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帕金森病中脑葡萄糖代谢和血流异常的脑网络标志物

Brain network markers of abnormal cerebral glucose metabolism and blood flow in Parkinson's disease.

作者信息

Peng Shichun, Eidelberg David, Ma Yilong

机构信息

Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, USA.

出版信息

Neurosci Bull. 2014 Oct;30(5):823-37. doi: 10.1007/s12264-014-1472-x. Epub 2014 Sep 28.

Abstract

Neuroimaging of cerebral glucose metabolism and blood flow is ideally suited to assay widely-distributed brain circuits as a result of local molecular events and behavioral modulation in the central nervous system. With the progress in novel analytical methodology, this endeavor has succeeded in unraveling the mechanisms underlying a wide spectrum of neurodegenerative diseases. In particular, statistical brain mapping studies have made significant strides in describing the pathophysiology of Parkinson's disease (PD) and related disorders by providing signature biomarkers to determine the systemic abnormalities in brain function and evaluate disease progression, therapeutic responses, and clinical correlates in patients. In this article, we review the relevant clinical applications in patients in relation to healthy volunteers with a focus on the generation of unique spatial covariance patterns associated with the motor and cognitive symptoms underlying PD. These characteristic biomarkers can be potentially used not only to improve patient recruitment but also to predict outcomes in clinical trials.

摘要

由于中枢神经系统中的局部分子事件和行为调节,大脑葡萄糖代谢和血流的神经成像非常适合用于分析广泛分布的脑回路。随着新型分析方法的进步,这项工作成功地揭示了多种神经退行性疾病的潜在机制。特别是,统计脑图谱研究在描述帕金森病(PD)及相关疾病的病理生理学方面取得了重大进展,通过提供标志性生物标志物来确定脑功能的系统性异常,并评估患者的疾病进展、治疗反应和临床相关性。在本文中,我们回顾了与健康志愿者相关的患者的相关临床应用,重点关注与PD潜在的运动和认知症状相关的独特空间协方差模式的生成。这些特征性生物标志物不仅有可能用于改善患者招募,还可用于预测临床试验结果。

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