For a study, researchers wanted to see if texture analysis of contrast-enhanced magnetic resonance enterography (MRE) images could be used to diagnose the histologic type of Crohn’s disease (CD) stricture.

A search of the radiology report database yielded 25 juvenile patients with established CD who received MRE followed by intestinal resection within 30 days. MRE pictures were evaluated to identify strictures on enteric phase T1-weighted fat-suppressed images, which were then matched with histologic sectioning sites. Texture analysis was done using TexRAD software, with skewness, mean, entropy, and standard deviation parameters measured over the intestinal wall. All stricture histology specimens were evaluated by a pathologist for active mucosal inflammation and mural fibrosis. To discover textural parameters linked with stricture fibrosis, multivariate logistic regression, and analysis of variance were used.


There were 64 bowel segments from 25 patients (mean age 16 ± 2 years) with the imaging-histologic association that was included in the study. It is worth noting that all of the included strictures had undergone surgical resection, with MRE imaging accessible within 30 days. These intestinal segments had a histologic distribution that included 9 segments with active inflammation but no fibrosis, 23 segments with just fibrosis, and 32 mixed segments with active inflammation and fibrosis. Skewness, standard deviation, entropy, and mean texture analysis parameters were found to be independently linked with stricture fibrosis using bivariate regression analysis. With a goodness-of-fit rating of 0.995, stepwise logistic regression revealed that the combination of mean, skewness, and entropy texture predicted stricture fibrosis. A combination of threshold values for these three texture analysis characteristics properly classified 100% of the strictures in the research cohort as having or not having fibrosis.

MRE texture analysis (MRE-TA) texture characteristics can distinguish between different kinds of CD strictures and reliably diagnose fibrosis.