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