Diagnostic performance and methodological heterogeneity of neuromelanin-sensitive MRI in Parkinson's disease: A systematic review and meta-analysis
Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: BACKGROUND: Parkinson's disease (PD) diagnosis remains primarily clinical and is often delayed until substantial neurodegeneration has occurred. Neuromelanin-sensitive MRI (NM-MRI) assesses the integrity of neuromelanin-rich nuclei affected in PD, the substantia nigra pars compacta (SNpc) and locus coeruleus (LC), but its diagnostic performance, technical determinants, and translational applicability remain unclear amid heterogeneity. We aimed to quantify diagnostic accuracy, determine whether performance varies across methodological approaches, and contextualise evidence from clinically relevant settings. METHODS: We systematically reviewed NM-MRI diagnostic studies through December 2025. QUADAS-2 assessed risk of bias. Sensitivity and specificity were jointly pooled using a bivariate model, and AUC using random-effects meta-analysis. Subgroup analyses and exploratory meta-regressions assessed methodological heterogeneity; broader clinical evidence was synthesised qualitatively. RESULTS: = 64.6%). No significant unadjusted differences emerged by sequence, dimensionality, segmentation, or measurement type. NM-MRI abnormalities were detectable across prodromal, early- and advanced-stage PD, although global measures showed limited discrimination between disease stages. Subregional measures captured phenotypic variation, genotype discrimination was limited, and PD-versus-ET/APS performance was promising but variable, within small, heterogeneous evidence bases. CONCLUSION: NM-MRI is a promising non-invasive imaging biomarker for PD, with strong discrimination across diverse methodological approaches. Harmonised acquisition and analysis, externally validated diagnostic thresholds, and prospective multicentre studies in clinically representative populations are needed to support future clinical implementation.
Source: NeuroImage Clinical
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,490
Funder: F. Hoffmann-La Roche
OpenAlex ID: W7223083429
