帕金森病脑萎缩进展的临床表型印记

D. Benninger, J. von Meyenburg, J. Dukart, C. Bassetti, S. Kollias, K. Iseki, Bogdan Draganski
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引用次数: 0

摘要

关于特发性帕金森病(PD)运动症状进展与大量报道的脑萎缩模式之间的联系存在很多争议。本研究的主要目的是为临床表型特征对大脑结构随时间动态变化的独特和共同贡献提供经验证据。通过纵向体素形态测量(VBM)的计算解剖学框架,我们分析了PD患者(n = 22)和健康个体(n = 21)相隔两年的行为和磁共振成像(MRI)数据。该分析显示,PD患者的灰质加速减少呈对称双半球模式,延伸至脑岛、海马旁回、内侧颞叶和楔前叶。我们观察到运动症状严重程度评分与运动区域萎缩率之间存在半球特异性相关性,PD患者的临床表型特征进一步区分了这一相关性。震颤主导型和肌动刚性PD之间的基线小脑解剖差异随着时间的推移保持稳定,可以被视为特征而不是状态相关特征。我们将观察到的进行性脑解剖变化模式解释为主要与岛区有关,岛区与基底神经节一起决定PD的运动和非运动表型。我们的研究结果为计算解剖学对PD动态变化的敏感性提供了经验证据,为建立可靠的疾病进展模型提供了额外的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clinical Phenotype Imprints on Brain Atrophy Progression in Parkinson’s Disease
There is much controversy about the link between motor symptom progression and the plethora of reported brain atrophy patterns in idiopathic Parkinson’s disease (PD). The main goal of this study is to provide empirical evidence for unique and common contributions of clinical phenotype characteristics on the dynamic changes of brain structure over time. We analyzed the behavioral and magnetic resonance imaging (MRI) data of PD patients (n = 22) and healthy individuals (n = 21) acquired two years apart through the computational anatomy framework of longitudinal voxel-based morphometry (VBM). This analysis revealed a symmetrical bi-hemispheric pattern of accelerated grey matter decrease in PD extending through the insula, parahippocampal gyrus, medial temporal lobes and the precuneus. We observed a hemisphere-specific correlation between the established scores for motor symptoms severity and the rate of atrophy within motor regions, which was further differentiated by the clinical phenotype characteristics of PD patients. Baseline cerebellum anatomy differences between the tremor-dominant and akineto-rigid PD remained stable over time and can be regarded as trait rather than state-associated features. We interpret the observed pattern of progressive brain anatomy changes as mainly linked to insular areas that determine together with basal ganglia the motor and non-motor phenotype in PD. Our findings provide empirical evidence for the sensitivity of computational anatomy to dynamic changes in PD, offering additional opportunities to establish reliable models of disease progression.
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