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使用电生理方法检测创伤性脑损伤。

Traumatic brain injury detection using electrophysiological methods.

作者信息

Rapp Paul E, Keyser David O, Albano Alfonso, Hernandez Rene, Gibson Douglas B, Zambon Robert A, Hairston W David, Hughes John D, Krystal Andrew, Nichols Andrew S

机构信息

Uniformed Services University of the Health Sciences School of Medicine , Bethesda, MD , USA.

Bryn Mawr College , Bryn Mawr, PA , USA.

出版信息

Front Hum Neurosci. 2015 Feb 4;9:11. doi: 10.3389/fnhum.2015.00011. eCollection 2015.

DOI:10.3389/fnhum.2015.00011
PMID:25698950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4316720/
Abstract

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

摘要

用电生理方法测量神经元活动可能有助于检测神经功能障碍,如轻度创伤性脑损伤(mTBI)。这种方法对于在包括军人和运动员在内的高危人群中进行快速检测可能特别有价值。电生理方法,如定量脑电图(qEEG)和记录事件相关电位(ERP)可能很有前景;然而,该领域尚处于起步阶段,对于这些方法作为诊断工具的有效性和准确性存在重大争议。例如,脑电图(EEG)中最适合作为功能障碍标志物的具体测量方法尚未明确确立。开展了一项研究,以总结和评估关于qEEG作为mTBI检测工具的总体效用的证据的统计严谨性。该分析评估了可能最适合作为实用诊断工具的qEEG测量指标/参数,确定了其他有前景的EEG测量类型和分析方法,推荐了作为mTBI检测工具进一步开发的具体测量指标和分析方法,确定了该领域的研究空白,并推荐了未来的研究和开发重点领域。qEEG研究小组得出了以下结论:(1) 个体qEEG测量指标对mTBI的诊断效用有限。然而,许多测量指标可能是qEEG判别函数的重要特征,而这些判别函数作为mTBI检测工具确实显示出了显著的前景。(2) ERP在mTBI检测中具有效用。事实上,有证据表明ERP能够在仅EEG未显示异常的情况下识别异常。(3) 用于表征mTBI脑电图的标准数学程序应加以扩展,以纳入更新的分析方法,包括非线性动力学分析、复杂性测量、因果相互作用分析、图论和信息动力学。(4) 对TBI的qEEG评估中高特异性的报告必须谨慎解读。在精心构建的临床研究中报告了高特异性,这些研究将健康对照与精心挑选的TBI人群进行了比较。然而,已发表的文献表明,在其他神经精神疾病中也观察到qEEG测量指标存在类似异常。虽然使用这项技术可能能够区分临床患者和健康对照参与者,但这些测量指标不太可能区分例如重度抑郁症、双相情感障碍或TBI。在这些临床研究中观察到的特异性在实际临床实践中很可能会丧失。(5) 缺乏特异性并不排除临床效用。作为治疗反应纵向测量指标的使用可能性仍然存在。然而,作为纵向临床测量指标的有效性确实需要可接受的重测可靠性。迄今为止,很少有关于从TBI患者或健康对照获得的qEEG数据的重测可靠性研究发表。这是一个特别令人担忧的问题,因为高变异性是受伤中枢神经系统的一个已知特征。

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