Imaging biomarkers in Parkinson's disease and movement disorders: emerging insights from multimodal neuroimaging

This editorial introduces a special issue detailing the rapid evolution of multimodal neuroimaging biomarkers for Parkinson's disease (PD) and related movement disorders. Advances in MRI, including quantitative susceptibility mapping for iron dysregulation, neuromelanin-sensitive MRI, diffusion tensor imaging for free water quantification, metabolic spectroscopy, and functional network mapping, are reviewed. The integrated application of these modalities demonstrates that PD neurodegeneration cannot be captured by a single biomarker. Instead, these complementary tools define overlapping biological dimensions of the disease, spanning dopaminergic neuronal integrity, microstructural injury, glymphatic impairment, vascular abnormalities, and large-scale network reorganization. Furthermore, the integration of artificial intelligence and machine learning allows for the extraction of multidimensional patterns, improving the differential diagnosis between PD and atypical parkinsonian syndromes like multiple system atrophy and progressive supranuclear palsy. We conclude that while these multimodal biomarkers offer unprecedented mechanistic insights into disease progression and therapeutic response, their ultimate value depends on successful clinical translation. Moving forward, it would be essential for the field to prioritize standardized acquisition protocols, automated post-processing pipelines, and accessible reporting frameworks to implement these powerful research tools into routine clinical environments.