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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

1080 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-09-05

Study Completion Date

2024-12-31

Brief Summary

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

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Detailed Description

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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

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Deep Learning Sarcopenia Computed Tomography Body Composition

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

CROSS_SECTIONAL

Eligibility Criteria

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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.

Exclusion Criteria

1. Age\<18 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.

Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes