Summary
Integrated digital diagnostics can support complex surgeries in many anatomies where brain tumour surgery is one of the most complex cases. Neurosurgeons face several challenges during brain tumour surgeries, such as critical tissue and brain tumour margins differentiation or the interpretation of large amount of data available provided by several independent devices.
To overcome these challenges, STRATUM will develop a 3D Decision Support Tool for brain surgery guidance and diagnostics (reaching TRL7) based on multimodal data processing through Artificial Intelligence (AI) algorithms that will be integrated as an energy-efficient Point-of-Care computing tool. It will be developed following a co-creation methodology involving key stakeholders and end-users. STRATUM will pursue the following objectives:
1) To foster advances in personalized medicine based on multimodal data (including the emerging hyperspectral imaging modality) and AI.
2) To increase the intraoperative diagnostic accuracy of brain tumours, improving surgical outcomes and patients’ quality of life.
3) To reduce surgery time with respect to current neurosurgical operation durations.
4) To improve current cost- and energy-efficiency of neurosurgical workflows.
5) To demonstrate the prototype in a two-year clinical study in 3 clinical sites, including an early health technology assessment.
6) To prepare the preliminary business plan and the TRL9 roadmap after the project ending.
An optimized integration and processing of available and new emerging data sources would aid surgeons in timely efficient and correct decision-making in tissue removal. This would maximize the degree of resection while simultaneously minimize the risk of neurological deficits. Moreover, time efficient surgical procedures not only benefit the patients directly by minimizing anaesthesia time and risks of e.g. postoperative infections, but also indirectly by optimizing resources of the health care system.
To overcome these challenges, STRATUM will develop a 3D Decision Support Tool for brain surgery guidance and diagnostics (reaching TRL7) based on multimodal data processing through Artificial Intelligence (AI) algorithms that will be integrated as an energy-efficient Point-of-Care computing tool. It will be developed following a co-creation methodology involving key stakeholders and end-users. STRATUM will pursue the following objectives:
1) To foster advances in personalized medicine based on multimodal data (including the emerging hyperspectral imaging modality) and AI.
2) To increase the intraoperative diagnostic accuracy of brain tumours, improving surgical outcomes and patients’ quality of life.
3) To reduce surgery time with respect to current neurosurgical operation durations.
4) To improve current cost- and energy-efficiency of neurosurgical workflows.
5) To demonstrate the prototype in a two-year clinical study in 3 clinical sites, including an early health technology assessment.
6) To prepare the preliminary business plan and the TRL9 roadmap after the project ending.
An optimized integration and processing of available and new emerging data sources would aid surgeons in timely efficient and correct decision-making in tissue removal. This would maximize the degree of resection while simultaneously minimize the risk of neurological deficits. Moreover, time efficient surgical procedures not only benefit the patients directly by minimizing anaesthesia time and risks of e.g. postoperative infections, but also indirectly by optimizing resources of the health care system.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101137416 |
| Start date: | 01-12-2023 |
| End date: | 30-11-2028 |
| Total budget - Public funding: | 10 714 691,25 Euro - 9 990 566,00 Euro |
Cordis data
Original description
Integrated digital diagnostics can support complex surgeries in many anatomies where brain tumour surgery is one of the most complex cases. Neurosurgeons face several challenges during brain tumour surgeries, such as critical tissue and brain tumour margins differentiation or the interpretation of large amount of data available provided by several independent devices.To overcome these challenges, STRATUM will develop a 3D Decision Support Tool for brain surgery guidance and diagnostics (reaching TRL7) based on multimodal data processing through Artificial Intelligence (AI) algorithms that will be integrated as an energy-efficient Point-of-Care computing tool. It will be developed following a co-creation methodology involving key stakeholders and end-users. STRATUM will pursue the following objectives:
1) To foster advances in personalized medicine based on multimodal data (including the emerging hyperspectral imaging modality) and AI.
2) To increase the intraoperative diagnostic accuracy of brain tumours, improving surgical outcomes and patients’ quality of life.
3) To reduce surgery time with respect to current neurosurgical operation durations.
4) To improve current cost- and energy-efficiency of neurosurgical workflows.
5) To demonstrate the prototype in a two-year clinical study in 3 clinical sites, including an early health technology assessment.
6) To prepare the preliminary business plan and the TRL9 roadmap after the project ending.
An optimized integration and processing of available and new emerging data sources would aid surgeons in timely efficient and correct decision-making in tissue removal. This would maximize the degree of resection while simultaneously minimize the risk of neurological deficits. Moreover, time efficient surgical procedures not only benefit the patients directly by minimizing anaesthesia time and risks of e.g. postoperative infections, but also indirectly by optimizing resources of the health care system.
Status
SIGNEDCall topic
HORIZON-HLTH-2023-TOOL-05-05Update Date
12-03-2024
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HORIZON.2.1.5 Tools, Technologies and Digital Solutions for Health and Care, including personalised medicine
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Organisations
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| UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA (ULP) (Coördinator)
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| BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION (BSC)
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| Eindhoven University of Technology
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| FUNDACION CANARIA INSTITUTO DE INVESTIGACION SANITARIA DE CANARIAS
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| FUNDACION CANARIA PARQUE CIENTIFICO TECNOLOGICO DE LA UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA
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| OPTOMIC ESPAÑA, S.A
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| REGION STOCKHOLM
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| SAS UPMEM
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| SERVICIO MADRILENO DE SALUD
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| Technische Universität Kaiserslautern
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| UNIVERSIDAD POLITECNICA DE MADRID
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| UNIVERSITA DEGLI STUDI DI PAVIA
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| VEREIN DER EUROPAEISCHEN BURGERWISSENSCHAFTEN - ECSA E.V.