Motility Mapping Quantification Using the Classical Optical Flow Algorithm for Small Bowel Crohn's Disease: Comparison with Balloon-assisted Enteroscopy Findings.

Abstract

To quantify bowel motility shown on cine MRI using the classical optical flow algorithm and compare it with balloon-assisted enteroscopy (BAE) findings in patients with Crohn's disease (CD). This retrospective study included 29 consecutive patients with CD who had undergone MR enterocolonography (MREC) and BAE between March and May 2017. We developed computer software to present motion vector magnitudes between consecutive cine MR images as bowel motility maps via a classical optical flow algorithm using the Horn-Schunck method. Cine MR images were acquired with a balanced steady-state free precession sequence in the coronal direction to capture small bowel motility. The small bowels were divided into three segments. In total, 63 bowel segments were assessed via BAE and MREC. Motility scores on the maps, simplified MR index of activity (sMaRIA), and MREC score derived from a 5-point MR classification were assessed independently by two radiologists and compared with the CD endoscopic index of severity (CDEIS). Correlations were assessed using Spearman's rank coefficient. The areas under the receiver-operating characteristic curve (AUCs) of motility score for differentiating CDEIS was calculated; a P value < 0.05 was considered statistically significant. Motility score was negatively correlated with CDEIS (r = -0.59 [P < 0.001] and -0.54 [P < 0.001]), and the AUCs of motility scores for detecting CDEIS ≥ 3 were 88.2% and 78.6% for observers 1 and 2, respectively. There were no significant differences in the AUC for detecting CDEIS ≥ 3 and CDEIS ≥ 12 between motility and sMaRIA or MREC score. The motility map was feasible for locally quantifying the bowel motility. In addition, the motility score on the map reflected the endoscopic inflammatory activity of each small bowel segment in patients with CD; hence, it could be used as a tool in objectively interpreting cine MREC to predict inflammatory activity in CD.