Microvascular Invasion Artificial Intelligence Prediction Via Contrast-enhanced Ultrasound With Explainability

NCT06760494 | Completed

• 4 other identifiers: MAPUSE921593058203004782325027
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 2

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.

Conditions

HCC - Hepatocellular Carcinoma; Microvascular Invasion (MVI)

Keywords

hepatocellular carcinoma; microvascular invasion; contrast-enhanced ultrasound; deep learning

Outcome Measures

Primary Outcomes (1)

• area under operating characteristic curves (AUC)

  the area under operating characteristic curves (AUC) to evaluate the performance of MAPUSE model in predicting MVI in HCC patients

  From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively)

Secondary Outcomes (3)

• ACC (accuracy)

  From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively)

• Specificity

  From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively)

• Sensitivity

  From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively)

Study Arms (2)

Chinese PLA General Hospital Cohort

Patients from Chinese PLA General Hospital (northern China) after surgical treatment

Diagnostic Test: the MAPUSE model

the First Affiliated Hospital of Sun Yat-sen University Cohort

Patients from the First Affiliated Hospital of Sun Yat-sen University (southern China) after surgical treatment

Diagnostic Test: the MAPUSE model

Interventions

the MAPUSE model DIAGNOSTIC_TEST

Using the MAPUSE model to predict MVI status before surgical resection for HCC patients

Chinese PLA General Hospital Cohort; the First Affiliated Hospital of Sun Yat-sen University Cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients who underwent surgical treatment for HCC

You may qualify if:

• Age \>18 years old.
• The HCC diagnosis and the presence of MVI were confirmed by surgical pathology.
• Complete and clear CEUS videos obtained within two weeks preoperatively.

You may not qualify if:

• Unqualified CEUS images.
• Missing surgical pathological diagnosis.
• Lesions underwent local treatments.
• Non-HCC diagnosis

Sponsors & Collaborators

• Chinese PLA General Hospital: lead
• Chinese Academy of Sciences: collaborator

Study Sites (2)

the First Affiliated Hospital of Sun Yat-sen University

Guangzhou, Guangdong, 510080, China

Location

Chinese PLA General Hospital

Beijing, 100853, China

Location

MeSH Terms

Conditions

Carcinoma, Hepatocellular

Condition Hierarchy (Ancestors)

Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Liver Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Digestive System Diseases; Liver Diseases

Study Officials

• Chuan Pang

  Chinese PLA General Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: December 28, 2024
• First Posted: January 6, 2025
• Study Start: November 1, 2023
• Primary Completion: May 30, 2024
• Study Completion: May 30, 2024
• Last Updated: January 6, 2025

Record last verified: 2025-01

Locations

CN (2)