Hepatocellular CarcinomaNCT05257694
Clinical Decision Biological Biomarker and Prognosis Prediction of Hepatocellular Carcinoma by Deep Learning
An observational study of Hepatocellular Carcinoma and Contrast-enhanced Ultrasound, run by Ping Liang at 1 site in China.
Trial summary
Developing a deep learning model based on contrast-enhanced ultrasound (CEUS) to predict the prognosis of hepatocellular carcinoma (HCC) and aid choose operation decisions Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Hepatocellular Carcinoma, Contrast-enhanced Ultrasound, Prognosis
- What is being tested?
- Surgery and Ablation (Microwave ablation or Radiofrequency ablation)
- Type of treatment
- Surgery or procedure
- How many people
- 1 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2022to 31 Dec 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: patients with HCC corresponding to Ia, Ib, IIa stage (China liver cancer staging) who undergo resection or ablation.
Who may be able to join
- 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)
Who cannot join
- postop follow-up loss or expired less than 3 months
- patients with co-malignancy
- poor images quality for analyzing
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Chinese PLA General Hospital
Beijing, Beijing Municipality, 100853
Ping Liang, Doctor
About this study
Official title: A Deep Learning Model Based on Contrast-enhanced Ultrasound to Aid Clinical Decisions and Predict Biological Biomarker and Prognosis of Hepatocellular Carcinoma
Developing a deep learning model based on contrast-enhanced ultrasound (CEUS) to predict the prognosis of hepatocellular carcinoma (HCC) and aid choose operation decisions
Read the detailed 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.
- Being tested
- Surgery, Ablation (Microwave ablation or Radiofrequency ablation)
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
SurgeryProcedure or surgery
hepatectomy
Ablation (Microwave ablation or Radiofrequency ablation)Procedure or surgery
image-guided ablation
What is being measured
The primary outcome is the main question the study is designed to answer.
Recurrence-free survival (RFS)
Recurrence-free survival is defined as the time elapsed between a predefined point in time (the date of diagnosis, randomization or the intervention) and any recurrence (local, regional, or distant) or death due to any cause (death is an event).
Measured: Immediately after the surgery or ablation
Secondary outcomes (1)
Recurrence
Recurrence included local tumor progression, regional recurrence, or distant recurrence.
Measured: Immediately after the surgery or ablation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Feb 2022
- Study start1 Jan 2022
- Primary completion31 Dec 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hepatocellular CarcinomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ping Liang
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Ping Liang, Chinese PLA General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05257694
- Sponsor's protocol ID
- S2022-002
- Status last verified
- Oct 2022
- First submitted
- 13 Feb 2022
- Last updated
- 21 Oct 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Oct 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Deep Learning Model Based on Contrast-enhanced Ultrasound to Aid Clinical Decisions and Predict Biological Biomarker and Prognosis of Hepatocellular Carcinoma
- ClinicalTrials.gov ID
- NCT05257694
- Acronym / sponsor ID
- S2022-002
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1 participants (estimated)
- Lead sponsor
- Ping LiangUniversity, hospital or other
- Study start
- 1 Jan 2022 (actual)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 25 Feb 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Developing a deep learning model based on contrast-enhanced ultrasound (CEUS) to predict the prognosis of hepatocellular carcinoma (HCC) and aid choose operation decisions
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- patients with HCC corresponding to Ia, Ib, IIa stage (China liver cancer staging) who undergo resection or ablation.
Key inclusion criteria (7 listed)
- 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
Key exclusion criteria (3 listed)
- postop follow-up loss or expired less than 3 months
- patients with co-malignancy
- poor images quality for analyzing
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Surgeryhepatectomy | Procedure or surgery | – |
| Ablation (Microwave ablation or Radiofrequency ablation)image-guided ablation | Procedure or surgery | – |
Primary outcome
Recurrence-free survival (RFS)
Time frame: Immediately after the surgery or ablation
Recurrence-free survival is defined as the time elapsed between a predefined point in time (the date of diagnosis, randomization or the intervention) and any recurrence (local, regional, or distant) or death due to any cause (death is an event).
1 secondary outcome
Recurrence
Time frame: Immediately after the surgery or ablation
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Oct 2022.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hepatocellular Carcinoma and Contrast-enhanced Ultrasound, run by Ping Liang at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Oct 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Ping Liang, Dr. (+86 10 66939530, liangping301@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Recurrence-free survival (RFS) (time frame: Immediately after the surgery or ablation). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Oct 2022; AzTrials last refreshed its copy on 8 Nov 2026.