Virtual liver surgery planning with segmented CT Images

Resection is the treatment of choice for patients suffering from liver tumors. Knowledge about involved liver segments, tumor size and topographic relationship of the tumor to vessels is needed for the decision if sufficient liver function capacity is guaranteed after a resection and for detailed planning of a possible resection. The main information sources are cross sectional imaging modalities like CT which deliver 2D images. The radiologist has thus to put all the information of the cross sectional images together in order to provide the surgeons with the needed information about the 3D topology. This process is difficult, tedious and time consuming. Combining the methods of medical computer vision and graphics a liver surgery planning system can be developed that enables a better overview and thus helps unfolding the full potential of surgical methods. Available approaches show that a number of improvements, specially on the fields of automation of segmentation and user friendly visualization are necessary to attain clinical applicability and gain the full acceptance by radiologists and surgeons. The proposed project will develop an experimental environment for the staging of liver operations. Special efforts will be put on two issues. First, a fully automated segmentation of the liver, its vessels and tumors will be studied. Second, the environment for the interactive, cooperative visualization of the medical sensor data, the extracted anatomical structures, and for the use of tools to assess the best surgical approach will be developed and assessed. After development, the approaches for segmentation/partitioning, visualization and interactive resection will undergo a careful validation procedure. The outcome of the proposed project will be a basis for the development of routinely useable liver surgery planning systems.

Surgical resection of liver tumors requires a detailed three-dimensional understanding of a complex arrangement of vasculature, liver segments and tumors inside the liver. In most cases, surgeons need to develop this understanding by looking at sequences of axial images from modalities like X-ray computed tomography (CT). Combining the methods of medical computer vision and graphics a liver surgery planning system was developed. It allows physicians to simulate and evaluate different resections plans and thus helps unfolding the full potential of surgical methods. Therefore, the developed system supports surgeons in finding the optimal treatment strategy for each patient. The use of Augmented Reality (AR) techniques contributes to a user-friendly design and simplifies complex interaction with 3D objects. To ease the data preparation process needed for the virtual surgical planning, automated methods for segmentation of the liver, tumors and portal veins in CT data have been developed. Automated segmentation can contain errors due to pathological changes of organ appearance. Hence, a tool for fixing segmentation errors utilizing AR techniques has been developed to avoid a time consuming manual segmentation of such cases. The developed method for liver segment partitioning allows an assessment of post surgical remaining liver volume, which is important for the survival of the patient. Several AR tools developed for visualization, interaction, measurements (volume, distances, etc.), and automated generation of resection proposals support surgeons during the virtual planning of liver resections. Evaluation of the developed virtual liver surgery planning system has shown a good acceptance by physicians and offers several advantages compared to traditional planning approaches. Work on the planning system is continued in an already granted follow-up research project (P17066-N04) which deals with the integration of an additional imaging modality that will allow the assessment of regional liver function.