Characterizing microstructural patterns within the cortico-striato-thalamo-cortical circuit in Parkinson's disease

IF 5.3 2区 医学 Q1 CLINICAL NEUROLOGY
Song'’an Shang , Lijuan Wang , Jun Yao , Xiang Lv , Yao Xu , Weiqiang Dou , Hongying Zhang , Jing Ye , Yu-Chen Chen
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引用次数: 0

Abstract

Purpose

Parkinson's disease (PD) involves pathological alterations that include cortical impairments at levels of region and network. However, its microstructural abnormalities remain to be further elucidated via an appropriate diffusion neuroimaging approach. This study aimed to comprehensively demonstrate the microstructural patterns of PD as mapped by diffusion kurtosis imaging (DKI).

Methods

The microstructure of grey matter in both the PD group and the matched healthy control group was quantified by a DKI metric (mean kurtosis). The intergroup difference and classification performance of global microstructural complexity were analyzed in a voxelwise manner and via a machine learning approach, respectively. The patterns of information flows were explored in terms of structural connectivity, network covariance and modular connectivity.

Results

Patients with PD exhibited global microstructural impairments that served as an efficient diagnostic indicator. Disrupted structural connections between the striatum and cortices as well as between the thalamus and cortices were widely distributed in the PD group. Aberrant covariance of the striatocortical circuitry and thalamocortical circuitry was observed in patients with PD, who also showed disrupted modular connectivity within the striatum and thalamus as well as across structures of the cortex, striatum and thalamus.

Conclusion

These findings verified the potential clinical application of DKI for the exploration of microstructural patterns in PD, contributing complementary imaging features that offer a deeper insight into the neurodegenerative process.

描述帕金森病患者皮质-纹状体-眼球-皮质回路的微结构模式。
目的:帕金森病(PD)的病理改变包括皮质在区域和网络层面的损伤。然而,其微观结构异常仍有待通过适当的弥散神经影像学方法进一步阐明。本研究旨在通过弥散峰度成像(DKI)全面展示帕金森病的微观结构模式:方法:通过 DKI 指标(平均峰度)对帕金森病组和匹配的健康对照组的灰质微观结构进行量化。分别以象素为单位和通过机器学习方法分析了组间差异和全局微结构复杂性的分类性能。从结构连通性、网络协方差和模块连通性方面探讨了信息流的模式:结果:帕金森病患者表现出整体微结构损伤,这是一个有效的诊断指标。纹状体与大脑皮层之间以及丘脑与大脑皮层之间的结构连接紊乱在帕金森病组中广泛分布。在帕金森氏症患者中观察到纹状体皮层回路和丘脑皮层回路的异常共变,他们还表现出纹状体和丘脑内部以及皮层、纹状体和丘脑之间的模块连接紊乱:这些研究结果验证了 DKI 在探索帕金森病微观结构模式方面的潜在临床应用价值,其补充性成像特征有助于深入了解神经退行性过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
12.00
自引率
1.80%
发文量
153
审稿时长
56 days
期刊介绍: Progress in Neuro-Psychopharmacology & Biological Psychiatry is an international and multidisciplinary journal which aims to ensure the rapid publication of authoritative reviews and research papers dealing with experimental and clinical aspects of neuro-psychopharmacology and biological psychiatry. Issues of the journal are regularly devoted wholly in or in part to a topical subject. Progress in Neuro-Psychopharmacology & Biological Psychiatry does not publish work on the actions of biological extracts unless the pharmacological active molecular substrate and/or specific receptor binding properties of the extract compounds are elucidated.
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