"LiverColor": Machine Learning in Liver Photographs

Catalan Institute of Health

Status

Unknown

Conditions

Brain Death

Liver Steatosis

Treatments

Diagnostic Test: Liver from deceased donors

Study type

Interventional

Funder types

Other

Identifiers

NCT05202886

PR(AG)04/2018

Details and patient eligibility

About

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.

Full description

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.

Enrollment

246 estimated patients

Sex

All

Volunteers

No Healthy Volunteers

Inclusion criteria

Livers from donor donor brain death with informed consent before inclusion in the study was obtained from all participants or families.

Exclusion criteria

Age < 18 years old
Donor after cardiac death
Split
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