Work

Quantitative Real‐Time MRI for the Assessment of Gastric Motility

Year: 2026

Type: article

Abstract: BACKGROUND: Current reference standards for measuring gastric emptying and motility are not considered optimal due to the time required, ionizing radiation, invasiveness, and spatial resolution. PURPOSE: To assess gastric motility using novel real-time dynamic magnetic resonance imaging in combination with static measurements for gastric emptying and training of an automated deep-learning-based segmentation pipeline. STUDY TYPE: Prospective. PARTICIPANTS: The study included 36 healthy volunteers (20 female, mean 24 ± 3 years) and three patients with diagnosed Crohn's disease. FIELD STRENGTH/SEQUENCES: Participants ingested water to assess fasting motility and pineapple juice for the postprandial state. 3 T, 3D spoiled gradient echo (GRE) sequence and real-time spoiled GRE. ASSESSMENT: Gastric emptying was measured by using the gastric volume, while motility was analyzed by tracking changes in the antrum's cross-sectional area and applying Fast Fourier Transformation. Segmentations were performed using a trained semantic segmentation model. STATISTICAL TESTS: Linear Mixed Model with continuous dependent variables and fixed effects. Models included a random intercept for participants. Statistical significance was defined as p = 0.05. RESULTS: = 64.24 ± 11.87 min). Contraction frequencies (fasted: 2.76 ± 0.43 cpm, fed: 2.89 ± 0.43 cpm) and velocities (fasted: 1.67 ± 0.38 mm/s, fed: 1.72 ± 0.37 mm/s) were within physiological ranges, with fasting conditions characterized by stronger occlusion compared to the fed. Measurements taken from three patients proved that the workflow could be used in a clinical context. DATA CONCLUSION: Real-time MRI with AI-based analysis enabled quantitative assessment of gastric emptying and motility, revealing physiological peristaltic parameters and state-dependent differences in occlusion. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 1.

Source: Journal of Magnetic Resonance Imaging

DOI: 10.1002/jmri.70243