The STRATUM Project: A Point-of-Care Computing System based on Multimodal Data Processing using Artificial Intelligence for Improving Brain Tumour Surgeries
Himar Fabelo, Raquel Leon, Laura Quintana-Quintana, Gustavo M. Callico, STRATUM Consortium
Presented by Raquel Leon
Brain and CNS (Central Nervous System) cancer was the 12th most common cancer in terms of mortality in 2022, with an estimated 321,731 incident cases, associated to 248,500 deaths worldwide for both sexes and all ages. In 2050, these numbers are expected to increase 56.6% and 64.8% in incidences and mortality, respectively. Particularly, brain tumours account for more than 90% of occurrence within CNS cancers, linked to high mortality and morbidity, especially in paediatric cases. Neurosurgery is the main treatment for brain tumours. During this procedure, the neurosurgeon makes an opening in the skull of the patient (called craniotomy) and, whenever possible, tries to resect the entire tumour from the brain, guided by a neurosurgical navigation system based on preoperative magnetic resonance images. Neurosurgeons face several challenges to address brain tumour surgeries, when trying to identify tumour mass and to distinguish between normal tissue and brain tumour margins, such as; 1) lack of specific tools to enhance the surgeons’ vision and provide real-time personalized tissue diagnostics for surgical guidance and decision making; 2) Lack of real-time representation, interpretation and analysis tools for the large amount of data acquired by various independent systems; 3) Long waiting times for intraoperative pathology consultation; 4) Non-existence of commercial tools for the analysis and visualisation of the brain shift phenomenon; 5) Use of photosensitive drugs or contrast agents because of employing fluorescent guidance tools. For these reasons, an innovative neurosurgical decision support tool able to provide quick, accurate and highly personalized diagnostics for optimal decision in neurosurgical practice could ensure a reduction of errors and delays during surgeries, and also save the associated medical costs. STRATUM is a 5-year Horizon Europe funded project with the goal of developing an innovative 3D decision support tool for brain tumour surgeries, based on real-time multimodal data processing using Artificial Intelligence (AI) algorithms. The proposed tool is envisioned as an energy-efficient Point-of-Care computing system to be integrated within neurosurgical workflows to aid surgeons to make informed, efficient, and accurate decisions during surgical procedures. STRATUM is pursuing the following objectives: 1) To foster advances in personalized medicine based on multimodal data, including the emerging as hyperspectral imaging tehnique; 2) To increase intraoperative diagnostic accuracy of brain tumours; 3) To reduce surgery time with respect to current neurosurgical operations by performing in-situ intraoperative pathological assessment and using high performance computing platforms for real time data processing; 4) To improve cost- and energy-efficiency of current neurosurgical workflows by integrating different data sources in an interactive non-contact 3D graphical user interface; 5) To clinically demonstrate the prototype in a two-year clinical study in 3 clinical sites in 2 different countries, including an early health technology assessment; 6) To prepare a preliminary business plan and the roadmap for commercialization at the end of the project. The expected long-term impact of STRATUM is to reduce the duration of surgical procedures, thus decreasing patients’ risks, but also optimising the resources of European health care systems.
Dr. Raquel Leon has been working, since 2018, on the use of Hyperspectral Imaging for real-time cancer detection in the University of Las Palmas de Gran Canaria (ULPGC), Spain, where she received her PhD in Telecommunication Technologies from the ULPGC.
Since 2023, she started a position as Research Project Manager in the STRATUM project. STRATUM is a European project with the goal of developing a clinically demonstrated 3D Decision Support Tool for brain surgery guidance and diagnostics based on multimodal data processing through Artificial Intelligence algorithms that will be integrated as an energy-efficient Point-of-Care computing tool. The STRATUM consortium, coordinated by the ULPGC, is an interdisciplinary research team of optical and imaging engineers, physicists, software engineers, clinicians, and industry stakeholders.
She has previously worked in other research projects in the field of imaging technologies for cancer (ITHaCA, TALENT), disease prevention (WARIFA), physiological monitoring (O3NPIQ, EPOOzo). In 2020, she obtained a predoctoral research grant from the Canary Islands Government and in 2024, she received the Outstanding Young Researchers Award for her contributions in the field of Engineering and Architecture awarded by the ULPGC.