{"title":"MScanFit MUNE 和定量肌电图在肌萎缩性脊髓侧索硬化症诊断中的比较评估:前瞻性研究。","authors":"","doi":"10.1016/j.clinph.2024.07.017","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Motor Unit Number Estimation (MUNE) techniques are crucial in assessing lower motor neuron loss. MScanFit MUNE (MScanFit) is a novel tool which estimates MUNE values from compound muscle action potential (CMAP) scans by considering the probabilistic nature of motor unit firing. We conducted a prospective study to evaluate the diagnostic utility of MScanFit compared to quantitative electromyography (qEMG) in ALS patients.</p></div><div><h3>Methods</h3><p>We enrolled 35 patients diagnosed with amyotrophic lateral sclerosis (ALS) and 14 healthy controls, assessing qEMG and MScanFit MUNE in abductor pollicis brevis, abductor digiti minimi and tibialis anterior muscles.</p></div><div><h3>Results</h3><p>We found higher sensitivity of qEMG in detecting abnormalities compared to MScanFit, with a high concordance rate between the two techniques. Notably, a few muscles exhibited abnormal MUNE but normal qEMG findings, suggesting a potential complementary role for MScanFit in ALS diagnosis. Neurophysiological parameters from MScanFit showed good correlations with qEMG measures. Subclinical neurophysiological involvement was observed in muscles with normal strength, emphasizing the importance of sensitive diagnostic tools.</p></div><div><h3>Conclusion</h3><p>MScanFit demonstrated validity in distinguishing ALS patients from healthy subjects and correlated well with qEMG parameters.</p></div><div><h3>Significance</h3><p>Our study confirmed the diagnostic utility of MScanFit MUNE in ALS, highlighting its role as a supplementary diagnostic tool.</p></div>","PeriodicalId":10671,"journal":{"name":"Clinical Neurophysiology","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative assessment of MScanFit MUNE and quantitative EMG in amyotrophic lateral sclerosis diagnosis: A prospective study\",\"authors\":\"\",\"doi\":\"10.1016/j.clinph.2024.07.017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>Motor Unit Number Estimation (MUNE) techniques are crucial in assessing lower motor neuron loss. MScanFit MUNE (MScanFit) is a novel tool which estimates MUNE values from compound muscle action potential (CMAP) scans by considering the probabilistic nature of motor unit firing. We conducted a prospective study to evaluate the diagnostic utility of MScanFit compared to quantitative electromyography (qEMG) in ALS patients.</p></div><div><h3>Methods</h3><p>We enrolled 35 patients diagnosed with amyotrophic lateral sclerosis (ALS) and 14 healthy controls, assessing qEMG and MScanFit MUNE in abductor pollicis brevis, abductor digiti minimi and tibialis anterior muscles.</p></div><div><h3>Results</h3><p>We found higher sensitivity of qEMG in detecting abnormalities compared to MScanFit, with a high concordance rate between the two techniques. Notably, a few muscles exhibited abnormal MUNE but normal qEMG findings, suggesting a potential complementary role for MScanFit in ALS diagnosis. Neurophysiological parameters from MScanFit showed good correlations with qEMG measures. Subclinical neurophysiological involvement was observed in muscles with normal strength, emphasizing the importance of sensitive diagnostic tools.</p></div><div><h3>Conclusion</h3><p>MScanFit demonstrated validity in distinguishing ALS patients from healthy subjects and correlated well with qEMG parameters.</p></div><div><h3>Significance</h3><p>Our study confirmed the diagnostic utility of MScanFit MUNE in ALS, highlighting its role as a supplementary diagnostic tool.</p></div>\",\"PeriodicalId\":10671,\"journal\":{\"name\":\"Clinical Neurophysiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Neurophysiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1388245724002177\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Neurophysiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1388245724002177","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的:运动单位数量估算(MUNE)技术对于评估下运动神经元损失至关重要。MScanFit MUNE(MScanFit)是一种新型工具,它通过考虑运动单位发射的概率性质,从复合肌肉动作电位(CMAP)扫描中估算出运动单位数。我们开展了一项前瞻性研究,评估 MScanFit 与定量肌电图(qEMG)相比在 ALS 患者中的诊断效用:我们招募了 35 名确诊为肌萎缩性脊髓侧索硬化症(ALS)的患者和 14 名健康对照者,评估了他们的肌电图(qEMG)和 MScanFit MUNE 在拇趾外展肌、趾外展肌和胫骨前肌中的应用:我们发现,与 MScanFit 相比,qEMG 检测异常的灵敏度更高,两种技术的吻合率也很高。值得注意的是,有几块肌肉的 MUNE 结果显示异常,但 qEMG 结果显示正常,这表明 MScanFit 在 ALS 诊断中具有潜在的补充作用。MScanFit 的神经电生理参数与 qEMG 测量结果显示出良好的相关性。在力量正常的肌肉中观察到了亚临床神经电生理受累,这强调了灵敏诊断工具的重要性:结论:MScanFit 在区分 ALS 患者和健康受试者方面具有有效性,并与 qEMG 参数具有良好的相关性:我们的研究证实了 MScanFit MUNE 对 ALS 的诊断效用,突出了其作为辅助诊断工具的作用。
Comparative assessment of MScanFit MUNE and quantitative EMG in amyotrophic lateral sclerosis diagnosis: A prospective study
Objective
Motor Unit Number Estimation (MUNE) techniques are crucial in assessing lower motor neuron loss. MScanFit MUNE (MScanFit) is a novel tool which estimates MUNE values from compound muscle action potential (CMAP) scans by considering the probabilistic nature of motor unit firing. We conducted a prospective study to evaluate the diagnostic utility of MScanFit compared to quantitative electromyography (qEMG) in ALS patients.
Methods
We enrolled 35 patients diagnosed with amyotrophic lateral sclerosis (ALS) and 14 healthy controls, assessing qEMG and MScanFit MUNE in abductor pollicis brevis, abductor digiti minimi and tibialis anterior muscles.
Results
We found higher sensitivity of qEMG in detecting abnormalities compared to MScanFit, with a high concordance rate between the two techniques. Notably, a few muscles exhibited abnormal MUNE but normal qEMG findings, suggesting a potential complementary role for MScanFit in ALS diagnosis. Neurophysiological parameters from MScanFit showed good correlations with qEMG measures. Subclinical neurophysiological involvement was observed in muscles with normal strength, emphasizing the importance of sensitive diagnostic tools.
Conclusion
MScanFit demonstrated validity in distinguishing ALS patients from healthy subjects and correlated well with qEMG parameters.
Significance
Our study confirmed the diagnostic utility of MScanFit MUNE in ALS, highlighting its role as a supplementary diagnostic tool.
期刊介绍:
As of January 1999, The journal Electroencephalography and Clinical Neurophysiology, and its two sections Electromyography and Motor Control and Evoked Potentials have amalgamated to become this journal - Clinical Neurophysiology.
Clinical Neurophysiology is the official journal of the International Federation of Clinical Neurophysiology, the Brazilian Society of Clinical Neurophysiology, the Czech Society of Clinical Neurophysiology, the Italian Clinical Neurophysiology Society and the International Society of Intraoperative Neurophysiology.The journal is dedicated to fostering research and disseminating information on all aspects of both normal and abnormal functioning of the nervous system. The key aim of the publication is to disseminate scholarly reports on the pathophysiology underlying diseases of the central and peripheral nervous system of human patients. Clinical trials that use neurophysiological measures to document change are encouraged, as are manuscripts reporting data on integrated neuroimaging of central nervous function including, but not limited to, functional MRI, MEG, EEG, PET and other neuroimaging modalities.