Development of a Computed Tomography Enterography Based Radiomics Model to Characterize Inflammation, Fibrosis and Smooth Muscle Thickening in Stricturing Crohn's Disease.
Authors
Affiliations (10)
Affiliations (10)
- Department of Gastroenterology, Hepatology & Nutrition, Digestive Diseases and Surgery Institute, Cleveland Clinic, Cleveland, USA, [email protected]; [email protected].
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA. [email protected]; [email protected].
- Section of Abdominal Imaging, Imaging Department, Enterprise Diagnostic Institute, Cleveland Clinic, Cleveland, Ohio, USA. [email protected]; [email protected]; [email protected].
- Division of Anatomic Pathology, Robert J. Tomsich Department of Pathology and Laboratory Medicine, Diagnostics Institute, Cleveland Clinic, Cleveland, OH, USA. [email protected]; [email protected].
- Digestive Disease and Surgery Institute, Cleveland Clinic, Abu Dhabi, UAE. [email protected].
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, MN, USA. [email protected].
- Division of Pediatric Gastroenterology, Hepatology & Nutrition, Cleveland Clinic, Cleveland, OH, [email protected].
- Program for Global Translational Inflammatory Bowel Disease Research, Cleveland Clinic, Cleveland, OH, USA. [email protected].
- Louis Stokes VA Cleveland Medical Center, Cleveland, OH, USA.
- Departments of Pediatrics & Biomedical Engineering, Emory University, Atlanta, GA. [email protected].
Abstract
Computed tomography enterography (CTE) is a non-invasive cross-sectional imaging modality routinely used for diagnosis of Crohn's disease (CD) strictures. However, CTE is limited in individually defining the severity of inflammation, fibrosis or smooth muscle hyperplasia/hypertrophy (SMH) within such strictures. We developed and internally validated a radiomics-based machine-learning (ML) model for separately characterizing the degree of histopathologic inflammation, fibrosis, and SMH in CD strictures and compared it to centrally read visual radiologist scoring of CTE. This single-center, cross-sectional study included 100 CD patients (n=66 for discovery; n=34 for validation) with terminal ileal strictures confirmed on diagnostic CTE within 15 weeks of intestinal resection. Histopathological specimens were scored for inflammation, fibrosis, and SMH and spatially linked with corresponding pre-surgical CTE sequences. Annotated stricture regions on CTE were scored visually by radiologists as well as underwent three-dimensional radiomics-based ML analysis; both evaluated against histopathology scoring. Three distinct sets of radiomic features capturing textural heterogeneity within strictures were separately linked with severe inflammation, fibrosis, and SMH across both discovery (accuracy=0.74, 0.71, 0.71, respectively) and validation (accuracy=0.74, 0.68, 0.68, respectively) cohorts. Radiologist visual scoring was limited, with accuracy of 0.51 for identifying severe inflammation, 0.48 for severe fibrosis, and 0.58 for severe SMH. Augmenting radiologist scoring with radiomic features yielded improved performance in identifying severe inflammation, fibrosis, or SMH compared to radiologist scoring alone. Radiomic features of CD strictures on CTE can identify severe histopathologic fibrosis, inflammation, and smooth muscle hyperplasia and perform better than radiologist visual scoring in stricture characterization.