Differentiation of Cerebellum-Type and Parkinson-Type of Multiple System Atrophy by Using Multimodal MRI Parameters.

Bin Cui,Weimin Zheng,Zhigang Chen,Zhiqun Wang,Shan Ren

doi:10.3389/fnagi.2021.687649

Abstract

Recent studies have demonstrated the structural and functional changes in patients with multiple system atrophy (MSA). However, little is known about the different parameter changes of the most vulnerable regions in different types of MSA. In this study, we collected resting-state structure, perfusion, and patients with functional magnetic resonance imaging (fMRI) data of cerebellum-type of MSA (MSA-c) and Parkinson-type of MSA (MSA-p). First, by simultaneously using voxel-based morphology (VBM), arterial spin labeling (ASL), and amplitude of low-frequency fluctuation (ALFF), we analyzed the whole brain differences of structure, perfusion, and functional activation between patients with MSA-c and MSA-p. Second, we explored the relationships among structure, perfusion, function, and the clinical variables in patients with MSA. Finally, we extracted the MRI parameters of a specific region to separate the two groups and search for a sensitive imaging biomarker. As a result, compared with patients with MSA-p type, patients with MSA-c type showed decreased structure atrophy in several cerebella and vermis subregions, reduced perfusion in bilateral cerebellum_4_5 and vermis_4_5, and an decreased ALFF values in the right lingual gyrus (LG) and fusiform (FFG). Subsequent analyses revealed the close correlations among structure, perfusion, function, and clinical variables in both MSA-c and MSA-p. Finally, the receiver operating characteristic (ROC) analysis showed that the regional cerebral blood flow (rCBF) of bilateral cerebellum_4_5/vermis_4_5 could differentiate the two groups at a relatively high accuracy, yielding the sensitivity of 100%, specificity of 79.2%, and the area under the curve (AUC) value of 0.936. These findings have important implications for understanding the underlying neurobiology of different types of MSA and added the new evidence for the disrupted rCBF, structure, and function of MSA, which may provide the potential biomarker for accurately detecting different types of patients with MSA and new ideas for the treatment of different types of MSA in the future.

Highlights

Multiple system atrophy (MSA) is a progressive neurodegenerative disorder, pathologically characterized by deposition of alpha synuclein-positive glial cytoplasmic inclusions (GCIs) in several specific regions including the striatum, cerebellum, and olivopontine structures (Brettschneider et al, 2017; Krismer et al, 2019)
79.2%/83.3%/79.2%, the area under the curve (AUC) was 0.880/0.864/0.833, FIGURE 4 | Relationships between clinical variables and multimode MRI parameters in patients with MSAc and multiple system atrophy (MSA)-p type, respectively. (A) In the MSA-c type group, we found significant negative correlations between the Unified Multiple System Atrophy Rating Scale (UMSARS) -II scores and structure changes. (B) In the MSA-p type group, we found a negative correlation between the UMSARS -I scores and white matter (WM) changes
By applying voxel-based morphology (VBM), Arterial spin labeling (ASL), and amplitude of low-frequency fluctuation (ALFF) analysis to the resting state data acquired from patients with MSA-c and MSA-p, we observed significant structure atrophy in several cerebellum and vermis subregions decreased perfusion in bilateral cerebellum_4_5/vermis_4_5, and decreased ALFF values in the right lingual gyrus (LG)/FFG in patients with MSA-c type, relative to patients with MSA-p type

Summary

Introduction

Multiple system atrophy (MSA) is a progressive neurodegenerative disorder, pathologically characterized by deposition of alpha synuclein-positive glial cytoplasmic inclusions (GCIs) in several specific regions including the striatum, cerebellum, and olivopontine structures (Brettschneider et al, 2017; Krismer et al, 2019). One of the previous studies revealed the decreased rCBF in several cerebellum subregions in patients with MSA-c type (Zheng et al, 2019). Another ASL study focused on differentiation of the Parkinson’s disease (PD) and MSA, the authors performed some perfusion comparisons between patients, with MSA-c and MSA-p they did not further extract the imaging biomarkers to classify the different types of MSA (Erro et al, 2020)

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