Advanced Cognitive Patterns in Multiple System Atrophy Compared to Parkinson's Disease: An Individual Diffusion Tensor Imaging Study

Huize Pang; Ziyang Yu; Hongmei Yu; Xiaolu Li; Shuting Bu; Yu Liu; Juzhou Wang; Mengwan Zhao; Guoguang Fan

doi:10.1016/j.acra.2024.01.006

Advanced Cognitive Patterns in Multiple System Atrophy Compared to Parkinson's Disease: An Individual Diffusion Tensor Imaging Study

Acad Radiol. 2024 Jan 13:S1076-6332(24)00006-0. doi: 10.1016/j.acra.2024.01.006. Online ahead of print.

Authors

Huize Pang¹, Ziyang Yu¹, Hongmei Yu², Xiaolu Li¹, Shuting Bu¹, Yu Liu¹, Juzhou Wang¹, Mengwan Zhao¹, Guoguang Fan¹

Affiliations

¹ Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China (H.P., Z.Y., X.L., S.B., Y.L., J.W., M.Z., G.F.).
² Department of Neurology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China (H.Y.).

PMID: 38220569
DOI: 10.1016/j.acra.2024.01.006

Abstract

Rationale and objectives: Although both Multiple system atrophy (MSA) and Parkinson's disease (PD) belong to alpha-synucleinopathy, they have divergent clinical courses and prognoses. The degeneration of white matter has a considerable impact on cognitive performance, yet it is uncertain how PD and MSA affect its functioning in a similar or different manner.

Methods: In this study, a total of 116 individuals (37 PD with mild cognitive impairment (PD-MCI), 37 MSA (parkinsonian variant) with mild cognitive impairment (MSA-MCI), and 42 healthy controls) underwent diffusion tensor imaging (DTI) and cognitive assessment. Utilizing probabilistic fiber tracking, association fibers, projection fibers, and thalamic fibers were reconstructed. Subsequently, regression, support vector machine, and SHAP (Shapley Addictive exPlanations) analyzes were conducted to evaluate the association between microstructural diffusion metrics and multiple cognitive domains, thus determining the white matter predictors of MCI.

Results: MSA-MCI patients exhibited distinct white matter impairment extending to the middle cerebellar peduncle, corticospinal tract, and cingulum bundle. Furthermore, the fractional anisotropy (FA) and mean diffusivity (MD)values of the right anterior thalamic radiation were significantly associated with global efficiency (FA: B = 0.69, P < 0.001, VIF = 1.31; MD: B = -0.53, P = 0.02, VIF = 2.50). The diffusion metrics of white matter between PD-MCI and MSA-MCI proved to be an effective predictor of the MCI, with an accuracy of 0.73 (P < 0.01), and the most predictive factor being the MD of the anterior thalamic radiation.

Conclusions: Our results demonstrated that MSA-MCI had a more noticeable deterioration in white matter, which potentially linked to various cognitive domain connections. Diffusion MRI could be a useful tool in comprehending the neurological basis of cognitive impairment in Parkinsonian disorders.

Keywords: Diffusion tensor imaging; Mild cognitive impairment; Multiple system atrophy; Parkinson’s disease.