Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Neoadjuvant chemotherapy.
- Who it may be relevant to
- Registry conditions: Non-Alcoholic Fatty Liver Disease. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Detailed description
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.
Interventions
- Drug Neoadjuvant chemotherapy
Neoadjuvant chemotherapy
Primary outcome measures
- Extract the whole liver fat fraction [Time frame: one year]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Single group
- Masking
- Double blind
- Primary purpose
- Diagnostic
Study locations
China · 1 center
- Yunnan Cancer Hospital — Kunming
Identifiers
NCT: NCT06735118 · KYLX2023-165