Objective Evaluation of Biomaterial Effects after Injection Laryngoplasty- Introduction of Artificial Intelligence-Based Ultrasonic Image Analysis.

OBJECTIVE Hyaluronic acid (HA) can be degraded over time. However, persistence of the effects after injection laryngoplasty (IL) for unilateral vocal fold paralysis (UVFP), longer than expected from HA longevity, has been observed. The purpose of the study was to develop an methodology with clinical utility for objective evaluation of the temporal change in HA volume after IL using artificial intelligence (AI)-based ultrasonic assessment. DESIGN, SETTING AND PARTICIPANTS Imaging phantoms simulating injected HA were built in different volumes for designing the algorithm for machine learning. Subsequently, five adult patients who had undergone IL with HA for UVFP were recruited for clinical evaluation. MAIN OUTCOME MEASURES Estimated volumes were evaluated for injected HA by the automatic algorithm as well as voice outcomes at 2 weeks, and 2 and 6 months after IL. RESULTS On imaging phantoms, contours on each frame were described well by the algorithm and the volume could be estimated accordingly. The error rates were 0 - 9.2%. Moreover, the resultant contours of the HA area were captured in detail for all participants. The estimated volume decreased to an average of 65.76% remaining at 2 months and to a minimal amount at 6 months while glottal closure remained improved. CONCLUSION The volume change of the injected HA over time for an individual was estimated non-invasively by AI-based ultrasonic image analysis. The prolonged effect after treatment, longer than HA longevity, was demonstrated objectively for the first time. The information is beneficial to achieve optimal cost-effectiveness of IL and improve the life quality of the patients.