Rossi Lorenzo, Bianchi Anna Maria, Merzagora Anna, Gaggiani Alberto, Cerutti Sergio, Bracchi Francesco
Department of Human Physiology, University of Milan, Italy.
Biomed Eng Online. 2007 Jan 4;6:2. doi: 10.1186/1475-925X-6-2.
When spinal cord functional integrity is at risk during surgery, intraoperative neuromonitoring is recommended. Tibial Single Trial Somatosensory Evoked Potentials (SEPs) and H-reflex are here used in a combined neuromonitoring method: both signals monitor the spinal cord status, though involving different nervous pathways. However, SEPs express a trial-to-trial variability that is difficult to track because of the intrinsic low signal-to-noise ratio. For this reason single trial techniques are needed to extract SEPs from the background EEG.
The analysis is performed off line on data recorded in eight scoliosis surgery sessions during which the spinal cord was simultaneously monitored through classical SEPs and H-reflex responses elicited by the same tibial nerve electrical stimulation. The single trial extraction of SEPs from the background EEG is here performed through AutoRegressive filter with eXogenous input (ARX). The electroencephalographic recording can be modeled as the sum of the background EEG, which can be described as an autoregressive process not related to the stimulus, and the evoked potential (EP), which can be viewed as a filtered version of a reference signal related to the stimulus. The choice of the filter optimal orders is based on the Akaike Information Criterion (AIC). The reference signal used as exogenous input in the ARX model is a weighted average of the previous SEPs trials with exponential forgetting behavior.
The moving average exponentially weighted, used as reference signal for the ARX model, shows a better sensibility than the standard moving average in tracking SEPs fast inter-trial changes. The ability to promptly detect changes allows highlighting relations between waveform changes and surgical maneuvers. It also allows a comparative study with H-reflex trends: in particular, the two signals show different fall and recovery dynamics following stressful conditions for the spinal cord.
The ARX filter showed good performances in single trial SEP extraction, enhancing the available information concerning the current spinal cord status. Moreover, the comparison between SEPs and H-reflex showed that the two signals are affected by the same surgical maneuvers, even if they monitor the spinal cord through anatomically different pathways.
当手术中脊髓功能完整性面临风险时,建议进行术中神经监测。在此,胫神经单次试验体感诱发电位(SEPs)和H反射被用于一种联合神经监测方法:两种信号均监测脊髓状态,尽管涉及不同的神经通路。然而,SEPs表现出每次试验之间的变异性,由于其固有的低信噪比,这种变异性难以追踪。因此,需要采用单次试验技术从背景脑电图中提取SEPs。
对在八次脊柱侧弯手术过程中记录的数据进行离线分析,在此期间通过经典SEPs和由相同胫神经电刺激引发的H反射反应同时监测脊髓。在此,通过具有外部输入的自回归滤波器(ARX)从背景脑电图中进行SEPs的单次试验提取。脑电图记录可建模为背景脑电图(可描述为与刺激无关的自回归过程)与诱发电位(EP)之和,诱发电位可视为与刺激相关的参考信号的滤波版本。滤波器最佳阶数的选择基于赤池信息准则(AIC)。在ARX模型中用作外部输入的参考信号是具有指数遗忘行为的先前SEPs试验的加权平均值。
用作ARX模型参考信号的指数加权移动平均值在追踪SEPs快速试验间变化方面比标准移动平均值表现出更好的敏感性。迅速检测变化的能力有助于突出波形变化与手术操作之间的关系。它还允许与H反射趋势进行比较研究:特别是,在脊髓面临压力的情况下,这两种信号显示出不同的下降和恢复动态。
ARX滤波器在单次试验SEP提取中表现出良好性能,增强了有关当前脊髓状态的可用信息。此外 SEPs与H反射之间的比较表明,即使它们通过解剖学上不同的通路监测脊髓,但这两种信号受相同手术操作的影响。