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SYNPARK

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Cerrado

Multimodal imaging in parkinsonisms from the molecular synaptic pruning to the...

Multimodal imaging in parkinsonisms from the molecular synaptic pruning to the whole brain connectomics Neurodegenerative diseases affect more than 6 million people in Europe, and its prevalence is growing as population ages, hence it is a timeliness health challenge we are facing as a society. Parkinsonism is the 2nd most prevalent... ver más

31/08/2023

232K€

Presupuesto del proyecto: 232K€

Líder del proyecto

UNIVERSIDAD DE BARCELONA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 327

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-08-31

MSCA-IF-2019: Individual Fellowships

I+D

Cerrada hace 5 años

0% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

232.50K€ | Lider

CAMH

152.03K€ | Participante

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Duración del proyecto: 41 meses Fecha Inicio: 2020-03-31
Fecha Fin: 2023-08-31

Líder del proyecto

UNIVERSIDAD DE BARCELONA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 327

Presupuesto del proyecto 232K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Neurodegenerative diseases affect more than 6 million people in Europe, and its prevalence is growing as population ages, hence it is a timeliness health challenge we are facing as a society. Parkinsonism is the 2nd most prevalent neurodegenerative form, being Parkinson’s disease (PD) the most frequent, whereas 20% of the patients are diagnosed with atypical parkinsonisms (AP). Despite presenting some clinical overlap, AP tends to be more therapy-resistant and have faster degeneration rates than PD. SYNPARK is an interdisciplinary project that will investigate the discriminative power of different imaging markers’ modalities in parkinsonisms. Improving diagnostic accuracy is crucial as disease-modifying therapies are becoming available for PD. For this challenge, I propose a multidisciplinary approach: from the in-vivo synaptic molecular brain assessment (using positron emission tomography, PET), the whole-brain connectomics organisation (using magnetic resonance imaging, MRI) to the clinics. I will conduct the outgoing phase in one of the world’s PET leading centres in Toronto to test the clinical validity of a new generation PET tracer in AP/PD. My host return institution (Barcelona) has pioneered the research on machine learning (ML) techniques that are revolutionising the medical sciences field to improve parkinsonisms’ differential diagnosis at the single-patient level by means of whole-brain MRI connectomics information. My current expertise and the proposed ambitious training objectives will position me at the forefront of this exciting new avenue in medical sciences and will enhance my professional independence for research leadership. Overall, the synergies established between these two leading centres are expected to have a tremendous impact on the understanding of AP/PD brain pathophysiology and its diagnostic accuracy, and ultimately enhancing a revolution in personalised medicine, a futuristic therapy that is increasingly becoming a reality.

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