NCT06616103尚未招募不适用
Utility of Quantitative Imaging Parameters from Deep Learning-based CT Segmentation in Assessing Hepatic Steatosis and Fibrosis in Chronic Hepatitis B: a Prospective Study Using MRI As the Reference Standard
适应症
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 111
- 试验地点
- 1
- 主要终点
- diagnostic performance of CT attenuatio parameters in assessing hepatic steatosis and fibrosis
研究概览
简要总结
This study aims to evaluate diagnostic performance of CT attenuation parameters acquired using deep learning algorithm in assessing hepatic steatosis and fibrosis.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •chronic hepatitis B
- •no chronic liver disease other than chronic hepatitis B
- •Body mass index >= 23
排除标准
- •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
结局指标
主要结局
diagnostic performance of CT attenuatio parameters in assessing hepatic steatosis and fibrosis
时间窗: 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
次要结局
- Consistency between MRI-derived body composition data and CT-derived data(At the time of enrollment)
研究者
Jeongin Yoo
Clinical assistant professor
Seoul National University Hospital
研究点 (1)
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