Liver CirrhosisNCT07056270
Development of a Set of Auxiliary Decision-making System for the Perioperative Period of Hepatectomy Based on Static CT and Artificial Intelligence.
An observational study of Liver Cirrhosis and Liver Cancer, run by Tongji Hospital.
Trial summary
The study will prospectively recruit patients with chronic liver disease and liver cancer for static CT scans to establish a high-definition CT database. Combining clinical data and pathological information, artificial intelligence technology will be utilized to construct models for assessing liver function and liver… Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Liver Cirrhosis, Liver Cancer
- What is being tested?
- static CT scans
- How many people
- 500 participants
- Where
- No sites listed yet
- Study dates
- Aug 2025to Feb 2028
- How long will I take part?
- 3 Months
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients who are clinically diagnosed with primary liver cancer and other space-occupying liver lesions preoperatively and are planned for surgical resection, or those with underlying liver diseases and cirrhosis
Who may be able to join
- Patients who are clinically diagnosed with primary liver cancer and other space-occupying liver lesions preoperatively and are planned for surgical resection, or those with underlying liver diseases and cirrhosis;
- Aged 18-75 years;
- Willing to participate in this study and have signed the informed consent.
Who cannot join
- Planned or unplanned pregnancy and pregnant women;
- Glomerular filtration rate (GFR) ≤60 ml/min;
- History of contrast media allergy.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
The study will prospectively recruit patients with chronic liver disease and liver cancer for static CT scans to establish a high-definition CT database. Combining clinical data and pathological information, artificial intelligence technology will be utilized to construct models for assessing liver function and liver cirrhosis, as well as predicting microvascular invasion (MVI).
Read the detailed description
Liver cancer is a common disease that seriously endangers public health in China, and CT technology is particularly critical in the diagnosis and treatment of liver cancer. Most patients with liver cancer in China are complicated with liver cirrhosis, and the treatment principle is a comprehensive model based on surgical resection. The main problem in the perioperative period of hepatectomy is to accurately evaluate the grade of cirrhosis, liver reserve function and predict microvascular invasion (MVI) before operation. In view of these problems, this project plans to develop a set of auxiliary decision-making system for the perioperative period of hepatectomy of liver cancer based on static CT and artificial intelligence technology and combined with expert consensus. The system will first establish a set of high-quality liver health/disease image database based on static CT (slice thickness 0.165mm, 2048×2048 scanning/reconstruction matrix, multi-energy spectrum), providing high-quality data source for clinical application development; Then, use artificial intelligence technology to optimize the output high-quality data, data mining and learning, and carry out targeted analysis from the aspects of liver cirrhosis grading, liver reserve function and MVI evaluation; Finally, on the basis of evidence-based medicine and expert consensus, intelligently fuse the multimodal biomedical information to form a set of auxiliary decision-making system for the perioperative period of hepatectomy for liver cancer, which provides a new method for further standardizing the diagnosis and treatment behavior of liver cancer and improving the surgical treatment effect of liver cancer.
- Conditions
- Liver Cirrhosis, Liver Cancer
- Being tested
- static CT scans
- Keywords
- liver cancer, liver cirrhosis, liver resection, microvascular invasion, liver function, static CT
- Medical subject headings
- Liver Cirrhosis, Liver Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
static CT scansOther
Patients with chronic liver disease and liver cancer received static CT scans before hepatectomy to establish a high-definition CT database.
| Study group | Role | What they receive |
|---|---|---|
| Static CT group | Patients with chronic liver disease and liver cancer receive static CT scans Receives: Other: static CT scans |
What is being measured
The primary outcome is the main question the study is designed to answer.
microvascular invasion
microvascular invasion based on pathology
Measured: 7 days after surgery
liver cirhosis
liver cirhosis according to laennec grading system
Measured: 7 days after surgery
liver function
liver funcion based Child-Pugh grading system
Measured: 1 day before static CT scanning
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jul 2025
- Study startAug 2025 (estimated)
- Primary completionAug 2027 (estimated)
- Study completionFeb 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Liver CirrhosisStudies of the same condition, open and under way.
- More trials run by Tongji HospitalThe 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
- Prospective
- Enrolment
- 500 participants (estimated)
- Target duration
- 3 Months
Sponsor and investigators
- Lead sponsor
- Tongji Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Suzhou Institute of Biomedical Engineering and Technology of the Chinese Academy of Sciences
- Responsible party
- Principal investigator, Chen Xiaoping, Tongji Hospital
- Investigators
- Xiaoping Chen, M.D., Study director, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07056270
- Sponsor's protocol ID
- CTLIVERai
- Status last verified
- Jun 2025
- First submitted
- 29 Jun 2025
- Last updated
- 9 Jul 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not to be shared to protect patient privacy.
Study at a glance
From the registry record, last updated by the sponsor on 9 Jul 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Set of Auxiliary Decision-making System for the Perioperative Period of Hepatectomy Based on Static CT and Artificial Intelligence.
- ClinicalTrials.gov ID
- NCT07056270
- Acronym / sponsor ID
- CTLIVERai
- Conditions
- Liver Cirrhosis, Liver Cancer
- Keywords
- liver cancer, liver cirrhosis, liver resection, microvascular invasion, liver function, static CT
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- Collaborators
- Suzhou Institute of Biomedical Engineering and Technology of the Chinese Academy of Sciences
- Study start
- Aug 2025 (estimated)
- Primary completion
- Aug 2027 (estimated)
- Study completion
- Feb 2028 (estimated)
- First posted
- 9 Jul 2025 (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.
The study will prospectively recruit patients with chronic liver disease and liver cancer for static CT scans to establish a high-definition CT database. Combining clinical data and pathological information, artificial intelligence technology will be utilized to construct models for assessing liver function and liver cirrhosis, as well as predicting microvascular invasion (MVI).
Detailed description
Liver cancer is a common disease that seriously endangers public health in China, and CT technology is particularly critical in the diagnosis and treatment of liver cancer. Most patients with liver cancer in China are complicated with liver cirrhosis, and the treatment principle is a comprehensive model based on surgical resection. The main problem in the perioperative period of hepatectomy is to accurately evaluate the grade of cirrhosis, liver reserve function and predict microvascular invasion (MVI) before operation. In view of these problems, this project plans to develop a set of auxiliary decision-making system for the perioperative period of hepatectomy of liver cancer based on static CT and artificial intelligence technology and combined with expert consensus. The system will first establish a set of high-quality liver health/disease image database based on static CT (slice thickness 0.165mm, 2048×2048 scanning/reconstruction matrix, multi-energy spectrum), providing high-quality data source for clinical application development; Then, use artificial intelligence technology to optimize the output high-quality data, data mining and learning, and carry out targeted analysis from the aspects of liver cirrhosis grading, liver reserve function and MVI evaluation; Finally, on the basis of evidence-based medicine and expert consensus, intelligently fuse the multimodal biomedical information to form a set of auxiliary decision-making system for the perioperative period of hepatectomy for liver cancer, which provides a new method for further standardizing the diagnosis and treatment behavior of liver cancer and improving the surgical treatment effect of liver cancer.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Static CT group | – | Other: static CT scansPatients with chronic liver disease and liver cancer receive static CT scans |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who are clinically diagnosed with primary liver cancer and other space-occupying liver lesions preoperatively and are planned for surgical resection, or those with underlying liver diseases and cirrhosis
Key inclusion criteria (3 listed)
- Patients who are clinically diagnosed with primary liver cancer and other space-occupying liver lesions preoperatively and are planned for surgical resection, or those with underlying liver diseases and cirrhosis;
- Aged 18-75 years;
- Willing to participate in this study and have signed the informed consent.
Key exclusion criteria (3 listed)
- Planned or unplanned pregnancy and pregnant women;
- Glomerular filtration rate (GFR) ≤60 ml/min;
- History of contrast media allergy.
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 |
|---|---|---|
| static CT scansPatients with chronic liver disease and liver cancer received static CT scans before hepatectomy to establish a high-definition CT database. | Other | Static CT group |
Primary outcome
microvascular invasion
Time frame: 7 days after surgery
microvascular invasion based on pathology
liver cirhosis
Time frame: 7 days after surgery
liver cirhosis according to laennec grading system
liver function
Time frame: 1 day before static CT scanning
liver funcion based Child-Pugh grading system
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Jul 2025.
- Individual participant dataSharing planned: No. Individual participant data will not to be shared to protect patient privacy.
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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.
Xiaoping Chen, M.D. study director
Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Questions about this trial
What is this clinical trial studying?
An observational study of Liver Cirrhosis and Liver Cancer, run by Tongji Hospital.
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 3 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: opening soon, as of the sponsor's last update on 9 Jul 2025. Status can change between updates, so confirm with the study contact before making plans.
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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hongwei Cheng, M.D. (+8613871459541, chengqi@hust.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
microvascular invasion (time frame: 7 days after surgery). The study lists 3 primary outcomes in all. 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 9 Jul 2025.