Neuroscience
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CMAP Scan MUNE (MScan) - A Novel Motor Unit Number Estimation (MUNE) Method
Chapters
Summary June 7th, 2018
This protocol describes a new method to estimate the number of functioning motor units in a muscle, by fitting a model to a detailed stimulus-response curve of the compound muscle action potential. It is quick and easy to perform and analyze and has excellent reproducibility.
Transcript
The overall goal of this procedure is to describe MScan, a new method used to estimate the number of functioning motor units in a muscle. MScan is a non-invasive method used to estimate the number of functioning motor units in a muscle. MScan works by fitting a model to a detailed stimulus-response curve, or CMAP scan.
This method has several advantages. It can be completed quickly, it's easy to perform and analyze, and it has excellent reproducibility. To begin, request written consent from the subject.
All subjects must give their written consent prior to the examination. Then, explain that the subject will experience a tickling sensation in their hand and wrist and that the examination can be halted at any time should they experience too much discomfort. First, use skin prep gel and alcohol to clean the subject's hand and forearm.
Position the active recording electrode over the abductor pollicis brevis muscle, and then place the reference electrode on the metacarpophalangeal joint of the thumb. Place a ground electrode on the dorsum of the subject's hand, and connect the electrodes to the pre-amplifier. After positioning and connecting the electrodes to the pre-amplifier, tape the subject's fingers together to reduce noise and artifacts caused by voluntary movement.
To start the semi-automated computerized system, use the standard protocol for motor nerve excitability tests. From the main menu, select MSCAN-R recording protocol and accept default settings for the pre-amplifier and the stimulator. In the Select recording parameters form, enter a two-to three-letter operator prefix in the Output file box.
Then, click OK to continue. When the screen displays the raw EMG input, accept the default parameters and click OK.To find the site of lowest threshold at the median nerve of the wrist, position a repositionable stimulating electrode. Continue to adjust the position of the electrode until the largest EMG response has been achieved.
Once the site of lowest threshold has been located, click OK to continue. Next, the modified response will be displayed with the window where the response is measured. The magenta line indicates the response measured in the window, while the short green line immediately before the window indicates the baseline.
Replace the repositionable electrode with a non-polarizable adhesive stimulating cathode electrode, and place an anode two centimeters proximally along the median nerve. Encourage the subject to find the most relaxed position for their hand to minimize spontaneous activity. Click the OK button to continue.
Manually increase stimulus intensity by steps of 3%by pressing the Insert key. Click the OK button to continue. Make fine 1%stimulus adjustments until the stimulus current is above the level for the maximal amplitude of the CMAP.
After the responses to 20 supramaximal pre-scans are recorded, the stimulus intensity will automatically decrease with the frequency and percent steps selected previously. Once there is no longer a response from the subject, click the OK button to finish the recording with the series of 20 CMAP post-scans. Finally, click the OK button in the lower right corner to finish the recording and save the data.
To do analyses offline, start the analysis program and select the MScan recording to be analyzed. Select Fit MScan on a QZD file from the menu. Then, the program will automatically generate a preliminary model and optimize the fit.
The program will continue to run without user intervention until the multicolored progress bar in the Optimization box is complete and the Stop button is gray. The original scan, in black, can be plotted next to the scan generated by the model, in magenta. Make serial adjustments to minimize the difference between the recorded and simulated scans and optimize the model.
In the Plot type box, different plotting options may be used to track the optimization process. A multicolored progress bar will also be displayed in the Optimization panel. Use a contour plot to assess the accuracy of the model by selecting the Diff and Contour map displays.
These displays show the differences between the recorded and modeled CMAP scans as a contour plot. As the optimization process runs, these differences will be minimized. When the optimization process is complete, view the analysis results in the MScanFit text display.
Finally, click on the OK button to save the model in a MEM file. In this study, MScan MUNE is used to derive an estimation of the number and sizes of functional motor units by fitting a model to CMAP scan. This technique is tested for sensitivity and specificity in both healthy controls and ALS patients.
As expected, the median number of motor units in patients with ALS is significantly lower than in healthy controls. As shown by the ROC curve, the ability of MScan MUNE to distinguish the healthy controls from ALS patients is compared to that of CMAP. Area under the curve, or AUC, is used to measure the ability of both techniques to distinguish between ALS patients and healthy controls.
The AUC of MScan MUNE is significantly higher than that of CMAP. Once mastered, this technique can be completed in six minutes if it's performed properly. The analysis process is also fast and should take less than five minutes.
When attempting this procedure, it's important to remember to achieve adequate relaxation of the subject. MScan is a method that may have the potential to be implemented in a clinical setting for diagnosis and monitoring of neuromuscular disorders such as ALS. Further studies with other neuromuscular disorders and larger study groups are warranted.
Studies on the application of MScan in different muscle groups should also be conducted. After watching this video, you should have a good understanding of how to perform and analyze MScan examinations.
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