Nerve conduction studies: clinical challenges and engineering solutions.

Nerve conduction studies (NCSs) have played an important role in the evaluation of neuromuscular disease for the past 50 years. When patients present with complaints of pain, numbness, tingling, or weakness, NCS is often one of the earliest tests obtained by physicians, because it enables the quantitative assessment of peripheral nerve and muscle function and, therefore, aid the physician in identifying the physiological source of the patient's symptoms. NCSs involve the delivery of electric stimuli to peripheral nerves at accessible locations on the human body and the recording of electrophysiological responses. This article reviews how NCS is traditionally performed. This paper also examines technical challenges associated with each step of performing an NCS and describes how engineering solutions could be realized to meet these challenges. The engineering goals were several: improvement in NCS workflow, use of prefabricated electrode arrays to standardize NCS technique and reduce the errors associated with electrode placement, and improvement of the overall accuracy and reliability of NCS.

Implementation and evaluation of a statistical framework for nerve conduction study reference range calculation.

Nerve conduction studies (NCS) play a central role in the clinical evaluation of neuropathies. Their clinical utilization depends on reference ranges that define the expected parameter values in disease-free individuals. In this paper, a statistical framework is proposed and described in detail for deriving NCS parameter reference ranges. The bootstrap technique is used to identify demographic and physiologic covariates that influence the NCS measurements. Multi-variate linear regression is used to improve the accuracy and effectiveness of NCS interpretation by reducing parameter variance. Non-linear mappings are used to transform parameters into a Gaussian distribution in order to minimize the influence of outliers. Modeling of heteroscedasticity observed in this and other studies leads to more sensible normal limits for several parameters. The proposed reference range method is automated using the MATLAB programming language. Data from a large sample of healthy subjects are used to establish reference ranges for 24 commonly measured NCS parameters. All but three parameters follow Gaussian distributions in their respective transformed domains. Excluding the distal motor latency difference between median and ulnar nerves, the reduction of the parameter variance as a result of regression in the transform domain is greater than 50% for all F-wave latency parameters and at least 10% for all other NCS parameters. Subject age is found to influence normal limits of all but one parameter and height has a statistically significant impact on all but three parameters. These reference range specifications provide clinicians with an alternative to developing their own reference ranges as long as their NCS techniques are consistent with those described in this paper. The proposed method should also be applicable to reference range development for other NCS techniques and physiological measurements.

Repeatability of nerve conduction measurements derived entirely by computer methods.

BACKGROUND: Nerve conduction studies are an objective, quantitative, and reproducible measure of peripheral nerve function and are widely used in the diagnosis of neuropathies. The purpose of this study is to determine the reliability of nerve conduction parameters derived entirely from computer based data acquisition and waveform cursor assignments and to quantify the relative contributions of test variability sources. METHODS: Thirty volunteers, some with symptoms suggestive of neuropathies; of these, 29 completed the study. The median, ulnar, deep peroneal, posterior tibial, and sural nerves were evaluated bilaterally at two test sessions 3-7 days apart. Within each session, nerves were tested twice within 10 minutes. The analyzed nerve conduction parameters include motor latencies, motor conduction velocity (CV), compound muscle action potential (CMAP) amplitude, F-wave latencies (minimum, mean and maximum), sensory peak latency (DSL), sensory CV, and sensory nerve action potential (SNAP) amplitude. The primary outcome measure is variance component analysis and the corresponding coefficient of variation (CoV). The between-session-test variance is the sum of within-session variance and between-session variance, quantifying the total variation between test sessions. Additional statistical measures include the intraclass correlation coefficient (ICC) and relative interval variation (RIV). RESULTS: Motor and sensory latencies, CV and F-wave latency parameters have low between-session-test CoVs, ranging from 4.2% to 9.8%. Amplitude parameters have a higher between-session-test CoVs in the range of 15.6--19.8%. Between-test CoVs are about 30--80% lower than between-session CoVs with the exception of F-wave latency parameters. Between-test ICC values are 0.96 or above for all parameters. Between-session ICC ranges from 0.98 for F-wave latency to 0.77 for sural sensory CV. All latency-related between-session ICCs have a value 0.83 or above. The RIVs are the tightest for F-wave latency parameters and widest for CMAP amplitude parameters. Repeatability in a sub-group of subjects with more severe symptom grades follows the same trend as the overall study population without substantial quantitative differences. CONCLUSION: The study demonstrates the high repeatability of nerve conduction parameters acquired by modern electrodiagnostic instruments using computer based waveform cursor assignment. The reliability is comparable to benchmark studies in which the nerve conduction measurements were performed manually in controlled multi-center clinical trials. Furthermore, the ranking of reliability, whereby F-wave latencies have the best reproducibility and amplitudes the worst, is also consistent with the benchmark studies.

Utilization of nerve conduction studies for the diagnosis of polyneuropathy in patients with diabetes: a retrospective analysis of a large patient series.

BACKGROUND: Diabetic polyneuropathy (DPN) is a disabling complication of diabetes mellitus. A population-based analysis of physician utilization of nerve conduction studies (NCS) for the assessment of DPN was conducted. METHODS: All electrodiagnostic encounters over a 30-month period using a computer-based neurodiagnostic instrument linked to a data registry were analyzed retrospectively. The DPN case definition was abnormal sural and peroneal nerve conduction. RESULTS: The study cohort consisted of a total of 63,779 electrodiagnostic encounters performed by 3468 physician practices. Primary care and internal medicine physicians represented 80.1% of the practices and accounted for 65.7% of the encounters. Endocrinologists represented 4.6% of the practices and 20.1% of the encounters. The demographics of patients were 52.7% female; 63.4+/-11.8 (mean+/-standard deviation) years (age); 168.1+/-10.9 cm (height); 92.2+/-22.6 kg (weight); and 32.6+/-7.2 kg/m(2) (body mass index). The most common peroneal abnormality was F-wave latency (33.6%). The sural nerve response latency and amplitude parameters had similar abnormality rates (58.3 and 62.7%). DPN was identified in 52.6% of the encounters; in another 19.3% no neuropathy was found. CONCLUSIONS: For over 70% of the patients, the specific diagnostic question of the presence of DPN was addressed by NCS with evidence-based criteria. The demographic features were strongly associated with risk of diabetes and DPN, suggesting that NCS were applied to appropriate demographic subgroups. The rate of DPN was also comparable to levels seen by academic electromyography laboratories. In 32.6% of the encounters the NCS suggested a posttest diagnosis other than DPN. This rate was similar to the results of referral to traditional electromyography laboratories. This study demonstrated that NCS using computer-based electrodiagnostic equipment was a suitable tool for the diagnosis of DPN. Furthermore, this technology permits examination of DPN in large populations.

Point-of-service nerve conduction studies: an example of industry-driven disruptive innovation in health care.

Nerve conduction studies (NCS) and needle electromyography are useful and established diagnostic procedures for evaluating patients with signs and symptoms of neuromuscular disease. Although technological advances have occurred since the introduction of commercial electromyography instrumentation in the 1950s, most improvements have been evolutionary and were designed to benefit traditional users--neurologists and physiatrists specializing in electromyography. In the past seven years, instruments have been introduced that automate NCS and thereby enable a broader group of physicians, including internists and orthopedic surgeons, to perform these studies and utilize electromyographic data in the care of their patients. Automated NCS devices are an example of what Clayton Christensen terms a "disruptive innovation." In this article, automated NCS is contrasted with traditional electromyography, and the challenges and opposition to its widespread adoption are explored.

Repeatability of nerve conduction measurements using automation.

OBJECTIVE: To quantify nerve conduction study (NCS) reproducibility utilizing an automated NCS system (NC-stat, NeuroMetrix, Inc.). METHOD: Healthy volunteers without neuropathic symptoms participated in the study. Their median, ulnar, peroneal, and tibial nerves were tested twice (7 days apart) by the same technician with an NC-stat instrument. Pre-fabricated electrode arrays specific to each nerve were used. Both motor responses (compound motor action potential [CMAP] and F-waves - all nerves) and sensory responses (sensory nerve action potentials [SNAP] - median and ulnar nerves only) were recorded following supramaximal stimuli. Automated algorithms determined all NCS parameters: distal motor latency (DML), mean F-wave latency (FWL), distal sensory latency (DSL), CMAP amplitude, and SNAP amplitude. Latency was adjusted for skin temperature deviation from reference. Pearson correlation coefficient (CC), intraclass correlation coefficient (ICC), coefficient of variance (CoV), and relative intertrial variation (RIV) were calculated. RESULTS: Fifteen subjects participated in either upper or lower extremity studies with nine participating in both. With the exception of CMAP amplitude, all parameters had CoV less than 0.06. Upper extremity amplitude parameters had CCs greater than 0.85. CCs for latencies were greater than 0.80 except for the median nerve FWL (CC = 0.69). For lower extremity nerves, ICCs were highest for mean FWL (>0.90), followed by DML (>0.82) and then CMAP (peroneal 0.33, tibial 0.73). The 10th to 90th RIV percentiles were bounded by +/-7% for F-wave latencies; +/- 9% for all DSLs; and +/- 11% for DML (except peroneal at 15%). CONCLUSIONS: The reproducibility of NCS parameters obtained with an automated NCS instrument compared favorably with traditional electromyography laboratories. F-wave latencies had the highest repeatability, followed by DML, DSL, SNAP and CMAP amplitude. Given their high reproducibility, automated NCS instrument may encourage wider utilization of NCS in clinical and research applications.