Integrating Radiomics With Clinicoradiological Scoring Can Predict High-Risk Patients Who Need Surgery in Crohn's Disease: A Pilot Study

Abstract

Background: Early identification of Crohn's disease (CD) patients at risk for complications could enable targeted surgical referral, but routine magnetic resonance enterography (MRE) has not been definitively correlated with need for surgery. Our objective was to identify computer-extracted image (radiomic) features from MRE associated with risk of surgery in CD and combine them with clinical and radiological assessments to predict time to intervention.

Methods: This was a retrospective single-center pilot study of CD patients who had an MRE within 3 months prior to initiating medical therapy. Radiomic features were extracted from annotated terminal ileum regions on MRE and combined with clinical variables and radiological assessment (via Simplified Magnetic Resonance Index of Activity scoring for wall thickening, edema, fat stranding, ulcers) in a random forest classifier. The primary endpoint was high- and low-risk groups based on need for surgery within 1 year of MRE. The secondary endpoint was time to surgery after treatment.

Results: Eight radiomic features capturing localized texture heterogeneity within the terminal ileum were significantly associated with risk of surgery within 1 year of treatment (P < .05); yielding a discovery cohort area under the receiver-operating characteristic curve of 0.67 (n = 50) and validation cohort area under the receiver-operating characteristic curve of 0.74 (n = 23). Kaplan-Meier analysis of radiomic features together with clinical variables and Simplified Magnetic Resonance Index of Activity scores yielded the best hazard ratio of 4.13 (P = (7.6 × 10-6) and concordance index of 0.71 in predicting time to surgery after MRE.

Conclusions: Radiomic features on MRE may be associated with risk of surgery in CD, and in combination with clinicoradiological scoring can yield an accurate prognostic model for time to surgery.

Keywords: Crohn’s disease; MRE; prognosis; radiomics; sMARIA; surgery.

Figure 1.

Overall experimental workflow for integrating radiomics, clinical variables, and radiological assessment to develop a prognostic model for time to surgery in Crohn’s disease via magnetic resonance (MR) enterography scans. AUC, area under the curve; HR, hazard ratio; sMARIA, Simplified Magnetic Resonance Index of Activity.

Figure 2.

Representative radiomic heatmaps overlaid within annotations of the terminal ileum on T2-weighted magnetic resonance imaging scans, depicting subtle differences between Crohn’s disease patients who did not get surgery or had surgery 13+ months after magnetic resonance enterography (left, low risk) and those who got surgery within 1 year of magnetic resonance enterography (right, high risk). Normalized intensities (top row) are not seen to be significantly different between risk groups (P > .05). By contrast, top-ranked radiomic features exhibit significant differences (P = .001 and P = .004) in local image heterogeneity between low-risk and high-risk patients.

Figure 3.

A, Receiver-operating characteristic curves comparing model performance between clinical variables (green), radiomics (blue), Simplified Magnetic Resonance Index of Activity (sMARIA) (red), and combined (black). Corresponding Kaplan-Meier curves for different feature sets based on median risk predictions from random forest models based on (B) clinical variables, (C) sMARIA scores, (D) radiomic descriptors, and (E) combined radiomics + sMARIA + clinical features. AUROC, area under the receiver-operating characteristic curve; CI, concordance index (See online version for color figure).

Figure 4.

Subgroup analysis of predictor performance within different Montreal subclassifications: (top) no complications (B1), (middle) stricturing (B2), and (bottom) penetrating (B3). Receiver-operating characteristic curves and confusion matrices depict differences in model performance between clinical variables, Simplified Magnetic Resonance Index of Activity (sMARIA) scores, radiomic descriptors, and combined radiomics + sMARIA + clinical features. FPR, false positive rate; ROC, receiver-operating characteristic; HR, hazard ratio; TPR, true positive rate.