Prediction of liver regeneration in recipients after living-donor liver transplantation in using preoperative CT texture analysis and clinical features

Purpose The aim of the study is to predict the rate of liver regeneration in recipients after living-donor liver transplantation using preoperative CT texture and shape analysis of the future graft. Methods 102 donor-recipient pairs who underwent living-donor liver transplantation using right lobe grafts were retrospectively included. We semi-automatically segmented the future graft from preoperative CT. The volume of the future graft (LVpre) was measured, and texture and shape analyses were performed. The graft liver was segmented from postoperative follow-up CT and the volume of the graft (LVpost) was measured. The regeneration index was defined by the following equation: [(LVpost-LVpre)/LVpre] x 100(%). We performed a stepwise, multivariate linear regression analysis to investigate the association between clinical, texture and shape parameters and the RI and to make the best-fit predictive model. Results The mean regeneration index was 47.5 +/- 38.6%. In univariate analysis, the volume of the future graft, energy, effective diameter, surface area, sphericity, roundness(m), compactness1, and grey-level co-occurrence matrix contrast as well as several clinical parameters were significantly associated with the regeneration index (p < 0.05). The best-fit predictive model for the regeneration index made by multivariate analysis was as follows: Regeneration index (%) = 127.020-0.367 x effective diameter - 1.827 x roundness(m) + 47.371 x recipient body surface area (m(2)) + 12.041 x log(recipient white blood cell count) (x 10(3)/mu L)+ 18.034 (if the donor was female). Conclusion The effective diameter and roundness(m) of the future graft were associated with liver regeneration. Preoperative CT texture analysis of future grafts can be useful for predicting liver regeneration in recipients after living-donor liver transplantation.