Parkinson’s disease (PD) is the second most common neurodegenerative disorder with an increasing prevalence that is expected to double by 2030. Differentiate disease phenotypes in PD is a crucial step for the development of disease modifying therapies, nowdays not yet available. We aim to explain phenotypic heterogeneity and pathology spreading, discriminating two PD-subtypes with the help of neuroimaging studies: brain-first-PD, originating from central nervous system and body-first-PD, from peripherical nervous structures. We will include structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), and positron emission tomography (PET). Each modality provides unique insights into the structure, function, and microstructural properties of the brain, both in healthy individuals and patients with neurodegenerative disorders. With the accumulation of large-scale, high-quality brain imaging data, efficient preprocessing using substantial computing resources is essential to enable advanced analysis techniques, such as deep learning, for a comprehensive understanding of brain organization.