Clinical implementation of in-house developed MR-based patient-specific 3D models of liver anatomy

Knowledge of patient-specific liver anatomy is key to patient safety during major hepatobiliary surgery. Three-dimensional (3D) models of patient-specific liver anatomy based on diagnostic MRI images can provide essential vascular and biliary anatomical insight during surgery. However, a method for generating these is not yet publicly available. This paper describes how these 3D models of the liver can be generated using open source software, and then subsequently integrated into a sterile surgical environment. The most common image quality aspects that degrade the quality of the 3D models as well possible ways of eliminating these are also discussed. Per patient, a single diagnostic multiphase MRI scan with hepatospecific contrast agent was used for automated segmentation of liver contour, arterial, portal, and venous anatomy, and the biliary tree. Subsequently, lesions were delineated manually. The resulting interactive 3D model could be accessed during surgery on a sterile covered tablet. Up to now, such models have been used in 335 surgical procedures. Their use simplified the surgical treatment of patients with a high number of liver metastases and contributed to the localization of vanished lesions in cases of a radiological complete response to neoadjuvant treatment. They facilitated perioperative verification of the relationship of tumors and the surrounding vascular and biliary anatomy, and eased decision-making before and during surgery.Radiolog

Remote visualization techniques for medical imaging research and image-guided procedures

There has been a tremendous increase in medical image computing research and development over the last decade. This trend continues to gain further speed, driven by the sheer amount of multimodal medical image data but also by the broad spectrum of computer-assisted applications. At the same time, user expectations with respect to diagnostic accuracy, robustness, speed, automation, workflow efficiency, broad availability, as well as intuitive use have reached a high level already. More recently, cloud computing has entered the field of medical imaging, providing means for more flexible workflows including the support of mobile devices and even a medical imaging equivalent of the App Store paradigm. This paper discusses requirements for modern medical software systems with a focus on image analysis and visualization. It provides examples from different areas of application covering collaborative multi-center imaging trials with online reading and advanced analysis as well as an intraoperative augmented-reality scenario for translating liver surgery planning data directly into the operating room through a mobile multi-touch device. A combination of remote rendering and visualization techniques with an efficient modular development framework (MeVisLab) is presented as a basis for fast implementation, early evaluation, and iterative optimization in these applications