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High Performance Soft-tissue Navigation. (HiPerNav)

Primary liver cancer, which consists predominantly of hepatocellular carcinoma (HCC), is the fifth most common cancer worldwide and the third most common cause of cancer mortality. A successful surgical resection of HCC requires complete removal of the tumour while sparing as much healthy tissue as possible. Due to technical and clinical difficulties relatively low percentage of patients are eligible for resection. There is an urgent need to increase the patient eligibility and improve the survival prognosis after liver interventions. HiPerNav will train early stage researchers (biomedical engineers and medical doctors) to become international leading in key areas of expertise through a novel coordinated plan of individual research projects addressing specific bottlenecks in soft tissue navigation for improved treatment of liver cancer. The multidisciplinary dialogue and work between clinicians and biomedical engineers is crucial to address these bottlenecks. By providing researchers with knowledge and training within specific topics from minimally invasive treatment, biomedical engineering, research methodologies, innovation and entrepreneurship, the link between academic research and industry will be strengthened. This allows for easy transfer of promising results from the research projects to commercially exploitable solutions. The global image guided surgery devices market is promising; it was valued at USD 2.76 billion in 2013 and is projected to expand 6.4% from 2014 to 2022 to reach USD 4.80 billion in 2022. The market for soft-tissue navigation is still in its infancy, mainly due to challenges in achieved accuracy for targeting deformable and moving organs. By providing multi-disciplinary training, the researchers in this consortium of international leading research institutions, universities and industry will initiate true translational research from academic theoretical ideas to the clinical testing of prototype, developed solutions and tools.

Universidad de Córdoba

The overall goal of HiPerNav is to successfully train and educate ESRs in the multidisciplinary field of image-guided interventions. The scientific and clinical goal is to develop a navigation platform for management of liver cancer and metastases treatment to improve the eligibility and prognosis for liver surgical procedures and ablation treatment. This platform should enable an integral management of surgical workflow in: (1) preoperative surgical planning; (2) intra-operative resection navigation and ablation monitoring; (3) post operative quality control.

To provide detailed understanding of treatment planning and navigation workflow in order to:
(1) Verify which visualization interfaces enable the most intuitive and fail-safe data interpretation and decision making.
(2) Serve as the foundation of the software and interface architectures.

- D6.1: Teaching materials (slides, lab. practices, and online seminars) [10]. Teaching materials (slides, lab. practices, and online seminars)
- D6.2: Report: "Study of parallelizable codes in WP2 to WP5" [18]. Report: "Study of parallelizable codes in WP2 to WP5"
- D6.3: Optimized parallel implementations of algorithms from WP2 to WP5 [40]. Optimized parallel implementations of algorithms from WP2 to WP5
- D6.4: Integration of parallel implementations in WP2 to WP5 [48]. Integration of parallel implementations in WP2 to WP5

The innovative training and research programme of HiPerNav has been designed to foster the knowledge exchange through cross-border and cross-sector mobility of researchers. The HiPerNav training programme will prepare ESRs (biomedical engineers and medical doctors) to face current and future technical and clinical challenges associated with image guided surgery for cancer treatment.


Arquitectura de Computadores, Electrónica y T.E

Code PAIDI: TIC-252


Universidad de Córdoba

Budget of Andalusian group: € 495.745,92€

Keywords: Minimally Invasive treatment, Laparoscopic liver surgery, Image guided surgery, Navigation, User-interaction, High performance computing, Image processing, Medical imaging, Biomechanical modeling, Medical engineering, biomedical engineering and technology,
Duration: 48 months. November, 1th 2016 to October, 30th 2020
Project cost: € 4.041.920,04€