Faculty Collaboration Database

Digital imaging software versus the "eyeball" method in quantifying steatosis in a liver biopsy. Liver Transpl 2023 Mar 01;29(3):268-278

Date

01/19/2023

Pubmed ID

36651194

DOI

10.1097/LVT.0000000000000064

Scopus ID

2-s2.0-85148678203 (requires institutional sign-in at Scopus site)   2 Citations

Abstract

Steatotic livers represent a potentially underutilized resource to increase the donor graft pool; however, 1 barrier to the increased utilization of such grafts is the heterogeneity in the definition and the measurement of macrovesicular steatosis (MaS). Digital imaging software (DIS) may better standardize definitions to study posttransplant outcomes. Using HALO, a DIS, we analyzed 63 liver biopsies, from 3 transplant centers, transplanted between 2016 and 2018, and compared macrovesicular steatosis percentage (%MaS) as estimated by transplant center, donor hospital, and DIS. We also quantified the relationship between DIS characteristics and posttransplant outcomes using log-linear regression for peak aspartate aminotransferase, peak alanine aminotransferase, and total bilirubin on postoperative day 7, as well as logistic regression for early allograft dysfunction. Transplant centers and donor hospitals overestimated %MaS compared with DIS, with better agreement at lower %MaS and less agreement for higher %MaS. No DIS analyzed liver biopsies were calculated to be >20% %MaS; however, 40% of liver biopsies read by transplant center pathologists were read to be >30%. Percent MaS read by HALO was positively associated with peak aspartate aminotransferase (regression coefficient= 1.04 1.08 1.12 , p <0.001), peak alanine aminotransferase (regression coefficient = 1.04 1.08 1.12 , p <0.001), and early allograft dysfunction (OR= 1.10 1.40 1.78 , p =0.006). There was no association between HALO %MaS and total bilirubin on postoperative day 7 (regression coefficient = 0.99 1.01 1.04 , p =0.3). DIS provides reproducible quantification of steatosis that could standardize MaS definitions and identify phenotypes associated with good clinical outcomes to increase the utilization of steatite livers.

Author List

Long JJ, Nijhar K, Jenkins RT, Yassine A, Motter JD, Jackson KR, Jerman S, Besharati S, Anders RA, Dunn TB, Marsh CL, Rayapati D, Lee DD, Barth RN, Woodside KJ, Philosophe B

Author

Ty Blink Dunn MD Professor in the Surgery department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Alanine Transaminase
Aspartate Aminotransferases
Bilirubin
Biopsy
Fatty Liver
Humans
Image Processing, Computer-Assisted
Liver
Liver Transplantation
Software