NCT06845462

Application of Artificial Intelligence Algorithm Based on CT Imaging for Muscle Parameter Measurement

Application of Artificial Intelligence Algorithm Based on CT Imaging for Muscle Parameter Measurement in the Diagnosis of Sarcopenia

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,080 (actual)
• Sponsor: RenJi Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 90 Years
• Healthy volunteers: Accepted

Summary

To establish an artificial intelligence model for automated diagnosis of sarcopenia based on CT imaging

Detailed description

With the accelerating aging process, the early identification and diagnosis of sarcopenia, along with the effective prevention of its adverse outcomes, have become a focal point in medical research. However, current methods for assessing and diagnosing sarcopenia still face significant limitations, making the development of more efficient and accurate techniques for muscle mass evaluation an urgent clinical need. Although CT is considered as the most promising method for assessing muscle mass, its practical application is hindered by factors such as reliance on physician expertise and time-consuming procedures, limiting its widespread clinical adoption. In light of these challenges, this study aims to develop an artificial intelligence model for fully automated muscle mass measurement based on abdominal CT imaging and to validate its application value in assisting the diagnosis of sarcopenia.

Conditions

• Deep Learning
• Sarcopenia
• Computed Tomography
• Body Composition

Timeline

• Start date: 2023-09-05
• Primary completion: 2024-12-31
• Completion: 2024-12-31
• First posted: 2025-02-25
• Last updated: 2025-02-25

Locations

1 site across 1 country: China