A recent study published in Academic Radiology unveils compelling findings in the realm of neurodegenerative disorders, particularly Multiple System Atrophy (MSA) and Parkinson’s Disease (PD). This groundbreaking research provides deeper insights into how these two forms of alpha-synucleinopathy, although related, diverge in their impact on the brain’s white matter and, consequentially, cognitive function. The full text of the study, titled “Advanced Cognitive Patterns in Multiple System Atrophy Compared to Parkinson’s Disease: An Individual Diffusion Tensor Imaging Study” is available at DOI: 10.1016/j.acra.2024.01.006.


MSA and PD are progressive neurodegenerative diseases characterized by the abnormal accumulation of alpha-synuclein protein within the brain. Both disorders share some motor symptoms, but they have vastly different clinical courses and prognoses. Cognitive impairment, a well-recognized feature of PD, has also been increasingly documented in patients with MSA. However, the extent and pattern of cognitive decline in MSA have remained less clear, with research being limited and often inconclusive.

The Study

Conducted by a team of researchers from the Department of Radiology, and the Department of Neurology at the First Affiliated Hospital of China Medical University, the study aimed to uncover the cognitive and neuroimaging differences between patients with MSA and PD.

Participants comprised 37 individuals with PD with mild cognitive impairment (PD-MCI), 37 with MSA (parkinsonian variant) with mild cognitive impairment (MSA-MCI), and 42 healthy control subjects. Each participant underwent thorough cognitive assessments alongside Diffusion Tensor Imaging (DTI), a magnetic resonance imaging (MRI) technique that maps the diffusion of water molecules along the brain’s white matter fibers, effectively providing a detailed picture of white matter integrity and connectivity.

Results and Implications

Results from the data analysis depict a more significant decline in cognitive domains among MSA-MCI individuals, notably in global efficiency. This deterioration is markedly linked to distinct impairments in key brain regions, including the middle cerebellar peduncle, the corticospinal tract, and the cingulum bundle. The study’s analysis of fractional anisotropy (FA) and mean diffusivity (MD)—key metrics derived from DTI—showed significant associations with different cognitive functions. Particularly, FA and MD values in the right anterior thalamic radiation were identified as a robust predictor of cognitive performance.

Machine learning approaches, incorporating regression, support vector machine, and SHAP (Shapley Additive Explanations) analyses, were utilized to tease out the complex relationship between microstructural diffusion metrics and cognitive domains. This advanced analytical process determined to be impactful white matter predictors of mild cognitive impairment (MCI) with substantial accuracy.


1. Multiple System Atrophy
2. Parkinson’s Disease
3. Cognitive Impairment
4. Diffusion Tensor Imaging
5. Neurodegenerative Disorders

The team from China Medical University not only established differences in cognitive decline patterns but also validated the application of diffusion MRI as a potent tool in understanding the neurological underpinnings of cognitive impairment within Parkinsonian disorders. These findings pave the way for improved diagnostic accuracy and the potential for more targeted therapeutic strategies for patients with MSA and PD.

Further Considerations

The implications of this study extend beyond diagnostics into the realm of personalized medicine and patient care. Understanding the differential impacts on cognitive domains helps clinicians tailor cognitive therapies and lifestyle interventions to mitigate the specific impairments associated with each disorder. Furthermore, by establishing a benchmark for cognitive decline in MSA and PD, future research can build on this knowledge to explore disease progression and response to treatment.

Limitations and Future Research

While the study’s findings are robust, the authors acknowledge the need for further research, including larger sample sizes and longitudinal analyses, to confirm and extend these insights. They also emphasize the necessity of exploring therapeutic interventions that may slow, halt, or reverse the progression of white matter degeneration and cognitive decline in these patient populations.


The research conducted by Pang Huize and colleagues represents a significant stride in understanding and distinguishing the cognitive patterns within Parkinsonian syndromes. Such studies are invaluable in enhancing the clinical approach to MSA and PD, ultimately contributing to better patient outcomes.

The team’s dedication to exploring the neural basis of cognitive impairment in neurodegenerative disorders promises to inform clinical practices and stimulate further research in this critical area of neuroscience and clinical neurology.


1. Pang Huize H., Yu Ziyang Z., Yu Hongmei H., Li Xiaolu X., Bu Shuting S., Liu Yu Y., Wang Juzhou J., Zhao Mengwan M., Fan Guoguang G. Advanced Cognitive Patterns in Multiple System Atrophy Compared to Parkinson’s Disease: An Individual Diffusion Tensor Imaging Study. Academic Radiology, 2024, 10.1016/j.acra.2024.01.006.
2. Salat D. et al. (2017). ‘White Matter and Cognitive Decline in Aging: A Focus on Processing Speed and Variability’. Journal of the International Neuropsychological Society.
3. Planetta P. J., et al. (2016). ‘Distinct functional and macrostructural brain changes in Parkinson’s disease and multiple system atrophy’. Human Brain Mapping.
4. Fanciulli A., & Wenning G. K. (2015). ‘Multiple-system atrophy’. New England Journal of Medicine.
5. Zeighami Y., et al. (2015). ‘Network structure of brain atrophy in de novo Parkinson’s disease’. eLife.