Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver

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.

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Key information

Conditions

Non-Alcoholic Fatty Liver Disease Digestive System Diseases Fatty Liver Liver Diseases

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Yunnan Cancer Hospital

Kunming, Yunnan, 650118, China

Location status: Recruiting

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

CT/B ultrasound showed no fatty liver
No MRI contraindications, including pacemaker, stent, metal implant, or claustrophobia
Received neoadjuvant/adjuvant chemotherapy

Exclusion criteria

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

Treatment and study plan

Neoadjuvant chemotherapy

Drug

Neoadjuvant chemotherapy

Other names: Non

Primary outcomes

Extract the whole liver fat fraction

Time frame: one year

Extract the whole liver fat fraction using the threshold extraction method.

Interested in participating?

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Sponsors and collaborators

Lead sponsor

Yunnan Cancer Hospital

Other

Registry information

Important dates

Study start: 2023
Primary completion: 2024
Study completion: 2024
First posted: Dec 16, 2024
Registry last updated: Dec 16, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

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