Computer-assisted risk prevention in surgical and interventional treatment of liver tumor

Computational support in intervention planning promises to support the subjective interpretation of data with reproducible measurements. Moreover, it is possible to develop and apply models that provide additional information which is not directly visible in the data. Based on computer-tomography multi-slice images of the liver, the planning software developed by Fraunhofer MEVIS provides valuable tools for the preoperative evaluation of surgical strategies. To support the surgeon in the detailed assessment and optimization of procedures, image based criteria for the surgical planning are provided in a quantitative manner for evidence-based decision making. In radiofrequency ablation of liver tumors, the treatment success highly depends on an effective placement of the radiofrequency applicators into the tumor to achieve sufficient coagulative necrosis. Beside tumor size and shape, the cooling effects of surrounding vessels are taken into account for a numerical estimation of the accessible thermal destruction. A fast approximation of costly numerical simulation supports the physician in finding an optimized placement. In order to transfer this preoperative planning information into the intraoperative stage, it is important to clearly understand the user's needs in the restricted setting of the clinical situation. The presentation of information according to cognitive needs calls for a context-driven reduction of complexity. Alertness should be focused on critical locations. Our aim is to provide surgeons and physicians with efficient tools for the assessment of planning information in diagnosis and therapy, which integrate well in the workflow of liver interventions. In this paper we will discuss approaches for a reliable and robust computational support developed at Fraunhofer MEVIS as part of the FUSION consortium.