Data on hydrodynamic flow and aspiration mechanisms in a patient-specific pharyngolaryngeal model with variable epiglottis angles.

Abstract

This dataset comprises a comprehensive collection of videos and images illustrating the fluid dynamics of swallowing and aspiration in a patient-specific pharyngolaryngeal model with varying epiglottis angles. The data also includes the physical properties of the fluids used, comprising dynamic viscosity, surface tension, and contact angle. Videos under varying swallowing conditions were collected to investigate the mechanisms underlying aspiration. The study utilized a biomechanical swallowing model developed using transparent casts of an anatomically accurate pharyngolaryngeal structure. Fluorescent dye was used to visualize the liquid flow dynamics from both side and back views. The dataset includes videos for two types of liquids, water and a 1% w/v methylcellulose aqueous solution, evaluated under two dispensing speeds (fast and slow) and two dispensing locations (anterior and posterior) across four epiglottis angles (30° up-tilt, 0° horizontal, 45° down-tilt, and 80° down-tilt). Additionally, the dataset includes photos of the pharyngolaryngeal model setup, photos of the epiglottis models used, and STL files for both the pharyngolaryngeal model and the epiglottis 3D models. The videos document the distinct flow patterns and frequent aspiration sites identified during the experiments, including the interarytenoid notch, the cuneiform tubercular recess, and the vallecula. These data are valuable for researchers aiming to understand the etiology of dysphagia and can be reused to validate computational models, guide future experimental designs, and inform clinical diagnostics and treatment strategies. The dataset is organized into folders based on the epiglottis angles, dispensing speeds, and locations, as well as liquid types. This organization facilitates easy access and analysis for researchers in biomedical engineering, clinical research, and computational biology. The data provide a rich resource for further investigation into swallowing mechanics and the development of etiology-based interventions for dysphagia management.