Objective
Alterations in the intrinsic physical tissue parameters measured with magnetic resonance imaging (MRI), such as of longitudinal (T1) and transverse (T2) relaxation times, have been implicated in major neurological conditions. Although these differences have been noted as useful signs in image contrasts, parameter quantification has not been exploited as a marker for disease stage or for monitoring treatment efficacy.
Previous attempts to perform quantitative MRI protocols have suffered from sensitivity to system imperfections as well as infeasible, long acquisition times. Recently, a new approach called MR fingerprinting (MRF) has been developed for the estimation of multiple parameters at once, featuring a new dedicated acquisition strategy. The method has shown great promise as data can be acquired in clinically acceptable time, is relatively insensitive to system imperfections and has high accuracy. To date, only two dimensional datasets using a single acquisition strategy (balanced steady state free precession bSSFP) have been explored. Further, this was using a rather slow reconstruction algorithm at 1.5T. In addition, the technique has not been yet applied outside healthy volunteer groups.
In this project we aim to develop a 3D MRF acquisition for imaging the whole brain with optimized acquisition trajectories. We will compare different acquisition strategies, including strategies sensitive to magnetic susceptibility in the brain, previously unexplored. The sequence parameters will be optimized using a dedicated novel genetic algorithm. An accelerated reconstruction software using a novel algorithm will be developed using graphics processing units. Initial data will be acquired with new protocols at 7T and at 1.5T. Statistical parametric maps will be used to investigate group differences. The close interaction with clinical facilities will facilitate the prompt application to patient groups, including neurological, psychiatric and pediatric patients.
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.
- natural sciences computer and information sciences software
- engineering and technology medical engineering diagnostic imaging magnetic resonance imaging
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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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
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.
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.
Funding Scheme
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.
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.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2014
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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.
56128 Calambrone Pisa
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.