For liver surgical planning, the structure and morphology of the hepatic vessels and their relationship to tumors are of major interest. To achieve a fast and robust assistance with optimal quantitative and visual information, we present methods for a geometrical and structural analysis of vessel systems. Starting from the raw image data a sequence of image processing steps has to be carried out until a three-dimensional representation of the relevant anatomic and pathologic structures is generated. Based on computed tomography (CT) scans, the following steps are performed. 1) The volume data is preprocessed and the vessels are segmented. 2) The skeleton of the vessels is determined and transformed into a graph enabling a geometrical and structural shape analysis. Using this information the different intrahepatic vessel systems are identified automatically. 3) Based on the structural analysis of the branches of the portal vein, their vascular territories are approximated with different methods. These methods are compared and validated anatomically by means of corrosion casts of human livers. 4) Vessels are visualized with graphics primitives fitted to the skeleton to provide smooth visualizations without aliasing artifacts. The image analysis techniques have been evaluated in the clinical environment and have been used in more than 170 cases so far to plan interventions and transplantations.

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Automatic liver tumor segmentation would have a big impact on liver therapy planning procedures and follow-up assessment, thanks to standardization and incorporation of full volumetric information. In this work, we develop a fully automatic method for liver tumor segmentation in CT images based on a 2D fully convolutional neural network with an object-based postprocessing step. We describe our experiments on the LiTS challenge training data set and evaluate segmentation and detection performance. Our proposed design cascading two models working on voxel- and object-level allowed for a significant reduction of false positive findings by 85% when compared with the raw neural network output. In comparison with the human performance, our approach achieves a similar segmentation quality for detected tumors (mean Dice 0.69 vs. 0.72), but is inferior in the detection performance (recall 63% vs. 92%). Finally, we describe how we participated in the LiTS challenge and achieved state-of-the-art performance.

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Background & ObjectivesThe Portable Document Format (PDF) is the de-facto standard for the exchange of electronic documents. It is platform-independent, suitable for the exchange of medical data, and allows for the embedding of three-dimensional (3D) surface mesh models. In this article, we present the first clinical routine application of interactive 3D surface mesh models which have been integrated into PDF files for the presentation and the exchange of Computer Assisted Surgery Planning (CASP) results in liver surgery. We aimed to prove the feasibility of applying 3D PDF in medical reporting and investigated the user experience with this new technology.MethodsWe developed an interactive 3D PDF report document format and implemented a software tool to create these reports automatically. After more than 1000 liver CASP cases that have been reported in clinical routine using our 3D PDF report, an international user survey was carried out online to evaluate the user experience.ResultsOur solution enables the user to interactively explore the anatomical configuration and to have different analyses and various resection proposals displayed within a 3D PDF document covering only a single page that acts more like a software application than like a typical PDF file (“PDF App”). The new 3D PDF report offers many advantages over the previous solutions. According to the results of the online survey, the users have assessed the pragmatic quality (functionality, usability, perspicuity, efficiency) as well as the hedonic quality (attractiveness, novelty) very positively.ConclusionThe usage of 3D PDF for reporting and sharing CASP results is feasible and well accepted by the target audience. Using interactive PDF with embedded 3D models is an enabler for presenting and exchanging complex medical information in an easy and platform-independent way. Medical staff as well as patients can benefit from the possibilities provided by 3D PDF. Our results open the door for a wider use of this new technology, since the basic idea can and should be applied for many medical disciplines and use cases.

Abstract. We present a fast and accurate tool for semiautomatic segmentation of volumetric medical images based on the live wire algorithm, shape-based interpolation and a new optimization method. While the user-steered live wire algorithm represents an efficient, precise and reproducible method for interactive segmentation of selected twodimensional images, the shape-based interpolation allows the automatic approximation of contours on slices between user-defined boundaries. The combination of both methods leads to accurate segmentations with significantly reduced user interaction time. Moreover, the subsequent automated optimization of the interpolated object contours results in a better segmentation quality or can be used to extend the distances between user-segmented images and for a further reduction of interaction time. Experiments were carried out on hepatic computer tomographies from three different clinics. The results of the segmentation of liver parenchyma have shown that the user interaction time can be reduced more than 60% by the combination of shape-based interpolation and our optimization method with volume deviations in the magnitude of inter-user differences.

The aim of this study was to evaluate a software tool for non-invasive preoperative volumetric assessment of potential donors in living donated liver transplantation (LDLT). Biphasic helical CT was performed in 56 potential donors. Data sets were post-processed using a non-commercial software tool for segmentation, volumetric analysis and visualisation of liver segments. Semi-automatic definition of liver margins allowed the segmentation of parenchyma. Hepatic vessels were delineated using a region-growing algorithm with automatically determined thresholds. Volumes and shapes of liver segments were calculated automatically based on individual portal-venous branches. Results were visualised three-dimensionally and statistically compared with conventional volumetry and the intraoperative findings in 27 transplanted cases. Image processing was easy to perform within 23 min. Of the 56 potential donors, 27 were excluded from LDLT because of inappropriate liver parenchyma or vascular architecture. Two recipients were not transplanted due to poor clinical conditions. In the 27 transplanted cases, preoperatively visualised vessels were confirmed, and only one undetected accessory hepatic vein was revealed. Calculated graft volumes were 1110 +/- 180 ml for right lobes, 820 ml for the left lobe and 270 +/- 30 ml for segments II+III. The calculated volumes and intraoperatively measured graft volumes correlated significantly. No significant differences between the presented automatic volumetry and the conventional volumetry were observed. A novel image processing technique was evaluated which allows a semi-automatic volume calculation and 3D visualisation of the different liver segments.

The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future.