Actively Recruiting
Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
Led by Yunnan Cancer Hospital · Updated on 2024-12-16
120
Participants Needed
1
Research Sites
53 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
Who Can Participate
Eligibility Criteria
You may qualify if you...
- CT/B ultrasound showed no fatty liver
- No MRI contraindications, including pacemaker, stent, metal implant, or claustrophobia
- Received neoadjuvant/adjuvant chemotherapy
You will not qualify if you...
- Missing follow-up information
- Liver lesions (metastases, hemangioma, etc.)
- Poor image quality
AI-Screening
AI-Powered Screening
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Trial Site Locations
Total: 1 location
1
Yunnan Cancer Hospital
Kunming, Yunnan, China, 650118
Actively Recruiting
Research Team
L
Lizhu Liu, Graduate
CONTACT
Z
Zhenhui Li, MD
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
DOUBLE
Allocation
RANDOMIZED
Model
SINGLE_GROUP
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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