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Application of artificial intelligence algorithm based on CT imaging for muscle parameter measurement in the diagnosis of sarcopenia

Application of artificial intelligence algorithm based on CT imaging for muscle parameter measurement in the diagnosis of sarcopenia

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500103485
Enrollment
Unknown
Registered
2025-05-29
Start date
2023-09-05
Completion date
Unknown
Last updated
2025-06-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Sarcopenia

Interventions

Observation group:None

Sponsors

Shanghai Jiaotong University School of Medicine, Renji Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
45 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1) The population undergoing BIA and abdominal CT examinations; 2) Can cooperate to complete human body composition analysis, grip strength measurement, 6m walking time measurement, and questionnaire survey. Artificial intelligence model for automated diagnosis of sarcopenia using imaging technology

Exclusion criteria

Exclusion criteria: 1) Age<45 years old; 2) Existence of abdominal wall edema; 3) History of spinal surgery or vertebral fractures, or vertebral tumor lesions; 4) History of neuromuscular disorders.

Design outcomes

Primary

MeasureTime frame
Skeletal muscle content;Visceral fat content;Subcutaneous fat content;—

Secondary

MeasureTime frame
Handgrip strength;Five-time sitting-up time;Fasting blood glucose;Triglycerides (TG);Total cholesterol (TC);Low density lipoprotein cholesterol (LDL-C);Creatine kinase;Liver function;Renal function;Complete blood count (CBC);—

Countries

China

Contacts

Public ContactYaomin Hu

Shanghai Jiaotong University School of Medicine, Renji Hospital

amin99@163.com+86 136 5161 7002

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026