Viewing Study NCT06735118


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Study NCT ID: NCT06735118
Status: RECRUITING
Last Update Posted: 2024-12-16
First Post: 2024-11-27
Is NOT Gene Therapy: False
Has Adverse Events: False

Brief Title: Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
Sponsor: Yunnan Cancer Hospital
Organization:

Study Overview

Official Title: Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
Status: RECRUITING
Status Verified Date: 2024-12
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
Brief Summary: 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.

Study Oversight

Has Oversight DMC: False
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: False
Is an FDA AA801 Violation?: