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A comprehensive CAD system based on radiologic- and pathologic-image biomarkers for diagnosis and prognosis of breast cancer relapse

Project description

DEENESFRITPL

Computer-aided design system for breast cancer classification and prognosis of relapse

Breast cancer (BC) incidence leads to more than 600 000 deaths annually. Distant metastasis due to illness relapse is incurable, underscoring the inadequacy of our understanding of its mechanisms. Thus, oncologists use screening programmes based on radiological and histopathological imaging to analyse tumours, study their immune microenvironment and predict the probability of distant metastasis and relapse. Funded by the Marie Skłodowska-Curie Actions programme, the BosomShield project proposes to join the two disciplines (pathological and radiological imaging) in a software that will analyse these images to classify cancer subtypes and predict distant metastasis and relapse. BosomShield will also provide high-level training to young researchers, advancing their skills and career prospects in BC research.

Objective

Breast cancer (BC) incidence in women produces more than 600,000 deaths each year. The primary cause of death in BC patients is metastasis, whereby cancer cells spread from their primary site of origin and grow in adjacent or distant sites. Distant metastasis produced due to the relapse of the illness is incurable, underscoring the inadequacy of our understanding of its mechanisms. The first step for fighting against disease progression is screening programs for BC focused on image analysis of mammography, MRI and tomosynthesis. Once the tumour has been diagnosed and given the high variability of clinical progressions, another problem arises: classifying the cancer type and determining the proper treatment for specific cancer. Moreover, in BC, the immune response from the tumour microenvironment has played an essential role in tumour evolution. To evaluate the tumour and its microenvironment, one technique garnered a lot of attention in the last years: Whole Slide Imaging (WSI). This technique replaces the use of the microscope for classical diagnosis. Still, it has also been used for developing biomarkers that allow the analysis of tumours and classification of cancer subtypes and the study of the immune tumour microenvironment. The use of WSI has applications for predicting the probability of relapse for distant metastasis. Now, for the first time, BosomShield proposes to join the two disciplines (pathological and radiological imaging) in a software that will analyze these images to classify the cancer subtypes and predict (together with the complete clinical history of the patient) the probability of relapse for distant metastasis. Besides, BosomShield will provide high-level training in BC research to young researchers by offering the necessary transferable skills for thriving careers underpinned using diverse disciplines, digital radiology and pathology, biomedical, AI, privacy and software development.

Fields of science

Programme(s)

Topic(s)

Call for proposal

HORIZON-MSCA-2021-DN-01

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Funding Scheme

HORIZON-AG-UN - HORIZON Unit Grant

Coordinator

UNIVERSITAT ROVIRA I VIRGILI
Net EU contribution
€ 251 971,20
Address
Carrer de escorxador
43003 Tarragona
Spain

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Region
Este Cataluña Tarragona
Activity type
Higher or Secondary Education Establishments
Links
EU contribution
No data

Participants (9)

Partners (15)

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Last update: 12 September 2022

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Permalink: https://cordis.europa.eu/project/id/101073222

European Union, 2023