflammation.MethodsA　total　of　68　cases　were　randomly　assigned　in　this　study,　with　48　cases　allocated　to　the　training　dataset　and　the　remaining　20　cases　assigned　to　the　independent　test　dataset.　Radiomic　features　were　extracted　and　constructed　a　diagnosis　model　by　univariate　analysis　and　least　absolute　shrinkage　and　selection　operator　(LASSO)　regression.　Construct　a　nomogram　based　on　multivariate　logistic　regression　analysis,　integrating　radiomics　signature,　MRI　features　and　clinical　characteristics.ResultsThe　radiomics　model　constructed　based　on　the　selected　features　of　the　post-contrasted　T1-weighted　images　has　good　diagnostic　performance,　which　yielded　a　sensitivity　of　0.880,　a　specificity　of　0.783,　and　an　accuracy　of　0.833　[AUC　=　0.856,　95%　confidence　interval　(CI)　=　0.765-0.947].　Moreover,　the　nomogram　representing　the　integrated　model　achieved　good　discrimination　performances,　which　yielded　a　sensitivity　of　0.836,　a　specificity　of　0.892,　and　an　accuracy　of　0.864　(AUC　=　0.926,　95%　CI　=　0.865-0.988),　and　it　was　better　than　that　of　the　radiomics　model　alone.ConclusionsThe　radiomics　based　on　post-contrasted　T1-weighted　images　provides　additional　biomarkers　for　Crohn　disease.　Additionally,　integrating　DCE-MRI,　radiomics,　and　clinical　data　into　a　comprehensive　model　significantly　improves　diagnostic　accuracy　for　identifying　muscular　alteration.