This systematic review and meta-analysis synthesized evidence of glymphatic dysfunction in Parkinson’s disease (PD) and related Parkinsonian syndromes using the diffusion tensor imaging along the perivascular space (DTI-ALPS) index. Following the PRISMA 2020 guidelines, 28 studies published up to May 12, 2025, were included. The primary meta-analysis of 21 studies (1678 patients with PD and 1088 HCs) demonstrated a significant reduction in the DTI-ALPS index in patients with PD (Cohen’s d = −0.57; 95% CI: −0.67 to −0.47; p < 0.001), indicating moderate glymphatic dysfunction. This impairment was significantly associated with clinical progression, including longer disease duration (β = −0.08, p = 0.005) and higher Hoehn and Yahr (H-Y) stages (β = −0.18, p = 0.057). This association was particularly strong in patients with early-stage PD (H-Y < 2.5). Phenotypic analyses revealed a gradient of dysfunction, with the most severe impairment found in patients with PD with dementia (Glass’s Δ = −1.04) and atypical Parkinsonian syndromes (Δ = −1.01). Technical subgroup analyses showed consistent findings, with region-of-interest size significantly moderating effect size (p = 0.04). The methodological quality of the included studies was high, with no evidence of publication bias. The methodological quality was high, with no evidence of publication bias (p ≥ 0.88). These findings underscore the progressive glymphatic decline with PD severity and duration, independent of age or cognition, and highlight distinct impairment patterns across different clinical phenotypes.
Magnetic resonance imaging (MRI) techniques, such as quantitative susceptibility mapping (QSM) and susceptibility-weighted imaging (SWI), can detect iron deposition in the brain. Iron accumulation in the putamen (PUT) can contribute to the pathogenesis of Parkinson's disease (PD) and atypical Parkinsonian disorders. This systematic review aimed to synthesize evidence on iron deposition in the PUT assessed by MRI susceptibility techniques in PD and Parkinsonism syndromes. The PubMed and Scopus databases were searched for relevant studies. Thirty-four studies from January 2007 to October 2023 that used QSM, SWI, or other MRI susceptibility methods to measure putaminal iron in PD, progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and healthy controls (HCs) were included. Most studies have found increased putaminal iron levels in PD patients versus HCs based on higher quantitative susceptibility. Putaminal iron accumulation correlates with worse motor scores and cognitive decline in patients with PD. Evidence regarding differences in susceptibility between PD and atypical Parkinsonism is emerging, with several studies showing greater putaminal iron deposition in PSP and MSA than in PD patients. Alterations in putaminal iron levels help to distinguish these disorders from PD. Increased putaminal iron levels appear to be associated with increased disease severity and progression. Thus, magnetic susceptibility MRI techniques can detect abnormal iron accumulation in the PUT of patients with Parkinsonism. Moreover, quantifying putaminal susceptibility may serve as an MRI biomarker to monitor motor and cognitive changes in PD and aid in the differential diagnosis of Parkinsonian disorders.
Introduction: Alzheimer’s disease (AD), characterized by distinctive pathologies such as amyloid-β plaques and tau tangles, also involves deregulation of iron homeostasis, which may accelerate neurodegeneration. This meta-analysis evaluated the use of quantitative susceptibility mapping (QSM) to detect iron accumulation in the deep gray matter (DGM) of the basal ganglia in AD, contributing to a better understanding of AD progression, and potentially leading to new diagnostic and therapeutic approaches.Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the PubMed, Scopus, Web of Sciences, and Google Scholar databases up to October 2023 for studies employing QSM in AD research. Eligibility criteria were based on the PECO framework, and we included studies assessing alterations in magnetic susceptibility indicative of iron accumulation in the DGM of patients with AD. After initial screening and quality assessment using the Newcastle-Ottawa Scale, a meta-analysis was conducted to compare iron levels between patients with AD and healthy controls (HCs) using a random-effects model.Results: The meta-analysis included nine studies comprising 267 patients with AD and 272 HCs. There were significantly higher QSM values, indicating greater iron deposition, in the putamen (standardized mean difference (SMD) = 1.23; 95% CI: 0.62 to 1.84; p = 0.00), globus pallidus (SMD = 0.79; 95% CI: 0.07 to 1.52; p = 0.03), and caudate nucleus (SMD = 0.72; 95% CI: 0.39 to 1.06; p = 0.00) of AD patients compared to HCs. However, no significant differences were found in the thalamus (SMD = 1.00; 95% CI: −0.42 to 2.43; p = 0.17). The sensitivity analysis indicated that no single study impacted the overall results. Age was identified as a major contributor to heterogeneity across all basal ganglia nuclei in subgroup analysis. Older age (>69 years) and lower male percentage (≤30%) were associated with greater putamen iron increase in patients with AD.Conclusion: The study suggests that excessive iron deposition is linked to the basal ganglia in AD, especially the putamen. The study underscores the complex nature of AD pathology and the accumulation of iron, influenced by age, sex, and regional differences, necessitating further research for a comprehensive understanding.
Motor neuron diseases (MNDs) like amyotrophic lateral sclerosis (ALS) are progressive neurodegenerative disorders affecting upper and lower motor neurons (UMN and LMN). Magnetic resonance imaging (MRI) often reveals a “motor band sign” (MBS) of hypointensity along the precentral gyri in ALS, considered a radiologic hallmark. This review comprehensively summarizes the literature on MBS in ALS and related MNDs using multiple MRI techniques. A systematic search was conducted in the PubMed and Scopus databases to identify relevant studies on MBS in MNDs published until August 2023. Twelve studies were included. Most patients had UMN involvement at the onset. MBS was correlated with UMN impairment severity. Susceptibility-weighted imaging (SWI) detected MBS in the majority of MND patients. The use of SWI could be particularly useful in detecting MBS, and it should be considered as part of the routine clinical MRI protocols. Recent studies suggest that hypointensity and atrophy of the primary motor cortex (M1) and nearby regions can be used as MRI markers of UMN impairment in MNDs. Other MRI techniques like T2-weighted (T2-w), T2-w, and fluid-attenuated inversion recovery (FLAIR) also showed characteristic changes. Furthermore, quantitative susceptibility mapping (QSM) is an advanced MRI technique that allows sensitive quantification of iron deposition and has shown promise for accurately detecting MBS in MNDs. The findings suggest that MR neuroimaging techniques can provide valuable insights into the pathophysiology of MND and can be used to detect biomarkers such as MBS. The review demonstrates that advanced MRI techniques can detect cortical and white matter changes reflecting upper motor neuron degeneration in MNDs like ALS. To find out how sensitive and suggestive the MBS is in MNDs and neurodegenerative movement disorders and how well it works as a prognostic indicator, we will need to do more research that combines comprehensive prospective and longitudinal research.
About Me
Dr. Sana Mohammadi is a medical doctor and a radiology and neuroimaging researcher with a proven publication record exploring MRI biomarkers in neurological conditions. Her expertise lies in advanced quantitative MRI techniques and physics. She is proficient in advanced neuroimaging analysis, integrating Python and MATLAB with software such as Freesurfer, FSL, and SPM. Her research interests include Volumetric Imaging, fMRI, Diffusion MRI (DTI/DKI/NODDI), Quantitative Susceptibility Imaging (QSM), and Magnetic Resonance Spectroscopy (MRS).
Dr. Sana Mohammadi is a medical doctor and a radiology and neuroimaging researcher with a proven publication record exploring MRI biomarkers in neurological conditions. Her expertise lies in advanced quantitative MRI techniques and physics. She is proficient in advanced neuroimaging analysis, integrating Python and MATLAB with software such as Freesurfer, FSL, and SPM. Her research interests include Volumetric Imaging, fMRI, Diffusion MRI (DTI/DKI/NODDI), Quantitative Susceptibility Imaging (QSM), and Magnetic Resonance Spectroscopy (MRS).