Subthalamic Deep Brain Stimulation: Mapping Non-Motor Outcomes to Structural Connections

IF 3.5 2区 医学 Q1 NEUROIMAGING
Garance M. Meyer, Ilkem Aysu Sahin, Barbara Hollunder, Konstantin Butenko, Nanditha Rajamani, Clemens Neudorfer, Lauren A. Hart, Jan Niklas Petry-Schmelzer, Haidar S. Dafsari, Michael T. Barbe, Veerle Visser-Vandewalle, Philip E. Mosley, Andreas Horn
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Abstract

In Parkinson's Disease (PD), deep brain stimulation of the subthalamic nucleus (STN-DBS) reliably improves motor symptoms, and the circuits mediating these effects have largely been identified. However, non-motor outcomes are more variable, and it remains unclear which specific brain circuits need to be modulated or avoided to improve them. Since numerous non-motor symptoms potentially respond to DBS, it is challenging to independently identify the circuits mediating each one of them. Data compression algorithms such as principal component analysis (PCA) may provide a powerful alternative. This study aimed at providing a proof of concept for this approach by mapping changes along extensive score batteries to a few anatomical fiber bundles and, in turn, estimating changes in individual scores based on stimulation of these tracts. Retrospective data from 56 patients with PD and bilateral STN-DBS was included. The patients had undergone comprehensive clinical assessments covering changes in appetitive behaviors, mood, anxiety, impulsivity, cognition, and empathy. PCA was implemented to identify the main dimensions of neuropsychiatric and neuropsychological outcomes. Using DBS fiber filtering, we identified the structural connections whose stimulation was associated with change along these dimensions. Then, estimates of individual symptom outcomes were derived based on the stimulation of these connections by inverting the PCA. Finally, changes along a specific non-motor score were estimated in an independent validation dataset (N = 68) using the tract model. Four principal components were retained, which could be interpreted to reflect (i) general non-motor improvement; (ii) improvement of mood and cognition and worsening of trait impulsivity; (iii) improvement of cognition; and (iv) improvement of empathy and worsening of impulsive-compulsive behaviors. Each component was associated with the stimulation of spatially segregated fiber bundles connecting regions of the frontal cortex with the subthalamic nucleus. The extent of stimulation of these tracts was able to explain significant amounts of variance in outcomes for individual symptoms in the original cohort (circular analysis), as well as in the rank of depression outcomes in the independent validation cohort. Our approach represents an innovative concept for mapping changes along extensive score batteries to a few anatomical fiber bundles and could pave the way toward personalized deep brain stimulation.

Abstract Image

丘脑下深部脑刺激:将非运动结果映射到结构连接
在帕金森氏病(PD)中,丘脑下核(STN-DBS)的深部脑刺激可靠地改善了运动症状,并且介导这些效果的回路已在很大程度上被确定。然而,非运动结果的变化更大,目前尚不清楚需要调节或避免哪些特定的大脑回路来改善它们。由于许多非运动症状可能对DBS有反应,因此独立确定介导每种症状的电路是具有挑战性的。数据压缩算法,如主成分分析(PCA)可能提供一个强大的替代方案。本研究旨在为该方法提供概念证明,通过将广泛的评分电池的变化映射到几个解剖纤维束,进而根据这些束的刺激估计个体评分的变化。回顾性数据来自56例PD和双侧STN-DBS患者。患者接受了全面的临床评估,包括食欲行为、情绪、焦虑、冲动、认知和共情的变化。采用PCA来确定神经精神病学和神经心理学结果的主要维度。通过DBS纤维过滤,我们确定了结构连接,其刺激与这些维度的变化有关。然后,对个体症状结果的估计是基于这些连接的刺激,通过反转PCA得出的。最后,在一个独立的验证数据集(N = 68)中使用通道模型估计特定非运动评分的变化。保留了四个主要成分,可以解释为反映(i)一般非运动改善;(2)情绪认知改善,特质性冲动加重;(三)认知能力的提高;(四)共情能力的提高和冲动强迫行为的恶化。每个成分都与连接额叶皮层和丘脑底核区域的空间分离纤维束的刺激有关。这些神经束的刺激程度能够解释原始队列中个体症状结果的显著差异(循环分析),以及独立验证队列中抑郁结果的等级差异。我们的方法代表了一种创新的概念,可以沿着广泛的score电池将变化映射到几个解剖纤维束,并为个性化的深部脑刺激铺平道路。
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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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