Development of a Set of Auxiliary Decision-making System for the Perioperative Period of Hepatectomy Based on Static CT and Artificial Intelligence.

Tongji Hospital

Status: Not yet enrolling

Conditions: Liver Cirrhosis; Liver Cancer

Treatments: Other: static CT scans

Study type: Observational

Funder types: Other

Identifiers

NCT07056270

CTLIVERai

Details and patient eligibility

About

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).

Full 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.

Enrollment: 500 estimated patients

Sex: All

Ages: 18 to 75 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. 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;
2. Aged 18-75 years;
3. Willing to participate in this study and have signed the informed consent.

Exclusion criteria

1. Planned or unplanned pregnancy and pregnant women;
2. Glomerular filtration rate (GFR) ≤60 ml/min;
3. History of contrast media allergy.

Trial design

500 participants in 1 patient group

Static CT group

Description:

Patients with chronic liver disease and liver cancer receive static CT scans

Treatment:

Other: static CT scans