首页> 外文期刊>Bangladesh Journal of Medical Physics >Distribution of Conduction Velocity (DCV) from measured F-Wave Latency for detection of cervical spondylotic radiculopathy and myelopathy (CRM)
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Distribution of Conduction Velocity (DCV) from measured F-Wave Latency for detection of cervical spondylotic radiculopathy and myelopathy (CRM)

机译:测得的F波潜伏期的传导速度(DCV)分布,用于检测颈椎神经根神经病和脊髓病(CRM)

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In the previous work of our extended group at Dhaka, Distribution of Conduction Velocity (DCV) of motor nerve fibres in a peripheral nerve trunk was established as an approximate mirror image of Distribution of F-Latency (DFL), for which consecutive 30 to 40 F-latencies were used through multiple stimulation of a peripheral nerve trunk. Using patterns of DFL a considerable amount of experience has been built up in the detection of Cervical Spondylotic Radiculopathy and Myelopathy (CRM). In the present work we have obtained DCV directly from the Conduction Velocity (CV) values obtained from each of the F-latencies. Because of the inverse relationship between latency and velocity, a small variation to the mirror image should be present, particularly when discrete bin widths are used to obtain the frequency distribution. Therefore, one challenge was to choose an appropriate bin width while obtaining DCV directly so that the patterns can be related to those of DFL easily for the detection of CRM. To obtain DFL our extended group at Dhaka had used a bin width of 2 ms which gave good results. To choose a corresponding bin width for DCV four recognized measures of central tendency: Average of the range, Median, Mode and Mean (weighted average) were used and the resulting patterns of DCV were compared to that of DFL to determine the percentage of matches with respect to the detection of CRM. It was observed that Median gave the best DCV with 89% matches followed closely by Mode giving 83% match. The other two gave much lower values, 67% and 50%. Therefore, median value gave the best match which could be used to obtain DCV from the CV values directly, for the determination of CRM. Bangladesh Journal of Medical Physics Vol.7 No.1 2014 56-65
机译:在我们达卡扩展小组的先前工作中,建立了周围神经干中运动神经纤维传导速度(DCV)的分布作为F延迟(DFL)分布的近似镜像,连续30到40通过多次刺激周围神经干来使用F潜伏期。使用DFL模式在颈椎神经根神经病和脊髓病(CRM)的检测中已经积累了大量经验。在本工作中,我们直接从每个F延迟获得的传导速度(CV)值中获得了DCV。由于等待时间和速度之间呈反比关系,因此镜像的变化应该很小,尤其是在使用离散的分箱宽度来获得频率分布时。因此,一个挑战是在直接获得DCV的同时选择合适的仓宽,以便可以将图案与DFL的图案轻松关联以检测CRM。为了获得DFL,我们在达卡的扩展小组使用了2 ms的bin宽度,这给出了很好的结果。要为DCV选择相应的条带宽度,请使用四个公认的集中趋势度量:范围的平均值,中位数,众数和均值(加权平均值),并将DCV的最终模式与DFL的模式进行比较,以确定与关于CRM的检测。观察到,Median的DCV最佳,匹配率为89%,其次是Mode的83%。其他两个给出的值要低得多,分别为67%和50%。因此,中值给出了最佳匹配,可用于直接从CV值获得DCV,从而确定CRM。孟加拉国医学物理学杂志2014年第7卷第1期56-65

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