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Press Release : Launch of Helicoid Project

HELICoiD is a European collaborative project funded by the Research Executive Agency, through the Future and Emerging Technologies (FET-Open) programme, under the 7th Framework Programme of the European Union.

Based on data from the World Cancer Research Fund (WCRF International), there were an estimated 12.7 million cancer cases around the world in 2008. This number is expected to increase to 21 million by 2030. Cancer of the lung is the most common cancer in the world (12.7%), followed by breast (10.9%), colorectal (9.8%), gastric (7.8%) and prostate cancer (7.1%). Cancer therefore represents a large clinical problem which may be ameliorated if hyperspectral imaging could differentiate healthy and diseased tissues and so lead to better surgical removal.

Hyperspectral imaging (also known as imaging spectroscopy) is a technique that generates very high-dimensional images through the use of sensor optics with a large number of nearly contiguous spectral bands. Due to this sampling strategy, hyperspectral images provide much more information about the captured scene than traditional solutions based on panchromatic or multispectral approaches.

One of the major benefits from such technology is likely to be in the removal of brain tumours. There are several reasons for this. Brain tumours, more than any other cancers, can resemble the normal surrounding brain making them difficult to differentiate. Unlike many tumours, they infiltrate the surrounding tissue and thus their borders are indistinct and difficult to identify. The surrounding brain is also very eloquent and there is no redundancy as is seen in many other organs where it is normal to remove the tumour with a surrounding rim of healthy tissue. This is not possible in the brain where it is essential to identify accurately the border between normal and disease. Although malignant primary brain tumours in adults occupy the 13th place in frequency of all cancers, due to their particularly poor prognosis they are the fifth most common cause of cancer death in the under 65 year old population. Moreover they are the second most common cancer in children and the most common cause of cancer death in children.

Starting with some specific types of cancers, this project will try to generalize the methodology to discriminate between healthy and malignant tissues in real-time during surgical procedures. Using the hyperspectral signatures of the healthy tissues and the same tissues affected by cancer, a model of how cancer affects to the hyperspectral signature will be derived. The research will start with the challenging task of brain cancer detection. A precise resection of the gliomas will minimize the negative effect of removing brain cells while assuring an effective tumour resection. The second type of tumours to be analysed will be the lung and breast cancers as they represent the two most common cancers in the world. As cancer supposes a change in the cellular physiology, it should be detected as a change in the hyper-spectral signature. This project will try to determine if there is a certain pattern that could be identified as a cancer hyperspectral signature. This information will be provided, through different display devices to the surgeon, overlapping normal viewing images with simulated colours that will indicate the cancer probability of the tissue presently exposed during every instant of the surgical procedure. A high-efficiency hardware/software prototype will be developed with the aim of recognising cancer tissues on real time.

Currently the main tool for differentiating normal from malignant tissue remains the human eye. Other techniques have been developed but none has succeeded in reliable tissue differentiation. Neuronavigation is plagued by brain shift, ultrasound is highly operator dependant and intraoperative MRI (Magnetic Resonance Imaging) fails to provide real time images obtaining just an occasional snapshot during surgery. Under these circumstances, hyperspectral imaging arises as a potential solution that allows a precise detection of the edges of the malignant tissues in real time, while assisting guidance for diagnosis during surgical interventions and treatment. Moreover, the cost associated with hyperspectral imaging instrumentation is significantly lower than the aforementioned techniques as it is based on conventional optical imaging technology. hyperspectral imaging supposes a non-contact, non-ionizing and minimal-invasive sensing technique based on registering extremely small wavelengths (normally in the nanometre range) of the tissues in order to determine their histological characteristics.

Research & Development activities will be mainly carried out by the 4 universities involved in the project: Universidad de Las Palmas de Gran Canaria acting as coordinator (Spain), the Imperial College of Science, Technology and Medicine in London (United Kingdom), the Universidad Politécnica de Madrid (Spain), and the Association pour la Recherche et le Développement des Méthodes et Processus Industriels, ARMINES, at Paris (France). The consortium also integrates 2 SMEs with wide experience in medical imaging technology and software development: ONCOVISION (Spain) and Virtual Angle (Netherlands). Clinical feasibility of the system will be assessed by Medtronic Ibérica (Spain), collaborating end-user, in the operating theatres of the University Hospital of Southampton NHS Foundation Trust (United Kingdom) and the Hospital Doctor Negrín at Las Palmas (Spain).


Kickoff meeting held in Spain, at the University of Las Palmas de Gran Canaria (ULPGC) during the 30th and 31st January 2014.