A Basic Study for Predicting Dysphagia in Panoramic X-ray Images Using Artificial Intelligence (AI) Part 2: Analysis of the Position of the Hyoid Bone on Panoramic Radiographs

Abstract

Background: Oral frailty is associated with systemic frailty. The vertical position of the hyoid bone is important when considering the risk of dysphagia. However, dentists usually do not focus on this position. Purpose: To create an AI model for detection of the position of the vertical hyoid bone. Methods: In this study, 1830 hyoid bone images from 915 panoramic radiographs were used for AI learning. The position of the hyoid bone was classified into six types (Types 0, 1, 2, 3, 4, and 5) based on the same criteria as in our previous study. Plan 1 learned all types. In Plan 2, the five types other than Type 0 were learned. To reduce the number of groupings, three classes were formed using combinations of two types in each class. Plan 3 was used for learning all three classes, and Plan 4 was used for learning the two classes other than Class A (Types 0 and 1). Precision, recall, f-values, accuracy, and areas under the precision–recall curves (PR-AUCs) were calculated and comparatively evaluated. Results: Plan 4 showed the highest accuracy and PR-AUC values, of 0.93 and 0.97, respectively. Conclusions: By reducing the number of classes and not learning cases in which the anatomical structure was partially invisible, the vertical hyoid bone was correctly detected.