"LiverColor": Machine Learning in Liver Photographs

Not Applicable

• Conditions: Liver Steatosis; Brain Death
• Interventions: Diagnostic Test: Liver from deceased donors

• Registration Number: NCT05202886
• Lead Sponsor: Hospital Vall d'Hebron

Brief 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.

Detailed 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.

Study Timeline

• Study Start: 2018-06-30
• Study First Submitted: 2021-06-08
• Status Verified: 2022-01
• Study First Submitted QC: 2022-01-20
• Last Update Submitted: 2022-01-20
• Study First Posted: 2022-01-24
• Last Update Posted: 2022-01-24
• Primary Completion: 2023-12-31
• Study Completion: 2023-12-31

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 246

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

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Liver from deceased donors	Liver from deceased donors	This study included all consecutive subjects with chronic liver disease who underwent LT for the first time with a deceased donor liver

Primary Outcome Measures

Name	Time	Method
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.	4 weeks	Accuracy

Secondary Outcome Measures

Name	Time	Method
To build an image dataset to evaluate postransplant liver function.	1 week	PDF will be evaluated according to Olthoff criteria

Trial Locations

Locations (1)

Concepción Gómez-Gavara; 🇪🇸 Barcelona, Spain