Project description
Making radiotherapy safer with AI
Despite radiotherapy (RT) being crucial for about half of all cancer patients, fewer than 80 % in Europe receive it. This is largely due to fears of serious side effects. RT can damage healthy tissues near tumours, sometimes fatally, as seen in a major lung cancer trial where heart damage outweighed tumour control. In this context, the ERC-funded AIDose project aims to tackle this. By combining AI and advanced medical imaging, AIDose will build the first toxicity risk atlas for organs in the chest and abdomen. This 3D map will identify the most vulnerable organ subregions, helping oncologists tailor treatment more safely. The project could revolutionise how doctors predict and prevent radiation harm in cancer care.
Objective
Radiotherapy (RT) is a critical component of cancer treatment, potentially benefiting approximately 50% of patients. However, less than 80% of patients who could benefit from RT actually receive it in Europe. The risk of toxicities, i.e. the radiation-induced damage of healthy tissues, is one of the main reasons why oncologists may exclude a potentially beneficial RT from the treatment regimen. For example, a recent analysis of the RTOG 0617 trial highlighted that the tumor control benefits of high-dose lung RT are accompanied by higher mortality rates due to extensive heart irradiation. The AIDose project will leverage my work on hepatobiliary toxicity prediction, artificial intelligence (AI) advancements, and medical image analysis to develop the first toxicity risk atlas for thoracic and abdominal organs-at-risk (OARs), i.e. organs located in close proximity to tumors. The atlas is envisioned as a three-dimensional map of OARs with pinpointed anatomical subregions associated with high toxicity risks. The AIDose project has four aims: a) developing AI-driven solutions for morphological and radiomic profiling of OARs; b) extracting and analyzing non-dosimetric clinical features associated with toxicities; c) utilizing AI to identify consistent patterns in radiation doses delivered to OAR subregions, and correlating them with toxicity risks; d) validating the resulting toxicity atlas against multi-hospital RT data. The feasibility of AIDose is supported by my previous research on liver and head-and-neck RT planning, which resulted in publications in key journals in the field and an award from the American Association of Medical Physicists. The use of AI for radiotherapy planning and outcome prediction is believed to be the main area of impact by the American and European Societies for Radiation Oncology. This proposal represents a unique opportunity to advance this highly innovative and clinically important research direction.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences sociology demography mortality
- medical and health sciences clinical medicine oncology
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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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 - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-COG
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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.
1165 KOBENHAVN
Denmark
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