Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model.

ABSTRACT: Although the capacity of the liver to recover its size after resection has enabled extensive liver resection, post-hepatectomy liver failure remains one of the most lethal complications of liver resection. Therefore, it is clinically important to discover reliable predictive factors after resection. In this study, we established a novel mathematical framework which described post-hepatectomy liver regeneration in each patient by incorporating quantitative clinical data. Using the model fitting to the liver volumes in series of computed tomography of 123 patients, we estimated liver regeneration rates. From the estimation, we found patients were divided into two groups: i) patients restored the liver to its original size (Group 1, n = 99); and ii) patients experienced a significant reductio

SUBMITTER: Yamamoto KN 

PROVIDER: S-EPMC5046126 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature