Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 120
- 试验地点
- 1
- 主要终点
- Extract the whole liver fat fraction
研究概览
简要总结
The purpose of this study is to quantitatively assess the changes in liver fat content in cancer patients before and after treatment.
The main questions it aims to answer are:How does the liver fat fraction change before and after chemotherapy? In this study, patients undergoing mDixon Quant scanning are subjected to fully automated segmentation and measurement of liver fat content using artificial intelligence.
详细描述
Regarding the extraction of liver fat fraction, the traditional axial ROI method involves selecting several regions of interest (ROIs) at the largest cross-sectional level or across multiple continuous sections, and taking the average value as the whole-liver fat fraction. This method is complex, time-consuming, and cannot obtain the whole-liver fat fraction. In this study, a threshold extraction method is used to obtain the whole-liver fat fraction, enabling a 2D-to-3D conversion, which is more time-efficient and labor-saving, and provides a more accurate measurement.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- Double (Participant, Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •CT/B ultrasound showed no fatty liver
- •No MRI contraindications, including pacemaker, stent, metal implant, or claustrophobia
- •Received neoadjuvant/adjuvant chemotherapy
排除标准
- •Missing follow-up information
- •Liver lesions (metastases, hemangioma, etc.)
- •Poor image quality
研究组 & 干预措施
neoadjuvant chemotherapy group
Cancer patients undergoing chemotherapy.
干预措施: Neoadjuvant chemotherapy (Drug)
结局指标
主要结局
Extract the whole liver fat fraction
时间窗: one year
Extract the whole liver fat fraction using the threshold extraction method.
次要结局
未报告次要终点