"LiverColor": AN ALGORITHM QUANTIFICATION OF LIVER GRAFT STEATOSIS USING MACHINE LEARNING AND COLOR IMAGE PROCESSING
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 246
- 试验地点
- 1
- 主要终点
- The main goal of this project is to create a machine learning model in order to quantify liver steatosis in liver donor faster, more objective and reliable than histological analysis and surgeons point-of-view.
研究概览
简要总结
The main goal of this project is to create a machine learning model in order to quantify liver steatosis in liver donor faster, more objective and reliable than histological analysis and surgeons point-of-view.
详细描述
Surgeons (junior and senior operators) from the HBP & Transplantation Unit took the pictures. They were taken after the laparotomy and before any type of surgical procedure. For each deceased donor case, a total of 5 pictures were taken: one for the left lobe and another for the right one before undergoing a surgical biopsy, two more (one for the left and one for the right lobe) after the histological analysis, near to the site of the surgical biopsy, and finally, one picture after liver perfusion.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Livers from donor donor brain death with informed consent before inclusion in the study was obtained from all participants or families.
排除标准
- •Age < 18 years old
- •Donor after cardiac death
- •Cholestasis due to a biliary obstruction
- •Total bilirubin levels above 2,5 mg/dL
- •Glutamic oxaloacetic transaminase (SGOT)/ serum glutamatepyruvate transaminase (SGPT) levels and gamma-glutamyl transaminase (GGT) levels above 400 U/L
- •Cirrhotic livers
结局指标
主要结局
The main goal of this project is to create a machine learning model in order to quantify liver steatosis in liver donor faster, more objective and reliable than histological analysis and surgeons point-of-view.
时间窗: 4 weeks
Accuracy
次要结局
- To build an image dataset to evaluate postransplant liver function.(1 week)
研究者
Concepción Gomez Gavara
PhD
Hospital Vall d'Hebron