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Marasco et al. Hepatoma Res 2020;6:32                            Hepatoma Research
               DOI: 10.20517/2394-5079.2019.54


               Review                                                                        Open Access


               Non-invasive tests for the prediction of post-
               hepatectomy liver failure in the elderly


               Giovanni Marasco , Antonio Colecchia , Matteo Milandri , Benedetta Rossini , Luigina Vanessa Alemanni ,
                                                                                                         1
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                                                               3
                                                                                1
                               1
               Elton Dajti , Federico Ravaioli , Matteo Renzulli , Rita Golfieri , Davide Festi 1
                                                                   3
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               1 Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna 40138, Italy.
               2 Unit of Gastroenterology, Borgo Trento University Hospital of Verona, P.le Aristide Stefani 1, Verona 37126, Italy.
               3 Radiology Unit, Sant’Orsola Malpighi Hospital, Bologna 40138, Italy.
               Correspondence to: Dr. Antonio Colecchia, Unit of Gastroenterology, Borgo Trento University Hospital of Verona, P.le Aristide
               Stefani 1, Verona 37126, Italy. E-mail: antonio.colecchia@aovr.veneto.it
               How to cite this article: Marasco G, Colecchia A, Milandri M, Rossini B, Alemanni LV, Dajti E, Ravaioli F, Renzulli M, Golfieri R,
               Festi D. Non-invasive tests for the prediction of post-hepatectomy liver failure in the elderly. Hepatoma Res 2020;6:32.
               http://dx.doi.org/10.20517/2394-5079.2019.54
               Received: 30 Dec 2019    First Decision: 16 Mar 2020    Revised: 5 May 2020    Accepted: 21 May 2020    Published: 18 Jun 2020
               Science Editor: Bruno Nardo   Copy Editor: Cai-Hong Wang    Production Editor: Tian Zhang


               Abstract
               Post-hepatectomy liver failure (PHLF) is associated with great morbidity and mortality after resection of
               hepatocellular carcinoma. Previous studies have underlined that advanced age could be a potential factor
               influencing post-operative complications and long-term survival.

               In the past, candidates for resection were based on the Child-Pugh classification, the predictive value of which was
               rather low. The selection of patients undergoing resection in Western countries is based on the assessment of
               portal hypertension (PH), which is clinically assessed by measurement of the hepatic venous pressure gradient, an
               invasive and costly process. Thus, there have been several attempts to identify the best non-invasive test (NIT) to
               accurately predict PHLF. Most biochemical NITs for the prediction of PHLF are focused on evaluation of underlying
               liver cirrhosis and PH. Amongst them, FIB-4, which also includes the patient’s age, seems to have more robust
               supporting results. In Europe and the USA., the most tested and reliable NIT for predicting PHLF is the evaluation
               of liver stiffness measurement, which is also influenced by age. Imaging parameters are promising tools which
               are used only in specialized centers however, and when available. Liver volume parameters, as well as contrast-
               enhanced data, demonstrate good accuracy in predicting PHLF. In this scenario, the evaluation of sarcopenia and
               bone mineral density through contextual imaging allows the delineation of PHLF in at-risk elderly patients. Further
               studies focused on parameters for the evaluation of PHLF in elderly patients are needed.

               Keywords: Post-hepatectomy liver failure, liver resection, elderly, liver stiffness measurement, indocyanine green
               retention test



                           © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
                sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long
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