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

ConditionNon-Alcoholic Fatty Liver Disease

Trial statusRecruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age18-80

SponsorYunnan Cancer Hospital

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

CT/B ultrasound showed no fatty liver

No MRI contraindications, including pacemaker, stent, metal implant, or claustrophobia

Received neoadjuvant/adjuvant chemotherapy

Disqualifiers

Missing follow-up information

Liver lesions (metastases, hemangioma, etc.)

Poor image quality

Trial design

Design model

Single group

Treatments tested in this trial

Neoadjuvant chemotherapy
Drug
Neoadjuvant chemotherapy

Treatment groups

120 Participants

are divided into 2 treatment groups

Group A: neoadjuvant chemotherapy groupExperimental treatment 1 intervention

Group B: Non-neoadjuvant chemotherapy groupNo intervention 0 interventions

Trial outcomes

Primary outcomes

Extract the whole liver fat fraction

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

Time frame

one year

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Yunnan Cancer Hospital

Lead sponsor

Source ClinicalTrials.gov

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