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Laparoscopic management of benign liver diseases: where are we?

ABSTRACT: BACKGROUND: The role of laparoscopic surgery in the management of benign cystic and solid liver tumours appears to differ according to each tumour type. As regards congenital liver cysts, laparoscopic treatment is now the gold standard for treating selected, huge, accessible, highly symptomatic or complicated cysts. In contrast, the laparoscopic approach is not useful for patients suffering from adult polycystic liver disease (PLD), except for type I PLD with large multiple hepatic cysts. For benign hepatocellular tumours, the surgical management has recently benefited from a better knowledge of the natural history of each type of tumour and from the improvement of imaging techniques in assuring a precise diagnosis of tumour nature. Thus the general tendency has led to a progressive restriction and tailoring of indications for resection in benign liver tumours, selecting only patients with huge, specifically symptomatic or compressive benign tumours or patients suffering from liver cell adenoma. Despite the enthusiastic use of the laparoscopic approach, selective indications for resection of benign liver tumours should indeed remain unchanged. For all types of benign liver tumours, the best indication remains small, superficial lesions, located in the anterior or the lateral segments of the liver. Deep, centrally located lesions or tumours in contact with major vascular or biliary trunks are not ideal candidates for laparoscopic liver resections. When performed by expert liver and laparoscopic surgeons using an adequate surgical technique, the laparoscopic approach is safe for performing minor liver resections and is accompanied by the usual postoperative benefits of laparoscopic surgery. When applied in selected patients and tumours, laparoscopic management of benign liver diseases appears to be a promising technique for hepatobiliary surgeons.

SUBMITTER: Gigot JF

PROVIDER: S-EPMC2020682 | biostudies-other | 2004

REPOSITORIES: biostudies-other

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Project description:BackgroundThe scarcity of grafts available necessitates a system that considers expected posttransplant survival, in addition to pretransplant mortality as estimated by the MELD. So far, however, conventional linear techniques have failed to achieve sufficient accuracy in posttransplant outcome prediction. In this study, we aim to develop a pretransplant predictive model for liver recipients' survival with benign end-stage liver diseases (BESLD) by a nonlinear method based on pretransplant characteristics, and compare its performance with a BESLD-specific prognostic model (MELD) and a general-illness severity model (the sequential organ failure assessment score, or SOFA score).Methodology/principal findingsWith retrospectively collected data on 360 recipients receiving deceased-donor transplantation for BESLD between February 1999 and August 2009 in the west China hospital of Sichuan university, we developed a multi-layer perceptron (MLP) network to predict one-year and two-year survival probability after transplantation. The performances of the MLP, SOFA, and MELD were assessed by measuring both calibration ability and discriminative power, with Hosmer-Lemeshow test and receiver operating characteristic analysis, respectively. By the forward stepwise selection, donor age and BMI; serum concentration of HB, Crea, ALB, TB, ALT, INR, Na(+); presence of pretransplant diabetes; dialysis prior to transplantation, and microbiologically proven sepsis were identified to be the optimal input features. The MLP, employing 18 input neurons and 12 hidden neurons, yielded high predictive accuracy, with c-statistic of 0.91 (P<0.001) in one-year and 0.88 (P<0.001) in two-year prediction. The performances of SOFA and MELD were fairly poor in prognostic assessment, with c-statistics of 0.70 and 0.66, respectively, in one-year prediction, and 0.67 and 0.65 in two-year prediction.Conclusions/significanceThe posttransplant prognosis is a multidimensional nonlinear problem, and the MLP can achieve significantly high accuracy than SOFA and MELD scores in posttransplant survival prediction. The pattern recognition methodologies like MLP hold promise for solving posttransplant outcome prediction.

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Laparoscopic management of benign liver diseases: where are we?

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