Multivariable linear model for predicting graft weight based on 3-dimensional volumetry in regards to body weight change of living liver donor: an observational cohort study.

Abstract

Purpose: The purpose of this study is to build a prediction model for estimating graft weight about different graft volumetry methods combined with other variables.

Methods: Donors who underwent living-donor right hepatectomy from March 2021 to March 2023 were included. Estimated graft volume measured by conventional method and 3-dimensional (3D) software were collected as well as the actual graft weight. Linear regression was used to build a prediction model. Donor groups were divided according to the 3D volumetry of <700 cm³, 700-899 cm³, and ≥900 cm³ to compare the performance of different models.

Results: A total of 119 donors were included. Conventional volumetry showed R² of 0.656 (P < 0.001) while 3D software showed R² of 0.776 (P < 0.001). The R² of the multivariable model was 0.842 (P < 0.001) including for 3D volume (β = 0.623, P < 0.001), body mass index (β = 7.648, P < 0.001), and amount of weight loss (β = -7.252, P < 0.001). The median errors between different models and actual graft weight did not differ in donor groups (<700 and 700-899 cm³), while the median error of univariable linear model using 3D software (122.5; interquartile range [IQR], 61.5-179.8) was significantly higher than multivariable-adjusted linear model (41.5; IQR, 24.8-69.8; P = 0.003) in donors with estimated graft weight ≥900 cm³.

Conclusion: The univariable 3D volumetry model showed an acceptable outcome for donors with an estimated graft volume <900 cm³. For donors with an estimated graft volume ≥900 cm³, the multivariable-adjusted linear model showed higher accuracy.