Actively Recruiting

Phase Not Applicable
Age: 18Years - 80Years
All Genders
Healthy Volunteers
NCT06735118

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

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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

Age: 18Years - 80Years
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

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
Not Eligible

You will not qualify if you...

  • Missing follow-up information
  • Liver lesions (metastases, hemangioma, etc.)
  • Poor image quality

AI-Screening

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Trial Site Locations

Total: 1 location

1

Yunnan Cancer Hospital

Kunming, Yunnan, China, 650118

Actively Recruiting

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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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