participants Project: HiPerNav is a European project carried by Dr. Ole Jakob Elle, at the University of Oslo in Norway. It has 10 partners, including Dr. Joaquín Olivares at the University of Cordoba. Dr. Faouzi Alaya Sheikh Norges at Teknisk-Naturvitenskapelige University. Prof.Azeddine Beghdadi at the University of Paris 13. Dr. Matthias Peterhans of the CAScination Society in Switzerland. Dr. Stefan Weber at the University of Bern. Dr. Stephane Cotin and Hadrien Courtecuisse at Inria. Dr. Thomas Langø at Sintef. Teacher. Jenny Dankelman at the University of Delft and Prof. Guido Beldi Inselspital-Stiftung.

Project Summary: Liver cancer is the fifth most common cancer in the world and the third leading cause of cancer death. The liver is also a frequent target of metastases from other cancers, such as colorectal cancer, with an estimated 100,000 liver metastases in Europe. Liver resection is often the preferred treatment in patients with liver metastases, with 5-year survival rates of up to 58%. Successful surgical resection of hepatocellular carcinoma requires complete removal of the tumor, including a margin of safety while sparing healthy tissue as much as possible. However, due to technical and clinical difficulties only a relatively small percentage of patients are eligible for resection, and the recurrence rate is considerable.

Objectives: The overall goal of HiPerNav is to train and educate future surgeons in the multidisciplinary field of image-guided interventions. The scientific and clinical aspects are aimed at developing a navigation platform to assist in the treatment of cancer and liver metastases, in order to improve eligibility and prognosis for liver surgery. This platform must allow complete management of surgical operations in: (1) preoperative surgical planning; (2) navigation during intraoperative resection; (3) postoperative quality control. HiPerNav sub objectives are listed below:

·         Multimodal Imaging: Improving the quality of pre- and intra-operative images to provide high quality multimodal data. This allows the extraction of features, the customization of biomechanical models, the registration of images and the improvement of image-guided interventions.

  • Biomechanical modeling: provide effective and robust solutions for the use of biomechanical models during the intervention. 
  • Data Merge and Registration: Align Multimodal Images for Intervention Planning. Recalibrate intraoperative images with preoperative data and the patient.
  • Integration into the navigation platform: extend the Cascination vavigation platform to soft tissues. Test research results in a clinical setting.
  • High Performance Computing: Algorithm Acceleration in all stages of image processing to navigation.
  • User interaction: Provide a detailed understanding of planning and navigation processing.
  • Clinical pilots: allow the transfer of research results in the clinical field. Conduct clinical trials and educate surgeons on minimally invasive liver surgery guided by the image.

This project is starting up. We are in the process of recruiting the two doctoral students who will be financed on this project.