Clinical Decision Biological Biomarker and Prognosis Prediction of Hepatocellular Carcinoma by Deep Learning

Ping Liang

Status: Enrolling

Conditions: Ablation; Surgery; Contrast-enhanced Ultrasound; Hepatocellular Carcinoma; Prognosis

Treatments: Procedure: Surgery; Procedure: Ablation (Microwave ablation or Radiofrequency ablation)

Study type: Observational

Funder types: Other

Identifiers

NCT05257694

S2022-002

Details and patient eligibility

About

Developing a deep learning model based on contrast-enhanced ultrasound (CEUS) to predict the prognosis of hepatocellular carcinoma (HCC) and aid choose operation decisions

Full description

Collecting CEUS and clinical data of HCC from different institutions retrospectively.

Developing a deep learning model based on CEUS to predict the prognosis of HCC. Developing a deep learning model based on CEUS to choose a better operation (ablation or surgery) of HCC patients.

Then, validating the deep learning model in the prospective data.

Enrollment: 1 estimated patient

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• patients with HCC (Ia, Ib, IIa stage) China liver cancer staging who underwent resection or ablation
• without macro-vascular invasion
• Child-Pugh A/B grade
• HCC is proved by pathological examination or two enhanced imaging
• CEUS (Sonovue or Sonozoid) images are performed two weeks before the operation
• Invasive biomarker or prognosis of HCC available
• CEUS images are included in at least three stages (Arterial phase, Portal phase, and Late phase)

Exclusion criteria

• postop follow-up loss or expired less than 3 months
• patients with co-malignancy
• poor images quality for analyzing