NCT07265011已完成不适用
Prospective Validation of an AI-Driven Ultrasound-Based Method for Estimating Hepatic Steatosis Using MRI-Derived Fat Fraction as Reference in Pediatric Metabolic Dysfunction-Associated Steatotic Liver Disease
Jae Won Choi1 个研究点 分布在 1 个国家目标入组 50 人开始时间: 2024年12月31日最近更新:
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- Agreement Between AI-Predicted Ultrasound Fat Fraction (AI-USFF) and MRI Proton Density Fat Fraction (MRI-PDFF)
研究概览
简要总结
The purpose of this study is to validate an artificial intelligence (AI)-based algorithm that estimates hepatic steatosis using ultrasound (US) B-mode images in pediatric participants with metabolic dysfunction-associated steatotic liver disease (MASLD). The MRI proton density fat fraction (MRI-PDFF) serves as the reference standard for hepatic fat quantification.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 8 Years 至 18 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •participants aged 8 to 18 years clinically indicated for liver ultrasound examination to evaluate hepatic steatosis
- •participants with suspected or known metabolic dysfunction-associated steatotic liver disease (MASLD)
- •able to understand the study purpose and provide written informed consent (from both participant and legal guardian).
- •agree to undergo same-day liver MRI examination in addition to the ultrasound
排除标准
- •unable to cooperate with imaging procedures
- •parent or legal guardian unable to understand the study explanation
- •contraindications to MRI
- •determined by the investigator to be otherwise unsuitable for participation after consultation
结局指标
主要结局
Agreement Between AI-Predicted Ultrasound Fat Fraction (AI-USFF) and MRI Proton Density Fat Fraction (MRI-PDFF)
时间窗: At time of imaging (single visit)
Reference standard: MRI-PDFF (percentage) \- intraclass correlation coefficient (ICC)
次要结局
- Diagnostic Performance of AI-USFF for MRI-Based Hepatic Steatosis Grades(At time of imaging (single visit))
- Inter-Vendor Reproducibility of AI-USFF(At time of imaging (single visit))
- Correlation Between AI-USFF and MRI-PDFF(At time of imaging (single visit))
研究者
Jae Won Choi
Clinical Assistant Professor
Seoul National University Hospital
研究点 (1)
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