CMRPredict
Financiado
Patient specific magnetic resonance image guided biomechanical modelling of the...
Patient specific magnetic resonance image guided biomechanical modelling of the heart A novel tool towards personalized medicine in heart failure
Heart failure (HF) is a progressing disease currently affecting 2% of the population in the developed world with a mortality rate of 50% within the first five years. While HF with reduced ejection fraction, primarily associated wi...
Heart failure (HF) is a progressing disease currently affecting 2% of the population in the developed world with a mortality rate of 50% within the first five years. While HF with reduced ejection fraction, primarily associated with myocardial infarction, can be detected with sufficient accuracy, HF with preserved ejection fraction is far more difficult to diagnose. Accordingly, there is an urgent need to better diagnose these patients to ultimately guide and improve treatment. Among the clinical imaging modalities, Cardiovascular Magnetic Resonance (CMR) is the gold standard for assessing cardiac mass and ejection fraction, and is capable to assess local cardiac mechanics and tissue properties. Beyond these established methods, cardiac diffusion tensor imaging has emerged as a new tool to enable insights into the microscopic morphology of the beating heart. Unfortunately, due to scan time limitations during clinical routine, compromises in spatial resolution and coverage have to be made. To overcome practical limitations of clinical in vivo CMR imaging and to enable prediction of disease progression for individual patients, additional tools are required. To this end, biomechanical models have attracted considerable attention. Once adapted sufficiently to in-vivo imaging, these models promise patient-specific insights into causes and progression of disease and, help guiding treatment. It is the objective of the present fellowship proposal to significantly advance patient-specific, image-guided modelling of HF by incorporating the most recent developments in both CMR imaging and biophysical modelling. The proposed framework will address limitations of current approaches, which impose generic assumptions about cardiac tissue properties and structure. With recent innovations in CMR imaging, as developed by the applicant, data on local changes of myocardial microstructure will be obtained to achieve the next level of diagnostic and predictive cardiac modelling of HF.
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Duración del proyecto: 41 meses
Fecha Inicio: 2017-03-17
Fecha Fin: 2020-08-31
Fecha Fin: 2020-08-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2020-08-31
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
MSCA-IF-2016:
Individual Fellowships
Cerrada
hace 8 años
Presupuesto
El presupuesto total del proyecto asciende a
248K€
Líder del proyecto
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
No se ha especificado una descripción o un objeto social para esta compañía.
282.16K€ |
Participante