AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16–68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey–Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R^{2 adjusted} value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R^{2 adjusted} = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.

Rationale and Objectives: The objective of this study was to develop and validate a predictive magnetic resonance imaging (MRI) activity score for ileocolonic Crohn disease activity based on both subjective and semiautomatic MRI features. Materials and Methods: An MRI activity score (the “virtual gastrointestinal tract [VIGOR]” score) was developed from 27 validated magnetic resonance enterography datasets, including subjective radiologist observation of mural T2 signal and semiautomatic measurements of bowel wall thickness, excess volume, and dynamic contrast enhancement (initial slope of increase). A second subjective score was developed based on only radiologist observations. For validation, two observers applied both scores and three existing scores to a prospective dataset of 106 patients (59 women, median age 33) with known Crohn disease, using the endoscopic Crohn's Disease Endoscopic Index of Severity (CDEIS) as a reference standard. Results: The VIGOR score (17.1 × initial slope of increase + 0.2 × excess volume + 2.3 × mural T2) and other activity scores all had comparable correlation to the CDEIS scores (observer 1: r = 0.58 and 0.59, and observer 2: r = 0.34–0.40 and 0.43–0.51, respectively). The VIGOR score, however, improved interobserver agreement compared to the other activity scores (intraclass correlation coefficient = 0.81 vs 0.44–0.59). A diagnostic accuracy of 80%–81% was seen for the VIGOR score, similar to the other scores. Conclusions: The VIGOR score achieves comparable accuracy to conventional MRI activity scores, but with significantly improved reproducibility, favoring its use for disease monitoring and therapy evaluation.

Objective: To evaluate a semi-automatic method for delineation of the bowel wall and measurement of the wall thickness in patients with Crohn's disease. Methods: 53 patients with suspected or proven Crohn's disease were selected. Two radiologists independently supervised the delineation of regions with active Crohn's disease on MRI, yielding manual annotations (Ano1, Ano2). Three observers manually measured the maximal bowel wall thickness of each annotated segment. An active contour segmentation approach semi-automatically delineated the bowel wall. For each active region, two segmentations (Seg1, Seg2) were obtained by independent observers, in which the maximum wall thickness was automatically determined. The overlap between (Seg1, Seg2) was compared with the overlap of (Ano1, Ano2) using Wilcoxon's signed rank test. The corresponding variances were compared using the Brown-Forsythe test. The variance of the semi-automatic thickness measurements was compared with the overall variance of manual measurements through an F-test. Furthermore, the intraclass correlation coefficient (ICC) of semiautomatic thickness measurements was compared with the ICC of manual measurements through a likelihood-ratio test. Results: Patient demographics: median age, 30 years; interquartile range, 25-38 years; 33 females. The median overlap of the semi-automatic segmentations (Seg1 vs Seg2: 0.89) was significantly larger than the median overlap of the manual annotations (Ano1 vs Ano2: 0.72); p=1.4×1025. The variance in overlap of the semiautomatic segmentations was significantly smaller than the variance in overlap of the manual annotations (p=1.1×1029). The variance of the semi-automated measurements (0.46mm2) was significantly smaller than the variance of the manual measurements (2.90mm2, p=1.1×1027). The ICC of semi-automatic measurement (0.88) was significantly higher than the ICC of manual measurement (0.45); p=0.005. Conclusion: The semi-automatic technique facilitates reproducible delineation of regions with active Crohn's disease. The semi-automatic thickness measurement sustains significantly improved interobserver agreement. Advances in knowledge: Automation of bowel wall thickness measurements strongly increases reproducibility of these measurements, which are commonly used in MRI scoring systems of Crohn's disease activity.