Project description
Imaging technology to improve diagnostic of Parkinsonism
Parkinsonism is the second most prevalent neurodegenerative disorder after Parkinson’s disease (PD), and 20 % of patients are diagnosed with atypical parkinsonisms (AP). AP tends to be therapy-resistant and presents a faster degeneration rate than PD. The EU-funded SYNPARK project is an interdisciplinary action that will investigate the value of the different imaging markers' modalities in various parkinsonism forms. Improving diagnostic accuracy is important now, when disease-modifying therapies are becoming available for PD. The research involves a multidisciplinary approach of the in vivo synaptic molecular brain assessment using positron emission tomography (PET), the whole-brain connectomics organisation using magnetic resonance imaging and the clinical validation of a new generation PET tracer in AP/PD.
Objective
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.
Fields of science
Not validated
Not validated
- medical and health sciencesbasic medicinephysiologypathophysiology
- medical and health scienceshealth sciencespersonalized medicine
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
- medical and health sciencesbasic medicineneurologyparkinson
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
08007 Barcelona
Spain