Project description
New model for non-invasive breast cancer diagnosis
Breast cancer patients often undergo biopsies, which may lack precision, are costly, painful, and require time-consuming analysis. Ultrasound B-mode imaging is a low-cost, non-invasive alternative. Researchers at the Institute of Physics for Medicine in Paris have developed quantitative ultrasound techniques to measure tissue stiffness, fibre organisation, and vascular mapping (key factors in understanding tumour development). The ERC-funded MUSCAD project aims to leverage machine learning to analyse multiparametric maps generated by innovative ultrafast ultrasound techniques for non-invasive breast cancer diagnosis. The project will integrate these techniques into a unified framework, compile a large clinical dataset, and develop a predictive malignancy model to assess tumour characteristics. This could enable virtual biopsies, improving diagnostic accuracy and enhancing patient comfort.
Objective
Tumour development follows a diversity of complementary biological pathways, including the modification of the tissue structure and vascularization, which are not currently captured by imaging techniques in the clinic. Breast cancer patients undergo a series of imaging sessions using complementary modalities, including ionizing mammographies. In many cases, this imaging is not precise enough for a diagnosis, so that tissue samples in the form of biopsies are used to further characterize the tumour and determine the appropriate treatment. Beyond the pain and stress associated with biopsies, this complex process is costly and time consuming, and delays the time to diagnosis.
Ultrasound B-mode imaging is largely used in the diagnostic process of breast cancer, in part because it is low cost, portable and largely available, as well as non-ionizing and non-invasive. Our laboratory, Institute Physics for Medicine Paris has recently developed several quantitative techniques allowing for the measurement of tissue stiffness, fiber organization, and vascular mapping, all relevant to tumour development. In this project, I propose a new approach to diagnosing breast cancer non-invasively by applying machine learning analysis to rich volumetric multiparametric maps of complementary tumour aspects, obtained using these innovative ultrafast ultrasound techniques. The project will tackle the technological challenge of integrating these techniques into a common acquisition and analysis framework, and include the collection of a large clinical dataset and the development and validation of a predictive malignancy model informing on tumour characteristics for the diagnosis. This approach will open the door to fully virtual biopsies, impacting society on a large scale in terms of cost, diagnostic efficacy, and patient comfort.
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.
- engineering and technology materials engineering fibers
- medical and health sciences clinical medicine oncology breast cancer
- natural sciences physical sciences acoustics ultrasound
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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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.
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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-STG
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75654 PARIS
France
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