Hepatocellular Carcinoma (HCC)NCT06637059
Artificially Intelligent Model for Accurate Detection of HCC
An observational study of Hepatocellular Carcinoma (HCC), run by Zhejiang University at 1 site in China.
Trial summary
Purpose: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. The investigators aimed to develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Hepatocellular Carcinoma (HCC)
- What is being tested?
- observational study
- How many people
- 1,092 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2024to 1 Oct 2024
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis were considered in this study. Participants who had undergone previous treatment for HCC or benign liver diseases, those who had taken medications affecting the hematological system within 2 weeks, or those who had received a blood transfusion within 6 months were excluded from the study.
Who may be able to join
- Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis
Who cannot join
- Participants who had undergone previous treatment for HCC or benign liver diseases,
- had taken medications affecting the hematological system within 2 weeks
- those who had received a blood transfusion within 6 months
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Construction of an Artificially Intelligent Model for Accurate Detection of HCC by Integrating Clinical, Radiological, and Peripheral Immunological Features
Purpose: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. The investigators aimed to develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection.
Experimental Design: A total of 1,092 participants were enrolled from 16 centers. These participants were allocated into the training, internal validation, and external validation cohorts. Peripheral blood specimens were collected prospectively and subjected to mass cytometry analysis. Clinical and radiological data were obtained from electrical medical records. Various AI methods were employed to identify pertinent features and construct single-modal models with optimal performance. The XGBoost algorithm was utilized to amalgamate these models, integrating multi-modal information and facilitating the development of a fusion model. Model evaluation and interpretability were demonstrated using the SHapley Additive exPlanations method.
- Conditions
- Hepatocellular Carcinoma (HCC)
- Being tested
- observational study
- Keywords
- Hepatocellular carcinoma; Early detection; Multi-modal; Fusion model; Artificial intelligence
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
observational studyOther
observation alone
| Study group | Role | What they receive |
|---|---|---|
| Training cohort | Not described Receives: Other: observational study | |
| Internal validation cohort | Not described Receives: Other: observational study | |
| External validation cohort | Not described Receives: Other: observational study |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnosis of liver disease through CT imaging
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Oct 2024
- Study start1 Jan 2024
- Primary completion1 Oct 2024
- Study completion1 Oct 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hepatocellular Carcinoma (HCC)Studies of the same condition, open and under way.
- More trials run by Zhejiang UniversityThe sponsor's other registered studies.
- 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
- Retrospective
- Enrolment
- 1,092 participants (actual)
Sponsor and investigators
- Lead sponsor
- Zhejiang University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, TingBo Liang, Zhejiang University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06637059
- Sponsor's protocol ID
- MMFAIHCC
- Status last verified
- Oct 2024
- First submitted
- 5 Oct 2024
- Last updated
- 15 Oct 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Construction of an Artificially Intelligent Model for Accurate Detection of HCC by Integrating Clinical, Radiological, and Peripheral Immunological Features
- ClinicalTrials.gov ID
- NCT06637059
- Acronym / sponsor ID
- MMFAIHCC
- Conditions
- Hepatocellular Carcinoma (HCC)
- Keywords
- Hepatocellular carcinoma; Early detection; Multi-modal; Fusion model; Artificial intelligence
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,092 participants (actual)
- Lead sponsor
- Zhejiang UniversityUniversity, hospital or other
- Study start
- 1 Jan 2024 (actual)
- Primary completion
- 1 Oct 2024 (actual)
- Study completion
- 1 Oct 2024 (actual)
- First posted
- 15 Oct 2024 (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.
Purpose: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. The investigators aimed to develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection.
Experimental Design: A total of 1,092 participants were enrolled from 16 centers. These participants were allocated into the training, internal validation, and external validation cohorts. Peripheral blood specimens were collected prospectively and subjected to mass cytometry analysis. Clinical and radiological data were obtained from electrical medical records. Various AI methods were employed to identify pertinent features and construct single-modal models with optimal performance. The XGBoost algorithm was utilized to amalgamate these models, integrating multi-modal information and facilitating the development of a fusion model. Model evaluation and interpretability were demonstrated using the SHapley Additive exPlanations method.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Training cohort | – | Other: observational study |
| Internal validation cohort | – | Other: observational study |
| External validation cohort | – | Other: observational study |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis were considered in this study. Participants who had undergone previous treatment for HCC or benign liver diseases, those who had taken medications affecting the hematological system within 2 weeks, or those who had received a blood transfusion within 6 months were excluded from the study.
Key inclusion criteria (1 listed)
- Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis
Key exclusion criteria (3 listed)
- Participants who had undergone previous treatment for HCC or benign liver diseases,
- had taken medications affecting the hematological system within 2 weeks
- those who had received a blood transfusion within 6 months
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 |
|---|---|---|
| observational studyobservation alone | Other | External validation cohort, Internal validation cohort, Training cohort |
Primary outcome
Diagnosis of liver disease through CT imaging
Time frame: 1 month
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2024.
- Individual participant dataSharing planned: No
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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.
The record lists no contact. Use the official record to reach the sponsor.
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 (HCC), run by Zhejiang University 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 1 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: finished, as of the sponsor's last update on 15 Oct 2024. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnosis of liver disease through CT imaging (time frame: 1 month). 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 15 Oct 2024.