An Artificial Intelligence Assessment System for Risk Grading of Sarcopenia Based on Ultrasonographic Multidimensional Data

What this Trial Is About

Sarcopenia is an age-related condition involving loss of muscle mass and function, often occurring alongside diseases like cancer, diabetes, and chronic kidney disease, which worsen muscle decline and overall prognosis. This research aims to develop an artificial intelligence (AI) system using ultrasound images to diagnose sarcopenia and estimate patient strength, helping to identify individuals at risk early and improve quality of life for older adults. The study focuses on using ultrasound, a cost-effective and accessible imaging technique, to gather multidimensional data including muscle thickness and original image content, combined with basic information like age and body mass index. Researchers plan to create AI models for diagnosis, classification, and risk grading of sarcopenia in hospitalized and community-dwelling older adults. This approach aims to provide rapid screening for potential sarcopenia cases for further clinical management. Participants will undergo ultrasound scans to collect muscle images and measurements. Researchers will track outcomes such as death and diagnosed sarcopenia within two years after the initial ultrasound. The study involves older adults over 50 years old, including those at risk of sarcopenia based on walking or strength difficulties. Data collected will help build AI tools for early detection and risk assessment, with ongoing monitoring for up to two years.

Assessment System for Sarcopenia Based on Ultrasonographic Data