Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease.

Sabato Santaniello, John T Gale, Sridevi V Sarma
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引用次数: 19

Abstract

Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive-compulsive disorders, essential tremor, Parkinson's disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients' responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson's disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.

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优化帕金森病深部脑刺激疗法的系统方法。
在过去的30年里,脑深部电刺激(DBS)已被用于治疗慢性神经系统疾病,如肌张力障碍、强迫症、特发性震颤、帕金森病,以及最近的痴呆症、抑郁症、认知障碍和癫痫。尽管应用广泛,但DBS给临床医生和工程师带来了许多挑战。一个挑战是设计新颖、更有效的DBS疗法,这受到对治疗性DBS细胞机制缺乏全面了解的阻碍。另一个挑战是临床结果存在冗余,也就是说,不同的DBS方案可以产生相似的临床效益,但很少有信息(例如,预测模型,纵向数据,指标等)可用于选择一个方案而不是另一个。最后,患者对DBS的反应有很大的可变性,这迫使临床医生通过长时间的编程来仔细调整每位患者的刺激设置。在过去的几年里,神经工程和系统生物学的研究人员一直在应对这些挑战,他们的具体目标是开发新的DBS疗法、设计方法和计算工具,以优化DBS对每位患者的治疗效果。此外,正在努力使DBS治疗自动适应疾病症状的波动。本文回顾了目前可用于治疗帕金森病的定量方法,重点介绍了系统理论方法对理解DBS下大脑中复杂神经元回路的全局动态的贡献。本文分类如下:转化、基因组和系统医学>治疗方法分析和计算方法>计算方法分析和计算方法>动力学方法生理学>健康与疾病中的哺乳动物生理学。
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来源期刊
CiteScore
18.40
自引率
0.00%
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0
审稿时长
>12 weeks
期刊介绍: Journal Name:Wiley Interdisciplinary Reviews-Systems Biology and Medicine Focus: Strong interdisciplinary focus Serves as an encyclopedic reference for systems biology research Conceptual Framework: Systems biology asserts the study of organisms as hierarchical systems or networks Individual biological components interact in complex ways within these systems Article Coverage: Discusses biology, methods, and models Spans systems from a few molecules to whole species Topical Coverage: Developmental Biology Physiology Biological Mechanisms Models of Systems, Properties, and Processes Laboratory Methods and Technologies Translational, Genomic, and Systems Medicine
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Tools for computational analysis of moving boundary problems in cellular mechanobiology. Cellular reprogramming: Mathematics meets medicine. Thermoregulation: A journey from physiology to computational models and the intensive care unit. Mammalian cell and tissue imaging using Raman and coherent Raman microscopy. Computational models to explore the complexity of the epithelial to mesenchymal transition in cancer.
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