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PRedictive mOdeling Of RAdiaTion-Induced CArdiotoxicity after breast cancer radiotherapy

Project description

Minimising cardiotoxicity from radiotherapy for breast cancer

Breast cancer (BC) is usually treated with radiotherapy. However, the irradiation of healthy tissue along with cancerous tissue inevitably occurs, often resulting in cardiac toxicity, a condition that increases cardiac morbidity and mortality among BC patients. Efforts to minimise the side effects are underway via the EU-funded PRO-ORATICA project. The researcher will apply innovative image processing and analysis techniques to detect radio-sensitive cardiac regions and develop multivariable subregion-driven predictive models of cardiac toxicities. Use of artificial intelligence in decision-making tools will aid in developing integrative, personalised and feasible strategies for reducing cardiac complications arising from radiotherapy.

Objective

Breast cancer is the most common cancer among women worldwide. Radiotherapy (RT) is an essential component of the treatment for the majority of BC patients. Although the therapeutic benefit of RT is well-proven, it may be offset by secondary effects, such as cardiac toxicity, arising from the inevitable irradiation of healthy tissue. Increased cardiac morbidity and mortality rates are well documented after breast cancer RT, but the exact underlying mechanisms behind cardiac toxicity is still unclear. Such information is crucial to develop accurate predictive models of cardiotoxicity and to devise new strategies for personalized RT treatments, either by optimizing the existing protocols or by considering emerging RT techniques, such as proton beam therapy.
The goal of PRO-ORATICA project, carried out by the researcher Eugenia Mylona, is to devise decision-making tools aimed at proposing integrative and feasible strategies for reducing radiation-induced cardiac complications after breast cancer RT. Novel image processing and analysis techniques will be applied to identify radio-sensitive cardiac regions, while artificial intelligence will be used to develop multivariable subregion-driven predictive models of cardiac toxicities. Strategies will be proposed for transferring the developed models to the clinics, offering optimized personalized treatments with reduced cardiac complications. This research project can be practice-changing as it may define new improved standards for the treatment of breast cancer, potentially enhancing patients’ quality-of-life.
The fellowship will take place at Universidad Carlos III de Madrid (UC3M) under the supervision of Dr Javier Pascau, Associate Professor at the Bioengineering and Aerospace Engineering Department. As part of this project, the researcher will carry out a secondment in the Clínica Universidad de Navarra (CUN) in Madrid, under the co-supervision of Dr Felipe Calvo, head of the Radiation Oncology Department.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

(opens in new window) H2020-MSCA-IF-2020

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Coordinator

UNIVERSIDAD CARLOS III DE MADRID
Net EU contribution
€ 160 932,48
Address
CALLE MADRID 126
28903 Getafe (Madrid)
Spain
Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 160 932,48