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

P

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

Trial contacts and locations

1

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Central trial contact

Ping Liang, Dr.; jiapeng wu, Dr.

Data sourced from clinicaltrials.gov

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