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Updated: Jul 12, 2025

Author Spotlight: Establishing a New Fluorescence-Based Protocol for In Vivo Mitochondrial Morphology Analysis in Parkinson's Disease
Published on: June 23, 2023
Structural and Functional Alterations of Motor-Thalamus in Different Motor Subtype of Parkinson's Disease: An
Shuting Bu1, Huize Pang1, Xiaolu Li1
1Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China (S.B., H.P., X.L., M.Z., J.W., Y.L., G.F.).
Rationale And Objectives:
This study aimed to investigate the structural and functional alterations occurring within bilateral premotor thalamus (mPMtha) in motor subtypes of Parkinson's disease (PD).
Materials And Methods:
Sixty-one individuals with instability and gait difficulty (PIGD) subtype, 60 individuals with tremor-dominant (TD) subtype and 66 healthy controls (HCs) participated in the study. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and 3D T1-weighted (3DT1) scans. Functional connectivity (FC) analysis and Voxel-based morphometry (VBM) analysis were performed to evaluate the function and volume of mPMtha. Additionally, correlations between motor performance and FC values, volumes were examined separately. Support vector machine (SVM) model based on FC values and thalamic volumes was conducted to assist in the clinical diagnosis of PD motor subtype.
Results:
Compared to HCs and PIGD, TD subtype showed increased FC between the bilateral mPMtha and left middle occipital gyrus, left inferior parietal lobule (IPL). While PIGD subtype demonstrated decreased FC between right mPMtha and precentral gyrus (PreCG), supramarginal, IPL and superior parietal lobule. FC of bilateral mPMtha with the identified regions were significantly correlated with motor performance scores in PD patients. The SVM classification based on FC values demonstrated a high level of efficiency (AUC=0.874). The volumes of the bilateral mPMtha were indifferent among three groups.
Conclusion:
We noted distinct FC alterations of mPMtha in TD and PIGD subtypes, and these changes were correlated with motor performance. Furthermore, the machine learning based on statistically significant FC might be served as an alternative approach for automatically classifying PD motor subtypes individually.
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