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

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.

Inclusion criteria

• 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.

Exclusion criteria

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