ArticleScientific reports2019
Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 43 citations in OpenAlex.
- Performance of machine learning algorithms in diffusion tensor imaging of movement disorders: an exploratory meta-analysis.Biomedical engineering online · 2026Pooled it
- Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies.Cerebellum (London, England) · 2022Pooled it
- Machine Learning for the Diagnosis of Parkinson's Disease: A Review of Literature.Frontiers in aging neuroscience · 2021Pooled it
- Multiparametric MRI and imaging transcriptomics reveal molecular and cellular correlates of neurodegeneration in experimental Parkinsonism.NPJ Parkinson's disease · 2026Article
- The role of neuro-imaging in multiple system atrophy.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Precise disease heterogeneity and progression quantification in MSA and Parkinson's disease using machine learning.Scientific reports · 2026Article
- Paired regional complementarity in diffusion MRI reveals disease-specific microstructural profiles in PD, MSA, and PSP: a feasibility study.Scientific reports · 2026Article
- Altered structural connectivity in white matter lesion-induced mild cognitive impairment: a probabilistic fiber tracking and graph theory analysis.Frontiers in neural circuits · 2026Article
- Novel applications of machine learning and computational neuroscience models to neuroimaging in Parkinson's disease and related disorders.Frontiers in aging neuroscience · 2026Review
- Protein Expression of TXNIP in the Dopaminergic Neurons of Subjects with Parkinson's Disease: Evidence from a Pilot Study.Life (Basel, Switzerland) · 2025Article
- Brain structural features with functional priori to classify Parkinson's disease and multiple system atrophy using diagnostic MRI.Scientific reports · 2025Article
- Advanced Magnetic Resonance Imaging for Early Diagnosis and Monitoring of Movement Disorders.Brain sciences · 2025Review
- Sensitivity and specificity of a seed amplification assay for diagnosis of multiple system atrophy: a multicentre cohort study.The Lancet. Neurology · 2024Article
- The Impact of Artificial Intelligence in the Odyssey of Rare Diseases.Biomedicines · 2023Review
- Parallel processing relies on a distributed, low-dimensional cortico-cerebellar architecture.Network neuroscience (Cambridge, Mass.) · 2023Article
- Classification of Parkinson's disease motor phenotype: a machine learning approach.Journal of neural transmission (Vienna, Austria : 1996) · 2022Article
- Multimodal striatal neuromarkers in distinguishing parkinsonian variant of multiple system atrophy from idiopathic Parkinson's disease.CNS neuroscience & therapeutics · 2022Article
- Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review.Movement disorders : official journal of the Movement Disorder Society · 2022Review
- Multiple system atrophy.Nature reviews. Disease primers · 2022Review
- Cerebrospinal Fluid Metabolome in Parkinson's Disease and Multiple System Atrophy.International journal of molecular sciences · 2022Review
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson's disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.
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