ltra-low Dose CT imaging with a Deep Learning Algorithm in Body Composition Analysis
Not Applicable
- Conditions
- Not Applicable
- Registration Number
- KCT0007446
- Lead Sponsor
- Seoul National University Bundang Hospital
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot yet recruiting
- Sex
- All
- Target Recruitment
- 100
Inclusion Criteria
Adult male and female of age 20 to 65.
Volunteers who reviewed and signed the informed consent form.
Exclusion Criteria
Pregnant, or potentially pregnant women
Those having underlying disease
Intellectual disability hampering understanding of the procedure
Metalic prosthesis at the scan area
Study & Design
- Study Type
- Observational Study
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Intraclass correlation of body composition measurements made at the L3 vertebral body level (muscle area, visceral fat area, subcutaneous fat area), between low-dose CT image aided by artificial intelligence and full-dose CT image.
- Secondary Outcome Measures
Name Time Method Intraclass correlation of body composition measurements (muscle area, visceral fat area, subcutaneous fat area) between low-dose CT image unaided by artificial intelligence and full-dose CT image.