Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model.
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 reduction in size (Group 2, n = 24). From discriminant analysis in 103 patients with full clinical variables, the prognosis of patients in terms of liver recovery was successfully predicted in 85-90% of patients. We further validated the accuracy of our model prediction using a validation cohort (prediction = 84-87%, n = 39). Our interdisciplinary approach provides qualitative and quantitative insights into the dynamics of liver regeneration. A key strength is to provide better prediction in patients who had been judged as acceptable for resection by current pragmatic criteria.
Departments of General and Gastroenterological Surgery, Osaka Medical College Hospital, Osaka, Japan.|Mathematical Biology Laboratory, Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.
Kimiyo N
KN
Yamamoto
Departments of General and Gastroenterological Surgery, Osaka Medical College Hospital, Osaka, Japan.
Masatsugu
M
Ishii
Departments of General and Gastroenterological Surgery, Osaka Medical College Hospital, Osaka, Japan.
Yoshihiro
Y
Inoue
Departments of General and Gastroenterological Surgery, Osaka Medical College Hospital, Osaka, Japan.
Fumitoshi
F
Hirokawa
Mathematical Sciences, University of Southampton, SO17 1BJ, UK.|Human Development and Health, Faculty of Medicine, University of Southampton, SO17 1BJ, UK.
Ben D
BD
MacArthur
Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA.
Akira
A
Nakamura
Mathematical Biology Laboratory, Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.
Hiroshi
H
Haeno
Departments of General and Gastroenterological Surgery, Osaka Medical College Hospital, Osaka, Japan.
Kazuhisa
K
Uchiyama
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008115:Liver Regeneration; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011184:Postoperative Period
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