Multi-modal laparoscopic liver navigation

Liver cancer is one of the deadliest types of cancer, with more than one million new patients diagnosed each year around the world. A major aim of medical innovation in this field is trying to offer curative-intent treatment to as many patients as possible, meaning to provide a therapy which has a reasonable chance to fully cure the disease. Minimally invasive “key-hole surgery”, also known as laparoscopy, is an increasingly popular practice and patients report a higher quality of life after laparoscopic surgery than after traditional open surgery. These surgeries can be relatively straightforward for small tumors close to the organ surface, but access to more challenging tumor locations will require careful planning to ensure the removal of diseased tissue while not spreading tumor cells during the surgery. During the surgery, it is important to exactly follow this plan, which is difficult in laparoscopic surgery due to complex organ anatomy and limited viewing angle. Our project aims to overcome these limitations by creating a GPS for minimally invasive liver surgery, allowing the surgeon to navigate through the organ until the tumor is safely removed. It also aims to show risk structures lying hidden in the organ beneath the surface, so the surgeon can safely circumvent them and avoid dangerous complications like bleeding or injury to bile ducts. To this end, tracking technology will be combined with intraoperative imaging like computed tomography scans, surgical ultrasound and algorithmic evaluation of the laparoscopic video images.

As modern surgery is increasingly being driven towards the minimally invasive approach, incisions into the patient body to reach and expose organs are kept to minimal dimensions, which implies a growing need for complementary and/or alternative visualization techniques. Laparoscopic surgery tackles this challenge through the incorporation of endoscopic systems. However, endoscopy presents the limitations of being confined to the restricted viewing field of the optical device and of visualizing only the surface. In this regard, 3D image data sets from other imaging modalities can help visualize structures, anatomies and pathologies below the surface, assumed these are registered to the optical view. These 3D models may be overlaid and fused with a laparoscopic video image in an augmented reality. The long-term goal of this project is to demonstrate that image-registered laparoscopic techniques will increase the efficiency and reduce the morbidity of tumor resection. As the soft-tissue anatomy moves and deforms throughout surgery, intra-operatively acquired datasets are needed to monitor the current state of the organ. The goal of this PhD project is to develop the necessary information extraction and fusion algorithms for ultrasound and optical images. Once the algorithmic building blocks are available, they will be brought together in a prototype navigation system ready for real-time use. Finally, the performance will be evaluated in a (pre-)clinical feasibility study. A close collaboration between Oslo Intervention Centre and Siemens Healthcare AS, Oslo, has been established to facilitate this project. Apart from scientific contributions to the field of image-guided laparoscopic surgery, a product enabling better and safer resection of abdominal tumors might result in the future.