Mechanomyography is the traditional gold standard research technique for quantitative assessment of neuromuscular blockade. Mechanomyography directly measures the isometric force generated by the thumb in response to ulnar nerve stimulation. Researchers must construct their own mechanomyographs since commercial instruments are no longer available. A mechanomyograph was constructed, and its performance was compared against an archival mechanomyography system from the 1970s that utilized an FT-10 Grass force transducer, hypothesizing that train-of-four ratios recorded on each device would be equivalent.
A mechanomyograph was constructed using 3D-printed components and modern electronics. An archival mechanomyography system was assembled from original components, including an FT-10 Grass force transducer. Signal digitization for computerized data collection was utilized instead of the original paper strip chart recorder. Both devices were calibrated with standard weights to demonstrate linear voltage response curves. The mechanomyographs were affixed to opposite arms of patients undergoing surgery, and the train-of-four ratio was measured during the onset and recovery from rocuronium neuromuscular blockade.
Calibration measurements exhibited a positive linear association between voltage output and calibration weights with a linear correlation coefficient of 1.00 for both mechanomyography devices. The new mechanomyograph had better precision and measurement sensitivity than the archival system: 5.3 mV versus 15.5 mV and 1.6 mV versus 5.7 mV, respectively (P < 0.001 for both). A total of 767 pairs of train-of-four ratio measurements obtained from eight patients had positive linear association (R 2 = 0.94; P < 0.001). Bland–Altman analysis resulted in bias of 3.8% and limits of agreement of −13% and 21%.
The new mechanomyograph resulted in similar train-of-four ratio measurements compared to an archival mechanomyography system utilizing an FT-10 Grass force transducer. These results demonstrated continuity of gold standard measurement of neuromuscular blockade spanning nearly 50 yr, despite significant changes in the instrumentation technology.
Mechanomyography measures the isometric force generated by the thumb in response to ulnar nerve stimulation directly
It is the gold standard research technique for quantitative assessment of depth of neuromuscular blockade
Mechanomyography systems are no longer commercially available
The hypothesis that the train-of-four ratios recorded by an archival mechanomyograph would be equivalent to those of a modern laboratory-built mechanomyograph was tested by comparing the train-of-four ratios measured by the two instruments in the contralateral arms of eight anesthetized patients during the onset and recovery from rocuronium neuromuscular blockade
A total of 767 paired train-of-four ratio data points were collected with the archival and new mechanomyography systems
The new laboratory-built mechanomyograph and the archival mechanomyograph obtained essentially interchangeable train-of-four ratio measurements, providing reassurance of comparability of past and future studies performed with these modern mechanomyography systems
Mechanomyography has been widely considered to be the gold standard1 technique for research measurements of neuromuscular blockade and has been in use for almost 50 yr,2,3 yet mechanomyographs are not commercially available. Recently, there have been several new neuromuscular blockade monitors introduced for clinical use, utilizing electromyography,4–8 acceleromyography9 and blood pressure cuff pulsation.10 Validation of these devices has sometimes been hampered by a lack of access to the gold standard measurement technique.11
Mechanomyography directly measures the isometric force of contraction of the adductor pollicis muscle. In contrast, acceleromyography indirectly measures force (force is directly proportional to acceleration), and electromyography measures the muscle action potential. Electromyography has been suggested as an alternative gold standard12 ; however, not all currently available electromyograph neuromuscular blockade monitors deliver reliable results.13
Many of the original studies of neuromuscular blockade were performed using mechanomyography with commercially available Grass force transducers14 that are no longer produced and not widely available. We and others have assumed that a modern mechanomyograph built using currently available parts would give results comparable to the archival equipment, but this has not previously been tested. To assess the performance of our new mechanomyograph relative to the technology used in the classic studies, an archival mechanomyography system utilizing an FT-10 Grass force transducer was obtained from an investigator in our department15 and modified for computerized data collection. It was compared to a modern laboratory-built mechanomyograph in patients undergoing surgery. Our hypothesis was that the train-of-four ratios recorded by archival and new mechanomyograph would be equivalent and that the new mechanomyograph would perform equally well or better when compared to the archival mechanomyograph.
Materials and Methods
Archival Mechanomyography System
A Grass Instruments FT-10 force transducer (Grass Instruments, USA) and a Grass model 7400 paper strip chart recorder (Astro-Med, Inc., USA) were obtained from storage (fig. 1E). The Grass force transducer was originally developed in the 1970s and operates on the principle of Hooke’s law, which relates force to the deformation of a spring. The system was connected to the physiologic recorder with a pixelated display showing results; alternatively, results could be printed in real-time on graph paper or saved to a 3.5-inch disk. An analog output channel was also available and made functional after wire splicing, shielding, and digitization via an analog-to-digital converter, NI DAQ USB 6009 (National Instruments, USA).
A complex arm holder was needed to suspend the force transducer above the hand of the patient, as shown in figure 1, A to D. Essential considerations in the building process included structural integrity to ensure the transducer stayed in place during high force loads and maintaining a perpendicular angle between the thumb and the transducer spring to maximize the output signal. An archival arm holder device used in earlier studies was obtained. However, it did not include a mechanism for suspending the force transducer, which was built using set screws and a beaker clamp to allow for adjustment (fig. 1A). The thumb was held in place through a commercially available disposable finger splint suspended by Kevlar thread (Superior Threads, USA).
New Mechanomyography System
Electronic components were selected based on measurement range, precision, and size. They included a force transducer (C9B 100N, HBM, Germany), amplifier (EMBSGB200 version 2.3; Tacuna Systems, USA), and analog-to-digital signal converter (NI DAQ USB 6009 National Instruments; fig. 2D). The force transducer was secured to the thumb via a custom 3D-printed force transducer insert (fig. 2B). A second 3D-printed part was created to hold the arm in place and was adjustable to account for differences in hand, finger size, and flexibility (fig. 2A). Computer-aided drawings of 3D printed parts are available upon request. Wrist immobilization was provided by a commercial wrist splint device (DonJoy, USA; fig. 2C). Once set to a patient’s hand, the system was completely rigid for measurement of isometric force generated by the thumb.
A linear response to an applied force for each mechanomyograph system was established before use in clinical testing. Each system was calibrated using a series of weights to assess the system’s accuracy, precision, sensitivity, and resolution. For these experiments, a set of calibration weights (Ohaus, USA) up to 2 g were tested on both systems, by averaging 1,000 samples per weight. Data analysis was performed using MATLAB (MathWorks, USA). The calibration process differed based on the structures of the two systems; the weights were hung from the archival mechanomyograph or applied to a plastic plate on top of the force transducer for the new mechanomyograph. The calibration curves were used to calculate the voltage output range for 200 to 300 g of preload. Voltage output was assessed during device attachment to ensure adequate preload before clinical measurements.
Precision was estimated by calculating the mean SD in the voltage signal at each calibration weight. Resolution was calculated from the voltage range for each device divided by the number of bits supported by the analog-to-digital converter. Sensitivity was determined by multiplying the mean SD by the resolution.
Human Studies Design
This study was approved by the institutional review board, and written informed consent was obtained from patients. The study was registered with Clinicaltrials.gov (NCT05006807, Principal Investigator: Dr. Andrew Bowdle) on August 10, 2021. Patient eligibility criteria included age over 18 yr, requiring general anesthesia with administration of neuromuscular blocking drug, and having access to both arms. Patient recruitment occurred between December 2021 and March 2022. Anesthesia care was at the discretion of the anesthesia team. No constraints were placed on anesthesia care regarding the selection of neuromuscular blocking drugs and timing of reversal. The patients were outfitted with a mechanomyograph device on each arm. The ulnar nerve was stimulated with a 60-mA current supplied by a TwitchView monitor (Blink Device Company, USA). Figure 3 shows the study device setup.
Preload was set to 200 to 300 g and checked every 15 to 30 min. The patient’s thumb was repositioned as needed to maintain adequate preload. Twitch measurements were taken every 20 s to 1 min when one or more twitches were present. During periods of rapid change in train-of-four ratio, frequent measurements were made to maximize measurements across the full range of train-of-four ratios. The paired measurements from each arm were taken within 2 s of each other.
A LABView (National Instruments) program was written to collect the data and save all recordings at a sampling rate of 1,000 measurements/s. A 10-s interval was recorded for each data point comparison and included both mechanomyograph devices. Postprocessing of the data was performed in MATLAB for both mechanomyographs. After removing low signal data and electrocautery noise, a smoothing filter was applied before calculation of the train-of-four ratio. The train-of-four ratio was calculated in two different ways: by measuring the peak amplitude and the area under the curve of each peak. T4 was divided by T1 to determine train-of-four ratio.
The descriptive statistics are presented as number (%), median (range), and mean (SD) as appropriate. A simple regression model was used to compare the correlation of voltage with calibration weight for each device, as well as the correlation of the train-of-four ratio between the new and archival mechanomyography devices.
Precision is an analysis of the noise in a signal, specifically variations in measured voltage when the voltage output is expected to be constant.16 To calculate precision, 1,000 measurements were made with each device at a constant voltage. These 1,000 measurements were repeated at several different voltage outputs in response to 17 calibration weights ranging from 0 to 1.6 kg in 100-g increments since the amount of noise can vary in a circuit depending on the voltage. For each voltage, a SD of each set of 1,000 measurements was calculated. The mean standard deviations across all voltages were compared using chi-square tests between the new and archival mechanomyography systems.
A convenience sample was used since the number of patients enrolled was limited by the eligibility criteria and willingness of the surgical and anesthesia teams to tolerate the extensive and time-consuming set-up of the archival mechanomyograph. A Bland–Altman plot was used to describe the relationship between the difference and the average of the train-of-four ratio of the two mechanomyographs. To account for assessment of the agreement between methods over a range of repeated measurements in individual participants, we incorporated a modified Bland–Altman method based on ANOVA that has been reported by Olofsen et al.17 specifying the participant as the unit of clustering. All other statistical comparisons were performed using STATA version 15.0 (StataCorp LP, USA).18 Statistical significance was defined as a P value of < 0.05.
Calibration testing results are shown in Table A1 of the appendix. The new mechanomyography system had improved precision, resolution, and sensitivity compared to the archival mechanomyography (P < 0.001). The calibration measurements for both devices demonstrated positive association between voltage output and calibration weights with a linear correlation coefficient of 1.00 (fig. 4).
Demographic characteristics and intraoperative variables for the eight patients who participated in the study are shown in Table A2 of the appendix. Sample digital signals collected in the LABView program during data collection are shown in figure 5A. The raw voltage output waveforms before and after the application of a smoothing filter were similar; smoothing removed small variations due to electrical noise (fig. 5B). Train-of-four ratios during spontaneous recovery from neuromuscular blockade after a maintenance dose in a single patient for both mechanomyography devices are shown in figure 5C.
With the archival and new mechanomyography systems, 767 paired train-of-four ratio data points were collected (see Table A3 of the appendix). There was a linear relationship of train-of-four ratio measurements using peak heights obtained with the archival and new mechanomyograph systems with an R2 value of 0.94 (P < 0.001; fig. 6A). Bland–Altman analysis of the train-of-four ratio showed a bias of 3.8 ± 2.0% (95% CI, −1.1 to 8.6) with higher values for the new mechanomyograph as compared to the archival mechanomyograph and limits of agreement of −13.4% and 20.9% (95% CI lower limits of agreement, −23.5 to −8.7; 95% CI upper limits of agreement, 16.3 to 31.0; fig. 6B). The train-of-four ratios determined from peak height were equivalent to those determined from the area under the curve (R2 = 1.0) for both the new and archival mechanomyographs (fig. 6C; only data for new mechanomyograph shown).
An archival mechanomyograph system utilizing an FT-10 Grass force transducer was modified for digital data acquisition, and train-of-four ratio measurements obtained with the archival system were compared to those obtained with a new mechanomyograph on a contralateral arm. Despite a span of nearly 50 yr separating the designs of these mechanomyographs, the results were remarkably similar, with a bias of 3.8% and limits of agreement of −13% and 21%. Train-of-four ratios calculated from peak amplitude and area under the curve of peaks were similar. The new mechanomyograph had improved resolution, sensitivity, and precision, reflecting technological progress over the years. The similarity of the results from these instruments instills confidence that data obtained in studies utilizing mechanomyography over nearly five decades are likely to be comparable. Mechanomyography is a robust approach to measuring neuromuscular blockade that should continue to be regarded as a gold standard measurement and should be used to validate electromyograph and acceleromyograph neuromuscular blockade monitors.
Mechanomyography is the gold standard for measuring the twitch response to ulnar nerve stimulation for several reasons. First, it directly measures the force of isometric muscle contraction using a sensor (force transducer), the performance of which can be tested and verified ex vivo at the benchtop in the laboratory. Second, the signal generated by the transducer is robust and not easily subject to interference from electrical noise that is ubiquitous in an operating room. Third, because the measurement is direct and robust, it should be highly reproducible, as shown by this study. By contrast, acceleromyography and electromyography have significant drawbacks. Acceleromyography does not measure force directly but derives it from a measurement of acceleration. Acceleromyography is complicated by a high prevalence of “overshoot” in the train-of-four ratio, such that the baseline, unparalyzed train-of-four ratio is often greater than 1.11,19 Electromyography is an attractive alternative because it directly measures the muscle action potential, and it does not commonly manifest “overshoot” in the train-of-four ratio. However, the electromyogram is a small electrical signal and is highly susceptible to electrical artifacts that can interfere with interpretation. Therefore, the reliability of electromyography will be strongly influenced by the methods used to manage noise, which vary from one device to another. Thus, mechanomyography has been recommended as the gold standard of neuromuscular blockade measurement.1 Our results reinforce that recommendation.
There are several limitations to this study. A single archival mechanomyography system was studied as that was all that was available to us. Although systems utilizing Grass force transducers were widely utilized for research purposes, other mechanomyography systems have been used, such as the Relaxometer.20 As these other mechanomyography systems were not tested, these results may not be generalizable beyond the archival or the new mechanomyographs described in this article. The paired measurements were not synchronized but were obtained within 2 s; it is possible that minor differences between paired measurements could be due to a lack of perfect synchronization. The paired measurements were obtained from different arms. Arm-to-arm variation in neuromuscular blockade has been shown previously by Claudius et al.21 not to be clinically significant. Our experience is that substantial variation in arm-to-arm train-of-four ratio may occur in an individual subject, but that in a large data set, arm-to-arm variation is not evident, in agreement with Claudius et al.21 This potential source of variation was unavoidable in our study because it is not possible to place two mechanomyographs on the same arm. Additionally, our study did not employ a stabilization period before administration of neuromuscular blocking drugs. This was not done because the train of four ratio should not require stabilization, as might be required when looking at T1 amplitude,22 and the additional time needed to obtain these data would have further delayed surgery start beyond the extra time needed to set up two mechanomyographs.
The patient sample size was small, but many paired measurements were obtained. There were more train-of-four ratio measurements at the extremes of train-of-four ratios than mid-range train-of-four ratios. Since the limitations of the study would generally contribute additional variability to measurements, the similarity of the results from the mechanomyographs is perhaps all the more remarkable.
In conclusion, an archival mechanomyograph utilizing a Grass force transducer and a new mechanomyograph built in our laboratory obtained essentially interchangeable train-of-four ratio measurements in anesthetized patients, demonstrating the feasibility of using mechanomyography to validate the performance of electromyographic and acceleromyographic neuromuscular blockade monitors.
The authors acknowledge Edward Pavlin, M.D., Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington, for donating the archival mechanomyograph; John Brock-Utne, M.D., Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, California, for donating the arm holding apparatus that was modified to fit the archival mechanomyograph; and Aaron Kopman, M.D., Department of Anesthesiology, Weill Cornell Medical College, New York, New York, for providing valuable perspective on the history of mechanomyography and suggestions for the article.
Supported by the Foundation of Anesthesia Education and Research and the Washington Research (Schaumburg, Illinois) Foundation (Seattle, Washington; to Dr. Michaelsen) and in part by the Laura Cheney Professorship in Anesthesia Patient Safety (Seattle, Washington; to Dr. Bowdle). Support was, otherwise, provided from departmental sources.
The authors declare no competing interests.