Using deep learning to predict outcomes for liver cancer patients
A Deep Learning Model Based on Contrast-enhanced Ultrasound to Aid Clinical Decisions and Predict Biological Biomarker and Prognosis of Hepatocellular Carcinoma
This study is testing a new computer program that uses ultrasound images to help doctors predict how well liver cancer patients will do and decide on the best treatment options.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 1 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Chinese PLA General Hospital Academic / other |
| Locations | 1 site (Beijing, Beijing) |
| Trial ID | NCT05257694 on ClinicalTrials.gov |
What this trial studies
This study aims to develop a deep learning model that utilizes contrast-enhanced ultrasound (CEUS) data to predict the prognosis of patients with hepatocellular carcinoma (HCC). By collecting retrospective CEUS and clinical data from various institutions, the study seeks to enhance decision-making regarding surgical options, such as resection or ablation. The model will be validated using prospective data to ensure its accuracy and reliability in clinical settings.
Who should consider this trial
Good fit: Ideal candidates include patients with HCC at stages Ia, Ib, or IIa who are eligible for surgical resection or ablation and meet specific clinical criteria.
Not a fit: Patients with co-morbid malignancies or those who have poor-quality imaging may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly improve treatment decisions and outcomes for patients with hepatocellular carcinoma.
How similar studies have performed: While the use of deep learning in medical imaging is gaining traction, this specific application in predicting HCC prognosis using CEUS is relatively novel and has not been extensively tested.
Eligibility criteria
Show full inclusion / exclusion criteria
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
Where this trial is running
Beijing, Beijing
- Chinese PLA General Hospital — Beijing, Beijing, China (Recruiting)
Study contacts
- Study coordinator: Ping Liang, Dr.
- Email: liangping301@hotmail.com
- Phone: +86 10 66939530
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.