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AI to predict Cancer metastasis using Ultra-Echo-Sono imaging

Objective

Cancer metastasis is the leading cause of death within tumor disease and is currently an unmet clinical need. This dramatic clinical evidence requires immediate action in terms of early diagnosis and then pre-emptive therapies, not only for the primary tumor, but especially at the first stages of metastasis formation. Metastasis is the result of a complex mechanism, still under study, which involves the trafficking of biological materials, in particular extracellular vesicles (EVs), from the primary tumor site towards other tissues.
The project AI CUrES aims to propose novel methodologies for early diagnosis of metastasis, by gaining new knowledge at the early stage of their formation with a real-time and predictive approach. This work has the future vision of predicting possible patient’s outcomes and helping to set timely pre-emptive therapies. I believe that this is possible by exploiting the EVs specifically produced by the primary tumor, here by colorectal cancer (CRC). In AI CUrES, such EVs will be tagged by specific nanosized-contrast agents and their trafficking in biological media reported by an innovative multi-modal bioimaging technology having high resolution, deep tissue penetration, real-time and molecular characteristics. The collected images of EVs trafficking towards recipient cells or tissues will be refined and further elaborated by artificial intelligence algorithms, with the aim to predict the possible metastasis development from a starting CRC tumor mass.
AI CuRES will prove the efficacy of this approach by enabling, as expected outcomes, deep scientific knowledge on metastasis formation mechanisms and demonstrating a breakthrough innovation in bioimaging technologies and digital tools for health monitoring and diagnosis of oncological patients. The results can be also useful in other tumors leading to metastasis and to empower Europe towards digital tools for predictive diagnosis.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2022-POC2

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Host institution

POLITECNICO DI TORINO
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
CORSO DUCA DEGLI ABRUZZI 24
10129 Torino
Italy

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Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Beneficiaries (1)

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