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International Clinical Validation of Radiomics Artificial Intelligence for Breast Cancer Treatment Planning

Project description

DEENESFRITPL

International study to validate AI for the prediction of treatment response in breast cancer

Radiomics is a quantitative approach to medical imaging that extracts information not accessible through traditional visual inspection of generated images, particularly in oncology. The aim of the EU-funded RadioVal project is to evaluate the potential of radiomics to predict response to neoadjuvant chemotherapy in breast cancer patients, using AI. The project will leverage large imaging repositories and results generated by previous EU-funded projects. Furthermore, RadioVal will implement a multi-faceted evaluation of radiomics AI tools in eight hospitals across Europe and beyond, to test their technical robustness, algorithmic fairness, as well as usability and acceptance in clinical setting. The results are expected to increased trust in AI-driven clinical decision-making, and reduce over-treatment and improve clinical outcome for breast cancer patients.

Objective

Breast cancer is now the most common cancer worldwide, surpassing lung cancer in 2020 for the first time. It is responsible for almost 30% of all cancers in women and current trends show its increasing incidence. Neoadjuvant chemotherapy (NAC) has shown promise in reducing mortality for advanced cases, but the therapy is associated with a high rate of over-treatment, as well as with significant side effects for the patients. For predicting NAC respondents and improving patient selection, artificial intelligence (AI) approaches based on radiomics have shown promising preclinical evidence, but existing studies have mostly focused on evaluating model accuracy, all-too-often in homogeneous populations.

RadioVal is the first multi-centre, multi-continental and multi-faceted clinical validation of radiomics-driven estimation of NAC response in breast cancer. The project builds on the repositories, tools and results of five EU-funded projects from the AI for Health Imaging (AI4HI) Network, including a large multi-centre cancer imaging dataset on NAC treatment in breast cancer. To test applicability as well as transferability, the validation with take place in eight clinical centres from three high-income EU countries (Sweden, Austria, Spain), two emerging EU countries (Poland, Croatia), and three countries from South America (Argentina), North Africa (Egypt) and Eurasia (Turkey).

RadioVal will develop a comprehensive and standardised methodological framework for multi-faceted radiomics evaluation based on the FUTURE-AI Guidelines, to assess Fairness, Universality, Traceability, Usability, Robustness and Explainability. Furthermore, the project will introduce new tools to enable transparent and continuous evaluation and monitoring of the radiomics tools over time. The RadioVal study will be implemented through a multi-stakeholder approach, taking into account clinical and healthcare needs, as well as socio-ethical and regulatory requirements from day one.

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Call for proposal

HORIZON-HLTH-2021-DISEASE-04

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

UNIVERSITAT DE BARCELONA
Net EU contribution
€ 801 250,00
Address
Gran via de les corts catalanes 585
08007 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
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Other funding
€ 0,00

Participants (15)

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Last update: 28 July 2022

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Permalink: https://cordis.europa.eu/project/id/101057699

European Union, 2023