Colon wall motility: comparison of novel quantitative semi-automatic measurements using cine MRI.

BACKGROUND: Recently, cine magnetic resonance imaging (MRI) has shown promise for visualizing movement of the colonic wall, although assessment of data has been subjective and observer dependent. This study aimed to develop an objective and semi-automatic imaging metric of ascending colonic wall movement, using image registration techniques. METHODS: Cine balanced turbo field echo MRI images of ascending colonic motility were acquired over 2 min from 23 healthy volunteers (HVs) at baseline and following two different macrogol stimulus drinks (11 HVs drank 1 L and 12 HVs drank 2 L). Motility metrics derived from large scale geometric and small scale pixel movement parameters following image registration were developed using the post ingestion data and compared to observer grading of wall motion. Inter and intra-observer variability in the highest correlating metric was assessed using Bland-Altman analysis calculated from two separate observations on a subset of data. KEY RESULTS: All the metrics tested showed significant correlation with the observer rating scores. Line analysis (LA) produced the highest correlation coefficient of 0.74 (95% CI: 0.55-0.86), p < 0.001 (Spearman Rho). Bland-Altman analysis of the inter- and intra-observer variability for the LA metric, showed almost zero bias and small limits of agreement between observations (-0.039 to 0.052 intra-observer and -0.051 to 0.054 inter-observer, range of measurement 0-0.353). CONCLUSIONS & INFERENCES: The LA index of colonic motility derived from cine MRI registered data provides a quick, accurate and non-invasive method to detect wall motion within the ascending colon following a colonic stimulus in the form of a macrogol drink.

Dual registration of abdominal motion for motility assessment in free-breathing data sets acquired using dynamic MRI.

At present, registration-based quantification of bowel motility from dynamic MRI is limited to breath-hold studies. Here we validate a dual-registration technique robust to respiratory motion for the assessment of small bowel and colonic motility. Small bowel datasets were acquired in breath-hold and free-breathing in 20 healthy individuals. A pre-processing step using an iterative registration of the low rank component of the data was applied to remove respiratory motion from the free breathing data. Motility was then quantified with an existing optic-flow (OF) based registration technique to form a dual-stage approach, termed Dual Registration of Abdominal Motion (DRAM). The benefit of respiratory motion correction was assessed by (1) assessing the fidelity of automatically propagated segmental regions of interest (ROIs) in the small bowel and colon and (2) comparing parametric motility maps to a breath-hold ground truth. DRAM demonstrated an improved ability to propagate ROIs through free-breathing small bowel and colonic motility data, with median error decreased by 90% and 55%, respectively. Comparison between global parametric maps showed high concordance between breath-hold data and free-breathing DRAM. Quantification of segmental and global motility in dynamic MR data is more accurate and robust to respiration when using the DRAM approach.