Ignite Creation Date:
2025-12-25 @ 1:40 AM
Ignite Modification Date:
2025-12-26 @ 4:27 AM
Study NCT ID:
NCT06760494
Status:
COMPLETED
Last Update Posted:
2025-01-06
First Post:
2024-12-28
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Microvascular Invasion Artificial Intelligence Prediction Via Contrast-enhanced Ultrasound With Explainability
Sponsor:
Chinese PLA General Hospital
Organization:
Study Overview
Official Title:
Prediction of Microvascular Invasion in HCC Using Spatiotemporal Radiomics of Contrast-enhanced Ultrasound: a Deep Learning Model With Transcriptomics Correlation
Status:
COMPLETED
Status Verified Date:
2025-01
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:
MAPUSE
Brief Summary:
An artificial intelligence (AI) model to predict MVI of HCC using contrast-enhanced ultrasound was constructed. This model also has biological explainability. The investigators named it as MAPUSE (MVI AI prediction via contrast-enhanced ultrasound with explainability).
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
Detailed Description:
The presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a critical prognostic indicator, but its preoperative diagnosis remains challenging. Contrast-enhanced ultrasound (CEUS), with its dynamic microvascular imaging capability, holds promise in prediction of MVI.
The investigators constructed an artificial intelligence (AI) model to predict MVI using contrast-enhanced ultrasound. This model also has biological explainability. We named it as MAPUSE (MVI AI prediction via contrast-enhanced ultrasound with explainability).
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
The performance of MAPUSE is to be tested in two prospective testing cohorts from two centers in southern and northern China. Before surgery, patient CEUS videos will be collected and analysed by MAPUSE model to generate an MVI risk score. According to the postoperative pathological diagnosis of MVI (golden criterion), the result of MAPUSE will be evaluated. Parameters include area under curve (AUC), accuracy (ACC), sensitivity, specificity and F1-score.
The investigators constructed an artificial intelligence (AI) model to predict MVI using contrast-enhanced ultrasound. This model also has biological explainability. We named it as MAPUSE (MVI AI prediction via contrast-enhanced ultrasound with explainability).
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
The performance of MAPUSE is to be tested in two prospective testing cohorts from two centers in southern and northern China. Before surgery, patient CEUS videos will be collected and analysed by MAPUSE model to generate an MVI risk score. According to the postoperative pathological diagnosis of MVI (golden criterion), the result of MAPUSE will be evaluated. Parameters include area under curve (AUC), accuracy (ACC), sensitivity, specificity and F1-score.
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?:
None
Is an FDA AA801 Violation?: