Preoperative network activity predicts the response to subthalamic DBS for Parkinson's disease

IF 6.9 2区医学 Q1 CLINICAL NEUROLOGY

Neurotherapeutics Pub Date : 2025-09-01 DOI:10.1016/j.neurot.2025.e00699

Prashin Unadkat , An Vo , Yilong Ma , Chris C. Tang , Vijay Dhawan , Martin Niethammer , Nha Nguyen , Shichun Peng , Akash Mishra , Ritesh Ramdhani , Albert Fenoy , Silvia Paola Caminiti , Daniela Perani , David Eidelberg

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引用次数: 0

Abstract

Quantitative imaging markers to aid in the selection of Parkinson's disease (PD) patients for surgical interventions such as subthalamic nucleus deep brain stimulation (STN-DBS) are currently lacking. Using metabolic PET and network analysis we identified and validated a treatment-induced topography, termed STN StimNet. Stimulation-mediated changes in network expression correlated with concurrent motor improvement in independent STN-DBS cohorts scanned on and off stimulation. Moreover, STN StimNet measurements off stimulation correlated with local field potentials recorded from the STN, whereas intraoperative modulation of cortical activity by STN stimulation correlated with contributions to the network from corresponding brain regions. These findings suggested that stimulation-mediated clinical responses are influenced by baseline StimNet expression. Indeed, we found that motor outcomes following STN-DBS were predicted by preoperative network expression measured using metabolic PET or resting-state fMRI. To illustrate the potential utility of these measures in selecting optimal candidates for DBS surgery, STN StimNet expression was computed in scans from 175 PD patients (0–21 years from diagnosis). The resulting values were used to identify those individuals likely to derive meaningful benefit from a potential STN-DBS procedure. This approach suggests that preoperative network quantification provides unique information regarding baseline brain circuitry, which may be useful in surgical decision making.

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术前网络活动预测帕金森病丘脑下DBS的反应。

目前缺乏定量成像标记来帮助选择帕金森病（PD）患者进行手术干预，如丘脑下核深部脑刺激（STN-DBS）。通过代谢PET和网络分析，我们确定并验证了一个处理诱发的地形，称为STN刺激网。刺激介导的网络表达变化与独立STN-DBS队列在刺激和关闭刺激扫描时并发运动改善相关。此外，STN StimNet测量的刺激与STN记录的局部场电位相关，而术中STN刺激对皮层活动的调节与相应大脑区域对网络的贡献相关。这些发现表明刺激介导的临床反应受到基线StimNet表达的影响。事实上，我们发现STN-DBS后的运动结果可以通过术前使用代谢PET或静息状态fMRI测量的网络表达来预测。为了说明这些措施在选择DBS手术最佳候选人方面的潜在效用，我们在175名PD患者（诊断后0-21年）的扫描中计算了STN StimNet表达。结果值用于识别那些可能从潜在的STN-DBS程序中获得有意义益处的个体。这种方法表明术前网络量化提供了关于基线脑回路的独特信息，这可能对手术决策有用。

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

Neurotherapeutics 医学-神经科学

CiteScore

11.00

自引率

3.50%

发文量

154

审稿时长

6-12 weeks

期刊介绍： Neurotherapeutics® is the journal of the American Society for Experimental Neurotherapeutics (ASENT). Each issue provides critical reviews of an important topic relating to the treatment of neurological disorders written by international authorities. The Journal also publishes original research articles in translational neuroscience including descriptions of cutting edge therapies that cross disciplinary lines and represent important contributions to neurotherapeutics for medical practitioners and other researchers in the field. Neurotherapeutics ® delivers a multidisciplinary perspective on the frontiers of translational neuroscience, provides perspectives on current research and practice, and covers social and ethical as well as scientific issues.