Advancing Sarcopenia Management Through Integrated Clinical-Research Translation and Innovation
Yaomin Hu

TL;DR
This paper presents a multidimensional approach to managing sarcopenia through clinical research, AI diagnostics, and personalized rehabilitation, aiming to improve aging outcomes.
Contribution
The paper introduces an AI diagnostic system and a collaborative framework for sarcopenia management, redefining it as a modifiable aging condition.
Findings
An AI system automates muscle quantification via CT scans, improving efficiency and analysis scope.
A rehabilitation unit using isokinetic dynamometry shows short-term improvements in physical and metabolic parameters.
A collaborative network and standardized biobank were established to support clinical and scientific advancements in sarcopenia.
Abstract
Sarcopenia is closely linked to aging, driving our comprehensive clinical and scientific efforts to address this condition through a multidimensional integration of clinical translation and technological innovation. We established a database and biobank for sarcopenia, which formed the foundation for leading the development of the 2024 Chinese Expert Consensus on the Construction of Standardized Biobank and Database for Sarcopenia. This initiative has fostered a collaborative medical consortium network for sarcopenia management. Our self-developed AI diagnostic system, Muscle and Fat Intelligent Analysis System (MFIAS), automates CT-based muscle quantification, significantly improving analytical efficiency compared to the traditional manual approach, while shifting from single-parameter to multidimensional metrics analysis. The newly constructed skeletal muscle rehabilitation unit…
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Taxonomy
TopicsNutrition and Health in Aging · Muscle Physiology and Disorders · Frailty in Older Adults
