Surface-based Characterization of Gastric Anatomy and Motility using Magnetic Resonance Imaging and Neural Ordinary Differential Equation
Gastrointestinal magnetic resonance imaging (MRI) provides rich spatiotemporal data about the volume and movement of the food inside the stomach, but does not directly report on the muscular activity of the stomach itself. Here we describe a novel approach to characterize the motility of the stomach wall that drives the volumetric changes of the gastric content. In this approach, a surface template was used as a deformable model of the stomach wall. A neural ordinary differential equation (ODE) was optimized to model a diffeomorphic flow that ascribed the deformation of the stomach wall to a continuous biomedical process. Driven by this diffeomorphic flow, the surface template of the stomach progressively changes its shape over time or between conditions, while preserving its topology and manifoldness. We tested this approach with MRI data collected from 10 Sprague Dawley rats under a lightly anesthetized condition. Our proposed approach allowed us to characterize gastric anatomy and motility with a surface coordinate system common to every individual. Anatomical and motility features could be characterized for each individual, and then compared and summarized across individuals for group-level analysis. As a result, high-resolution functional maps were generated to reveal the spatial, temporal, and spectral characteristics of muscle activity as well as the coordination of motor events across different gastric regions. The relationship between muscle thickness and gastric motility was also evaluated throughout the entire stomach wall. Such a structure-function relationship was used to delineate two distinctive functional regions of the stomach. These results demonstrate the efficacy of using GI-MRI to measure and model gastric anatomy and function. This approach described herein is expected to enable non-invasive and accurate mapping of gastric motility throughout the entire stomach for both preclinical and clinical studies.