"LiverColor": Machine Learning in Liver Photographs

  • STATUS
    Recruiting
  • End date
    Dec 31, 2023
  • participants needed
    246
  • sponsor
    Hospital Vall d'Hebron
Updated on 23 March 2022

Summary

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.

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.

Details
Condition Brain Death, Liver Steatosis
Treatment Liver from deceased donors
Clinical Study IdentifierNCT05202886
SponsorHospital Vall d'Hebron
Last Modified on23 March 2022

Eligibility

Yes No Not Sure

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
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