Prediction of liver remnant regeneration after living donor liver transplantation using preoperative CT texture analysis

Abstract

Purpose

To predict the rate of liver regeneration after living donor liver transplantation (LDLT) using pre-operative computed tomography (CT) texture analysis.

Materials and methods

112 living donors who performed right hepatectomy for LDLT were included retrospectively. We measured the volume of future remnant liver (FLR) on pre-operative CT and the volume of remnant liver (LR) on follow-up CT, taken at a median of 123 days after transplantation. The regeneration index (RI) was calculated using the following equation: \( [(V_{\text{LR}} - V_{\text{FLR}} )/V_{\text{FLR}} ]\, \times \,100 \) . Computerized texture analysis of the semi-automatically segmented FLR was performed. We used a stepwise, multivariable linear regression to assess associations of clinical features and texture parameters in relation to RI and to make the best-fit predictive model.

Results

The mean RI was 110.7 ± 37.8%, highly variable ranging from 22.4% to 247.0%. Among texture parameters, volume of FLR, standard deviation, variance, and gray level co-occurrence matrices (GLCM) contrast were found to have significant correlations between RI. In multivariable analysis, smaller volume of FLR (ß − 0.17, 95% CI − 0.22 to − 0.13) and lower GLCM contrast (ß − 1.87, 95% CI − 3.64 to − 0.10) were associated with higher RI. The regression equation predicting RI was following: RI = 203.82 + 10.42 × pre-operative serum total bilirubin (mg/dL) − 0.17 × V_FLR (cm³) − 1.87 × GLCM contrast (× 100).

Conclusion

Volume of FLR and GLCM contrast were independent predictors of RI, showing significant negative correlations. Pre-operative CT with texture analysis can be useful for predicting the rate of liver regeneration in living donor of liver transplantation.

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