肌电图干扰相转折—波幅云图分析在神经肌肉疾病的应用研究

发布时间：2019-05-20 13:33

【摘要】：研究背景肌电检测是临床上一种重要的电生理检测手段,是神经肌肉病变诊断过程中非常重要的一个环节。随着电子技术的迅猛发展,肌电图检查逐渐趋向定量化。最早采用人工定量肌电图的方法,起始于40年代,所分析的是单个运动单位电位(motor unit potential,MUP),即平均运动单位动作电位量化分析(quantitative evaluation of mean motor unit potential,QMUP)。此方法要求选取至少20个不同的MUP样本,并分析平均时限、平均波幅以及多相电位所占的百分率。分析单个MUP的缺点是单个不同的MUP只能在轻收缩情况下获取,收缩力量仅为最大随意收缩(maximal voluntary contraction,MVC)的4%左右。随着力量的增加,动作电位数增加,产生动作电位的干扰,即干扰相(interferencepattern;,IP),以致不可能识别各不同的单个MUP。因此,此方法仅代表轻收缩时激活的运动单位,而不能显示较强收缩时激活的运动单位的异常情况。由于干扰相分析可提供多种阈值水平运动单位的功能状态情况,包括转折、波幅、复杂性和募集型等信息,对轻度失神经支配更敏感,因此建立干扰相分析方法非常必要。人眼无法识别较强收缩时肌电信号的干扰,因此需要用自动化方法来分析。60年代以后建立了多种干扰相自动分析方法(automated interference pattern analysis,IPA)。目前对肌电干扰型的研究方法多种多样,采用的参数特性也各有不同,包括转折-波幅分析、过零率、峰值比率、功率谱、云图分析等。其中转折-波幅云图分析(turns-amplitude cloud analysis)为最成熟和完善的方法之一,即也称Willison analysis。该技术由Stalberg等在1983年改良:在所测肌肉的几个不同部位,从轻收缩到大力收缩的不同力量水平记录肌电IP信息,最后以平均波幅作为转折数/秒的函数作散点图,利用特殊的算法画出这些点的上限、下限、最大转折数、最大波幅,所得图形即为云图,该图包含正常人群90%以上的数据点,而神经源性损害患者的大多数点落在云图的上限之上,肌源性损害患者的数据点大多落在云图的下限之下。此后多项研究证实此方法对于神经源性与肌源性疾病的鉴别具有较好的敏感性和特异性。因为不需要收缩力测定,此法既可靠又快速。但正常值范围确定困难,且是否受到种族、年龄、性别、肌肉、左右侧等诸多因素影响仍不明确,故没有得到广泛应用。国内相关领域研究较少,云图正常值范围及相关影响因素尚未建立,神经源性及肌源性疾病的云图诊断标准也未确立,上述诸多因素是否会影响此方法对国内神经肌肉疾病患者的诊断率仍不明确。目的:本研究旨在应用云图分析方法检测国内健康的成年人及神经肌肉疾病患者的IP信号,分析其转折、波幅特点,探讨我国成年人IP云图的形状及正常值范围,及正常云图的影响因素,比较IP云图分析方法(IPA)和传统手工定量肌电图方法(QMUP)对神经肌肉疾病诊断的敏感性及特异性。本研究的开展将为建立我国成年人正常云图,利用云图技术提高神经源性与肌源性疾病的诊断率提供科学依据。方法:(1)入组2014年9月～2016年3月于临沂市人民医院体检中心行健康体检的部分成年人,门诊和病房中部分具有局部神经疾病但未累及所检查部位的病人,以及部分医务人员和学生为正常志愿者,并收集同期在门诊和病房的部分典型神经肌肉疾病者为患者组。运用IP云图方法检测正常志愿者肢体肌肉,收集转折-波幅数据,对患者组和对照组(选取部分同期志愿者为对照组)肢体肌肉同时运用传统定量针极肌电图和IP云图分析两种方法进行检测,并记录受试者年龄、性别、肌肉名称。(2)分析受试者肌肉IP信号的转折及波幅分布情况。(3)分析年龄、性别、肌肉和优势或非优势侧别对云图的影响。根据影响因素分组,分别确定正常云图。(4)根据建立的正常云图,比较云图分析与传统定量肌电图两种方法对国人神经肌肉疾病的诊断率,并分析与国外报道的异同。结果:(1)共收集60例正常者、27例神经肌肉疾病患者和20例正常对照者信息。(2)数据分布结果显示:受试者肌肉IP信号的转折和对应波幅值有相关性,分别取对数值后均呈正态分布,用线性回归分析呈线性相关。(3)正常云图受年龄、性别、肌肉的影响。分别按年龄、性别、肌肉分组,计算回归分析参数,分别确定正常云图。(4)两种方法对国人神经肌肉疾病诊断的敏感性和特异性相似。结论:IP信号自动分析技术之转折-波幅云图分析在检测人群肌肉转折-波幅值中具有较高的便捷性,利用此技术测得的值可分别计算出国人五块肌肉(肱二头肌、三角肌、指总伸肌、胫骨前肌、股四头肌)的正常云图;性别及年龄是正常成人肌肉云图主要影响因素;云图对神经肌肉疾病诊断的敏感性和特异性与传统定量针极肌电图方法类似。应用云图技术可以较好地诊断神经肌肉疾病。国人IP信号波幅正常值稍低于国外研究推荐的标准,故建议使用该方法时需要考虑人种差异,建立适合不同人种的诊断标准。
[Abstract]:The research background myoelectric detection is an important method of electrophysiological detection in the clinic, which is a very important part in the diagnosis of neuromuscular disease. With the rapid development of the electronic technology, the electromyogram examination gradually becomes quantitative. The first method of using artificial quantitative electromyography, which began in the 1940s, was analyzed as a single motor unit potential (MUP), i.e., an average motion unit action potential quantitative analysis (QMUP). This method requires that at least 20 different MUP samples be selected and the mean time, mean amplitude, and the percentage of the polyphase potential are analyzed. The disadvantage of the analysis of a single MUP is that a single different MUP can only be obtained in the case of light shrinkage, and the contraction force is only about 4% of the maximum random contraction (MVC). As the power increases, the number of action potentials increases, resulting in an interference of the action potential, i. e., an interference pattern, ip, so that it is not possible to identify the different individual mups. Therefore, this method only represents a motion unit that is activated at light shrinkage, and does not display an abnormal condition of the active unit that is activated when a strong contraction is not displayed. Because of the interference phase analysis, the functional state of a plurality of threshold level moving units can be provided, including the information such as turning, amplitude, complexity and raised type, which is more sensitive to the control of the slight loss of nerve, and therefore it is necessary to establish an interference-phase analysis method. The human eye can't recognize the disturbance of the muscle electrical signal at the time of the strong contraction, so it is necessary to use the automatic method to analyze. The automatic interference pattern analysis (IPA) is set up in the '60s. At present, the research methods of the myoelectric interference type are various, and the parameter characteristics adopted are also different, including the turning-wave amplitude analysis, the zero crossing rate, the peak ratio, the power spectrum, the cloud image analysis, and the like. The transformation-amplitude cloud analysis is one of the most mature and perfect methods, that is, it is also known as wilson analysis. The technique is modified by Stalkberg et al. in 1983: at several different parts of the measured muscle, the myoelectric IP information is recorded from the light of different strength levels of light contraction to the large-scale contraction, and finally, the average amplitude is used as a function of the turning number/ second as a scatter diagram, and the upper limit and the lower limit of the points are drawn by using a special algorithm. The maximum number of turns and the maximum amplitude, the resulting graph is the cloud picture, which contains more than 90% of the data points in the normal population, and most of the point of the neurogenic damage patients fall above the upper limit of the cloud picture, and the data points of the patients with the myogenic damage fall below the lower limit of the cloud picture. After that, a number of studies have confirmed that this method has better sensitivity and specificity for the identification of neurogenic and myogenic diseases. This method is both reliable and fast because no shrinkage force is required. However, that range of normal value is difficult, and the influence of many factors, such as race, age, sex, muscle, left and right side, is still unclear, so it is not widely used. The research of the related fields in China is less, the normal range of the cloud image and the related influencing factors have not been established, and the diagnostic standard of the nephogram of the neurogenic and myogenic diseases is not established, and whether the above factors will affect the diagnosis rate of the patients with internal neuromuscular diseases is still unclear. Objective: The purpose of this study is to use the cloud image analysis method to detect the IP signals of adult and neuromuscular diseases in China, and to analyze the change and amplitude characteristics of the adult IP nephogram in China, and to explore the influence factors of the shape and normal value of the adult IP nephogram in our country, and the influence factors of the normal cloud picture. To compare the sensitivity and specificity of the method (IPA) and traditional manual quantitative electromyography (QMUP) to the diagnosis of neuromuscular diseases. The development of this study will provide a scientific basis for the establishment of the normal cloud image of adult adults and the improvement of the diagnostic rate of neurogenic and myogenic diseases by using the cloud image technique. Methods: (1) The patients who were enrolled in the health examination at the health examination center of the People's Hospital of Linyi City from September 2014 to March 2016, the patients in the outpatient department and the ward, the patients not involved in the examination site, and some of the medical personnel and the students were the normal volunteers. And collecting part of the typical neuromuscular disease in the clinic and the ward for the same period as the patient group. using the method of the IP nephogram to detect the limb muscle of the normal volunteers, the turning-wave amplitude data is collected, and the limb muscles of the patient group and the control group (the selected part of the same period of the same time as the control group) are used for detecting the limb muscles of the normal volunteers at the same time, The subject's age, sex, and muscle name were recorded. (2) The change of the muscle IP signal and the amplitude distribution of the subject's muscle were analyzed. (3) Analyze the influence of age, sex, muscle and advantage or non-dominant side on the cloud picture. And according to the influence factors, the normal cloud picture is respectively determined. (4) according to the established normal cloud picture, comparing the cloud image analysis and the traditional quantitative electromyogram to the diagnosis rate of the Chinese neuromuscular diseases, and analyzing the similarities and differences with the foreign reports. Results: (1) A total of 60 normal subjects,27 patients with neuromuscular disease and 20 normal controls were collected. (2) The results of data distribution show that there is a correlation between the transition of the muscle IP signal and the corresponding amplitude of the subject's muscle. (3) The normal cloud picture is affected by age, sex and muscle. And calculating the regression analysis parameters according to the age, the sex and the muscle group respectively, and respectively determining the normal cloud picture. (4) The sensitivity and specificity of the two methods to the diagnosis of neuromuscular diseases in the Chinese are similar. Conclusion: The change of the auto-analysis technology of IP signal-amplitude cloud image has a higher convenience in the detection of the muscle-turn-amplitude value of the population, and the value measured by this technique can be used to calculate the five-block muscle (biceps, deltoid, finger total extensor, and pretibial muscle). Normal nephogram of quadriceps femoris (quadriceps femoris); gender and age are the main influencing factors of the normal adult muscle nephogram; the sensitivity and specificity of nephogram to the diagnosis of neuromuscular diseases are similar to that of traditional quantitative needle-electrode electromyography. The neuromuscular disease can be well diagnosed by the application of the cloud image technique. The normal value of the Chinese IP signal is slightly lower than the standard recommended by the foreign research, so it is recommended that the method be used to consider the ethnic difference and establish a diagnostic standard suitable for different ethnic groups.
【学位授予单位】：山东大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：R746

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