Chronic Hepatitis B, Steatosis of Liver, Fibrosis and Cirrhosis of Liver
Conditions
Brief summary
This study aims to evaluate diagnostic performance of CT attenuation parameters acquired using deep learning algorithm in assessing hepatic steatosis and fibrosis.
Interventions
DIAGNOSTIC_TESTcomputerized tomography
noncontrast abdominal CT
Sponsors
Seoul National University Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
19 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* chronic hepatitis B * no chronic liver disease other than chronic hepatitis B * Body mass index >= 23
Exclusion criteria
* pregnant women * unable to perform MRI examinations due to claustrophobia or metallic foreign body * suspicious hepatic malignancy on previous imaging studies * history of local treatment for hepatic lesions * history of surgery or catheter insertion of liver or spleen
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| diagnostic performance of CT attenuatio parameters in assessing hepatic steatosis and fibrosis | At the time of enrollment | diagnostic performance of CT attenuatio parameters in assessing hepatic steatosis and fibrosis using MRI-PDFF and MR elastography as reference standards |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Consistency between MRI-derived body composition data and CT-derived data | At the time of enrollment | Consistency between MRI-derived body composition data and CT-derived data using automated 3D organ segmentation algorithm |
Countries
South Korea
Outcome results
None listed