Abstract: Esophageal bolus transport and esophageal mechanics are quantified from medical imaging data, such as dynamic magnetic resonance imaging (“MRI”) data, computed tomography (“CT”) data, or the like. A machine learning model is used to process geometric or other spatiotemporal parameters of a bolus imaged with medical imaging in order to estimate quantitative parameters of the bolus and/or esophagus, such as cross-sectional area, fluid velocity, and fluid pressure. From these values, other parameters can be computed, such as esophageal stiffness and active relaxation.

Abstract: A catheter-based baro-hydrometer device measures or otherwise monitors esophageal function. The device includes a segmented balloon design, including a first and second balloon whose fill volumes can be independently controlled. In general, the device leverages secondary peristalsis related to balloon distention in order to study esophageal function. Pressure sensors coupled to the balloons record pressure data, which can be classified and processed to measure or otherwise monitor esophageal function.

Abstract: A fluid mechanics-based analysis tool is implemented to compute pressure field data, fluid velocity data, and/or muscular work data in a lumen or other tubular organ or structure from planimetry and pressure data (e.g., measured using a balloon dilation or other planimetry catheter). In this way, flow data can be estimated, which are otherwise insensible from current planimetry catheter technologies due to economic and/or manufacturing limitations.

Abstract: Flow through tubular organs (e.g., the esophagus) is analyzed based on fluid mechanics analysis of medical images. Using computational fluid dynamics, a reduced-order model is constructed and implemented to predict flow rate and fluid pressure developed inside flexible tubular organs inside the body. As one non-limiting example, the constructed model can be applied to analyze esophageal transport using fluoroscopy image sequences to predict flow rate, pressure, esophagus wall stiffness, and active relaxation.

Abstract: Systems, methods, and apparatus for esophageal panometry are provided. An example method includes capturing measurement data including an area and a pressure of an esophageal body via a measurement device positioned with respect to the esophageal body; generating representations of the exported measurement data; analyzing the measurement data to determine esophageal reactivity based on the area and pressure; assessing esophageal function based on the determined esophageal reactivity; and outputting an indication of esophageal function.

Abstract: Systems, methods, and apparatus for esophageal panometry are provided. An example method includes capturing measurement data including an area and a pressure of an esophageal body via a measurement device positioned with respect to the esophageal body; generating representations of the exported measurement data; analyzing the measurement data to determine esophageal reactivity based on the area and pressure; assessing esophageal function based on the determined esophageal reactivity; and outputting an indication of esophageal function.