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Take the A Train
Clinical Neurophysiology 126 (2015) 1647–1649
Contents lists available at ScienceDirect
Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Editorial
Take the A Train See Article, pages 1833–1839
Bill Strayhorn’s tune ‘‘Take the A Train’’, one of the jazz standard of all times, was composed in 1939, and then popularized by the Duke Ellington Orchestra in 1941 (Fig. 1). Strayhorn was a soda jerk and drugstore delivery boy by day, a musician by night. Strayhorn had played for Ellington after a show at the Stanley Theatre in Pittsburgh on December 2, 1938. After mimicking the orchestra’s version of ‘‘Sophisticated Lady,’’ Strayhorn played his own version. Ellington was so impressed, that eventually invited Strayhorn to Ellington’s home in the wealthy Sugar Hill neighborhood in Harlem, for a new job in his organization. Ellington gave Strayhorn directions to reach his house in Upper Manhattan by subway: ‘‘Take the A Train. . .’’ The need for writing a new book of composition for Ellington’s Orchestra came from the new ruling of the American Society of Composers and Publishers (ASCAP). ASCAP raised the licensing fees for broadcast use to the point that many composers – including Ellington – could no longer play their music over radio. Ellington therefore turned to his son Mercer and to Billy Strayhorn, both registered with Broadcast Music Inc., an ASCAP competitor, searching for a new repertory. Among other tunes, ‘‘Take the A Train’’ came into play. Interestingly enough, the draft was initially discarded by Strayhorn who considered it too close to Fletcher Henderson’s style, another prominent big band jazz and swing music composer. ‘‘Take the A Train’’, therefore, ended up in the trash, before Mercer Ellington found it and got it back (Smithsonian Documents Gallery, 2009). Eventually, the song became the signature opening piece for Duke Ellington and his Orchestra and, according to the National Public Radio, one of the hundred greatest songs of the 20th century. As much as Jazz and Intraoperative Neurophysiology have little in common, there is another ‘‘A Train’’ that has become quite popular over the past decade, this time among clinical neurophysiologists, especially those actively involved in intraoperative neuromonitoring. In 2000, Romstock et al. proposed a new classification system for free running EMG activity during surgery for vestibular schwannomas (Romstock et al., 2000). This classification was based on visual offline analysis of EMG tracing. Among the different patterns described in this study, the A-train – a sinusoidal, symmetrical sequence of high-frequency and low-amplitude signals (Fig. 2) – proved to be a highly reliable predictor for postoperative facial palsy. Later on, Prell et al. – from the same group of authors – looked at the correlation between the quantity of A-train activity during surgery, and the severity of postoperative facial palsy (Prell et al., 2007). By automatically adding up the time intervals
of A-train activity from the recording channels in the three main branches of the facial nerve (nasal, orbicularis oculi and orbicularis oris muscles), the ‘‘train time’’ parameter was defined. This parameter was a strong predictor of the degree of postoperative deterioration of facial nerve function, as described by the House– Brackmann scale. The automated analysis, however, was valuable as a prognostic indicator but not for intraoperative use because it was performed offline. In addition, a number of false positive and false negative results were still observed. In 2010 these same authors offered an algorithm to monitor the train activity in real time, in the operating room (Prell et al., 2010). This transposition from offline to real time analysis resulted in a very strict interpretation of EMG activity and a drastic reduction in the amount of train time, as compared to the original observations. Yet, the intraoperatively monitored train time showed a high degree of correlation with the functional outcome of the facial nerve early after surgery and in the long-term. In this study, the authors observed five false positive results, namely patients with high train time activity but only mild post-operative facial palsy, suggesting that maybe some subgroups of A-train activity might have no prognostic value and be irrelevant for facial nerve outcome. In their most recent study, Prell and coworkers started from the hypothesis that a systematic flaw in the automated analysis could be the reason for false positive results (Prell et al., 2014). Therefore, they compared automated and visual analyses of the facial nerve EMG data from 79 patients. The results confirmed that the automated analysis identified only a small fraction of the visualized A-train activity, but this fraction was nevertheless very representative and well correlated with the functional outcome. Moreover, the risk for postoperative facial palsy turned out to be reflected by an inverse sigmoid curve, which makes the use of intraoperative rigid warning thresholds more problematic. In spite of these additional findings on the correlation between A-train activity and outcome, the answer for the false positive results was not there yet. On the other hand, it was noted that in the literature similar rates of false positive results, with positive predictive values in the range of 50–60%, were reported also for the other modality of facial nerve monitoring – namely facial motor evoked potentials (MEPs). This may suggest that, following surgical stimulation, some facial nerves might be more prone than others to elicit A-trains (or to cause a drop in the MEP amplitude), without a clinical correlate. In this issue of Clinical Neurophysiology, Prell et al. provide a possible new explanation for this innocent A-train activity, based
http://dx.doi.org/10.1016/j.clinph.2015.01.002 1388-2457/Ó 2015 Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.
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Editorial / Clinical Neurophysiology 126 (2015) 1647–1649
on the hypothesis that motor fibers within the nervus intermedius, rather than the facial, nerve may account for this activity (Prell et al., 2015). Traditionally the nervus intermedius is supposed to convey visceral sensory fibers from the tongue, palate and preganglionic parasympathetic fibers to the pterygopalatine and submandibular ganglia. More recently, however, a small number of motor fibers was identified as part of the nervus intermedius. Its intraoperative stimulation elicited long-latency, low-amplitude responses which were recorded only on the perioral region (and sometimes in the perinasal region), and differed significantly from responses recorded after stimulation of the facial nerve (Alfieri et al., 2012, 2014). In this study, Prell et al. undertook a retrospective analysis of surgical videos looking for the presence of a nervus intermedius as determined either anatomically or electrophysiologically. Anatomically it is described as a bundle of neural tissue, running separately from the main portion of the facial nerve within the cerebellopontine angle and reuniting with it distally at the internal auditory meatus. Electrophysiologically it is characterized by appropriate latency and amplitude responses in perioral muscles, following stimulation in an area unrelated to the known location of the facial nerve (Ashram et al., 2005). The train time and its correlation with the outcome were then assessed for the two groups of patients, with and without an identifiable nerve intermedius. The main finding in this study is that patients with an identifiable nerve intermedius clearly had additional A-train activity, mainly in the perioral muscles, but this activity lacked correlation with the post-operative facial nerve function and turned out to be prognostically irrelevant. The possibility to identify confounding factors impairing the reliability of free running EMG activity is important and may impact substantially on the intraoperative surgical strategy when neurosurgeons handle the facial nerve during surgery for cerebello-pontine angle lesions. However, for now, the practical value of this study remains debatable because an important pre-requisite is the possibility to reliably discriminate between the two different origins (nerve intermedius versus facial nerve) of the A-train during surgery, in particular during the early stages of tumor removal. As the authors clearly stated ‘‘in an actual operative case, the sur-
Fig. 2. Examples of A-train activity of various duration and frequency (printed from Romstock et al., 2000).
geon will only have fragments of this information available when the first A-trains are observed intraoperatively. Especially with larger tumours, the anatomical situation may be distorted, and the source of A-train activity unclear. This will limit the applicability of the new information in the present study in clinical terms – at least for the time being’’. There is another aspect that suggests some caution in applying the EMG criteria suggested by Prell et al. to common neurosurgical practice. A critical issue in sciences is reproducibility of the results while, so far, data on the value of the A-train have come essentially from the same group of authors. Therefore, we look forward to confirmation of the hypotheses and results reported by Prell et al. by other groups with similar experience in vestibular schwannoma surgery. With this limitation in mind, Prell et al. should be congratulated, once again, for adding new elements to the interpretation of facial nerve EMG activity during surgery for vestibular schwannomas. In spite of the fact that this monitoring modality has been one of the first intraoperative neuromonitoring technique established as standard of care, the reliability of free running
Fig. 1. Left panel: Duke Ellington (left) and Billy Strayhorn (right) playing together around 1948. Right panel: musical notes from ‘‘Take the A Train’’.
Editorial / Clinical Neurophysiology 126 (2015) 1647–1649
EMG activity for facial nerve monitoring has been a matter of debate for many years, and it remains controversial nowadays for the other motor cranial nerves. Although several criteria have been proposed to identify EMG activity patterns suspicious for nerve injury, the terminology remains somewhat confusing. For cranial nerves other than the facial, convincing data regarding a clinical correlation between EMG activity and clinical outcome are still lacking (Grabb et al., 1997; Schlake et al., 2001). Paradoxically, the same electrical silence (no EMG activity) suggesting that no significant changes are occurring in the functional integrity of the nerve can be observed after complete section of a peripheral nerve. On the other hand, the same irritative EMG activity that persists behind the surgical manipulation of the nerve – and that is often considered indicative of a potential injury to the nerve – can be elicited by simply irrigating the surgical field with cold saline. Free running EMG still lacks sensitivity and, to a larger extent, specificity, to the point that strongly tailoring the surgical strategy on the basis of the different patterns of EMG activity may be hazardous. So called corticobulbar MEP monitoring is a technique that can be combined with free running EMG monitoring not only for the facial but also for other motor cranial nerves. So far, the experience with MEPs for facial nerve monitoring suffers a similar degree of low specificity (namely significant drop in MEP amplitude without major functional impairment) (Dong et al., 2005; Fukuda et al., 2008; Matthies et al., 2011). On the other hand, the use of MEPs for lower cranial nerve monitoring is still limited, and there is a lack of published data on the correlation with post-operative nerve function, although some preliminary experience is encouraging (Sala et al., 2004; Ito et al., 2013). Future studies will clarify the value of MEPs for cranial nerve monitoring and their reliability in comparison to free running EMG. The evidence is not there yet. Overall, free running EMG as an intraoperative monitoring modality for motor cranial nerve has been criticized, especially for a lack of specificity, but not discarded. At least for the facial nerve, the work of this group of German colleagues has, over the past fifteen years, prevented free running EMG from being discarded, and has resulted in compelling evidence for the value of this technique. Looking forward to their next achievement, we may wish their ‘‘A-train’’ the same luck as Strayhorn’s and Ellington’s one. Conflict of interest statement None.
1649
References Alfieri A, Fleischhammer J, Peschke E, Strauss C. The nervus intermedius as a variable landmark and critical structure in cerebellopontine angle surgery: an anatomical study and classification. Acta Neurochir (Wien) 2012;154:1263–8. Alfieri A, Rampp S, Strauss C, Fleischhammer J, Rachinger J, Scheller C, et al. The relationship between nervus intermedius anatomy, ultrastructure, electrophysiology, and clinical function. Usefulness in cerebellopontine microsurgery. Acta Neurochir (Wien) 2014;156:403–8. Ashram YA, Jackler RK, Pitts LH, Yingling CD. Intraoperative electrophysiologic identification of the nervus intermedius. Otol Neurotol 2005;26:274–9. Dong CC, MacDonald DB, Akagami R, Westerberg B, Alkhani A, Kanaan I, et al. Intraoperative facial motor evoked potential monitoring with transcranial electrical stimulation during skull base surgery. Clin Neurophysiol 2005;116:588–96. Fukuda M, Oishi M, Takao T, Saito A, Fujii Y. Facial nerve motor-evoked potential monitoring during skull base surgery predicts facial nerve outcome. J Neurol Neurosurg Psychiatry 2008;79:1066–70. Grabb PA, Albright L, Sclabassi RJ, Pollack IF. Continuous intraoperative electromyographic monitoring of cranial nerves during resection of fourth ventricular tumors in children. J Neurosurg 1997;86:1–4. Ito E, Ichikawa M, Itakura T, Ando H, Matsumoto Y, Oda K, et al. Motor evoked potential monitoring of the vagus nerve with transcranial electrical stimulation during skull base surgeries. J Neurosurg 2013;118:195–201. Matthies C, Raslan F, Schweitzer T, Hagen R, Roosen K, Reiners K. Facial motor evoked potentials in cerebellopontine angle surgery: technique, pitfalls and predictive value. Clin Neurol Neurosurg 2011;113:872–9. Prell J, Rachinger J, Scheller C, Alfieri A, Strauss C, Rampp S. A real-time monitoring system for the facial nerve. Neurosurgery 2010;66:1064–73. Prell J, Rampp S, Romstock J, Fahlbusch R, Strauss C. Train time as a quantitative electromyographic parameter for facial nerve function in patients undergoing surgery for vestibular schwannoma. J Neurosurg 2007;106:826–32. Prell J, Strauss C, Rachinger J, Alfieri A, Scheller C, Herfurth K, et al. Facial nerve palsy after vestibular schwannoma surgery: dynamic risk-stratification based on continuous EMG-monitoring. Clin Neurophysiol 2014;125:415–21. Prell J, Strauss C, Rachinger J, Scheller C, Alfieri A, Herfurth K et al. The intermedius nerve as a confounding variable for monitoring of the free-running electromyogram. Clin Neurophysiol 2015;126:1833–9. Romstock J, Strauss C, Fahlbusch R. Continuous electromyography monitoring of motor cranial nerves during cerebellopontine angle surgery. J Neurosurg 2000;93:586–93. Sala F, Lanteri P, Bricolo A. Intraoperative neurophysiological monitoring of motor evoked potentials during brain stem and spinal cord surgery. In: Pickard JD (Editor in Chief), Dolenc VV, Lobo Antunes J, Reulen HJ, Sindou M, Strong AJ et al. (Eds.), Advanced and technical standards in neurosurgery, vol. 29; 2004. pp. 133–169. Schlake HP, Goldbrunner RH, Milewski C, Krauss J, Trautner H, Behr R, et al. Intraoperative electromyographic monitoring of the lower cranial motor nerves (LCN IX–XII) in skull base surgery. Clin Neurol Neurosurg 2001;103:72–82. Smithsonian Documents Gallery. April 4–June 28, 2009. Duke Ellington and Billy Strayhorn, Jazz Composers: Take the ‘‘A’’ Train, p. 6.
Francesco Sala Section of Neurosurgery, Department of Neurological and Movement Sciences, University of Verona, Italy Available online 16 January 2015
Contents lists available at ScienceDirect
Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Editorial
Take the A Train See Article, pages 1833–1839
Bill Strayhorn’s tune ‘‘Take the A Train’’, one of the jazz standard of all times, was composed in 1939, and then popularized by the Duke Ellington Orchestra in 1941 (Fig. 1). Strayhorn was a soda jerk and drugstore delivery boy by day, a musician by night. Strayhorn had played for Ellington after a show at the Stanley Theatre in Pittsburgh on December 2, 1938. After mimicking the orchestra’s version of ‘‘Sophisticated Lady,’’ Strayhorn played his own version. Ellington was so impressed, that eventually invited Strayhorn to Ellington’s home in the wealthy Sugar Hill neighborhood in Harlem, for a new job in his organization. Ellington gave Strayhorn directions to reach his house in Upper Manhattan by subway: ‘‘Take the A Train. . .’’ The need for writing a new book of composition for Ellington’s Orchestra came from the new ruling of the American Society of Composers and Publishers (ASCAP). ASCAP raised the licensing fees for broadcast use to the point that many composers – including Ellington – could no longer play their music over radio. Ellington therefore turned to his son Mercer and to Billy Strayhorn, both registered with Broadcast Music Inc., an ASCAP competitor, searching for a new repertory. Among other tunes, ‘‘Take the A Train’’ came into play. Interestingly enough, the draft was initially discarded by Strayhorn who considered it too close to Fletcher Henderson’s style, another prominent big band jazz and swing music composer. ‘‘Take the A Train’’, therefore, ended up in the trash, before Mercer Ellington found it and got it back (Smithsonian Documents Gallery, 2009). Eventually, the song became the signature opening piece for Duke Ellington and his Orchestra and, according to the National Public Radio, one of the hundred greatest songs of the 20th century. As much as Jazz and Intraoperative Neurophysiology have little in common, there is another ‘‘A Train’’ that has become quite popular over the past decade, this time among clinical neurophysiologists, especially those actively involved in intraoperative neuromonitoring. In 2000, Romstock et al. proposed a new classification system for free running EMG activity during surgery for vestibular schwannomas (Romstock et al., 2000). This classification was based on visual offline analysis of EMG tracing. Among the different patterns described in this study, the A-train – a sinusoidal, symmetrical sequence of high-frequency and low-amplitude signals (Fig. 2) – proved to be a highly reliable predictor for postoperative facial palsy. Later on, Prell et al. – from the same group of authors – looked at the correlation between the quantity of A-train activity during surgery, and the severity of postoperative facial palsy (Prell et al., 2007). By automatically adding up the time intervals
of A-train activity from the recording channels in the three main branches of the facial nerve (nasal, orbicularis oculi and orbicularis oris muscles), the ‘‘train time’’ parameter was defined. This parameter was a strong predictor of the degree of postoperative deterioration of facial nerve function, as described by the House– Brackmann scale. The automated analysis, however, was valuable as a prognostic indicator but not for intraoperative use because it was performed offline. In addition, a number of false positive and false negative results were still observed. In 2010 these same authors offered an algorithm to monitor the train activity in real time, in the operating room (Prell et al., 2010). This transposition from offline to real time analysis resulted in a very strict interpretation of EMG activity and a drastic reduction in the amount of train time, as compared to the original observations. Yet, the intraoperatively monitored train time showed a high degree of correlation with the functional outcome of the facial nerve early after surgery and in the long-term. In this study, the authors observed five false positive results, namely patients with high train time activity but only mild post-operative facial palsy, suggesting that maybe some subgroups of A-train activity might have no prognostic value and be irrelevant for facial nerve outcome. In their most recent study, Prell and coworkers started from the hypothesis that a systematic flaw in the automated analysis could be the reason for false positive results (Prell et al., 2014). Therefore, they compared automated and visual analyses of the facial nerve EMG data from 79 patients. The results confirmed that the automated analysis identified only a small fraction of the visualized A-train activity, but this fraction was nevertheless very representative and well correlated with the functional outcome. Moreover, the risk for postoperative facial palsy turned out to be reflected by an inverse sigmoid curve, which makes the use of intraoperative rigid warning thresholds more problematic. In spite of these additional findings on the correlation between A-train activity and outcome, the answer for the false positive results was not there yet. On the other hand, it was noted that in the literature similar rates of false positive results, with positive predictive values in the range of 50–60%, were reported also for the other modality of facial nerve monitoring – namely facial motor evoked potentials (MEPs). This may suggest that, following surgical stimulation, some facial nerves might be more prone than others to elicit A-trains (or to cause a drop in the MEP amplitude), without a clinical correlate. In this issue of Clinical Neurophysiology, Prell et al. provide a possible new explanation for this innocent A-train activity, based
http://dx.doi.org/10.1016/j.clinph.2015.01.002 1388-2457/Ó 2015 Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.
1648
Editorial / Clinical Neurophysiology 126 (2015) 1647–1649
on the hypothesis that motor fibers within the nervus intermedius, rather than the facial, nerve may account for this activity (Prell et al., 2015). Traditionally the nervus intermedius is supposed to convey visceral sensory fibers from the tongue, palate and preganglionic parasympathetic fibers to the pterygopalatine and submandibular ganglia. More recently, however, a small number of motor fibers was identified as part of the nervus intermedius. Its intraoperative stimulation elicited long-latency, low-amplitude responses which were recorded only on the perioral region (and sometimes in the perinasal region), and differed significantly from responses recorded after stimulation of the facial nerve (Alfieri et al., 2012, 2014). In this study, Prell et al. undertook a retrospective analysis of surgical videos looking for the presence of a nervus intermedius as determined either anatomically or electrophysiologically. Anatomically it is described as a bundle of neural tissue, running separately from the main portion of the facial nerve within the cerebellopontine angle and reuniting with it distally at the internal auditory meatus. Electrophysiologically it is characterized by appropriate latency and amplitude responses in perioral muscles, following stimulation in an area unrelated to the known location of the facial nerve (Ashram et al., 2005). The train time and its correlation with the outcome were then assessed for the two groups of patients, with and without an identifiable nerve intermedius. The main finding in this study is that patients with an identifiable nerve intermedius clearly had additional A-train activity, mainly in the perioral muscles, but this activity lacked correlation with the post-operative facial nerve function and turned out to be prognostically irrelevant. The possibility to identify confounding factors impairing the reliability of free running EMG activity is important and may impact substantially on the intraoperative surgical strategy when neurosurgeons handle the facial nerve during surgery for cerebello-pontine angle lesions. However, for now, the practical value of this study remains debatable because an important pre-requisite is the possibility to reliably discriminate between the two different origins (nerve intermedius versus facial nerve) of the A-train during surgery, in particular during the early stages of tumor removal. As the authors clearly stated ‘‘in an actual operative case, the sur-
Fig. 2. Examples of A-train activity of various duration and frequency (printed from Romstock et al., 2000).
geon will only have fragments of this information available when the first A-trains are observed intraoperatively. Especially with larger tumours, the anatomical situation may be distorted, and the source of A-train activity unclear. This will limit the applicability of the new information in the present study in clinical terms – at least for the time being’’. There is another aspect that suggests some caution in applying the EMG criteria suggested by Prell et al. to common neurosurgical practice. A critical issue in sciences is reproducibility of the results while, so far, data on the value of the A-train have come essentially from the same group of authors. Therefore, we look forward to confirmation of the hypotheses and results reported by Prell et al. by other groups with similar experience in vestibular schwannoma surgery. With this limitation in mind, Prell et al. should be congratulated, once again, for adding new elements to the interpretation of facial nerve EMG activity during surgery for vestibular schwannomas. In spite of the fact that this monitoring modality has been one of the first intraoperative neuromonitoring technique established as standard of care, the reliability of free running
Fig. 1. Left panel: Duke Ellington (left) and Billy Strayhorn (right) playing together around 1948. Right panel: musical notes from ‘‘Take the A Train’’.
Editorial / Clinical Neurophysiology 126 (2015) 1647–1649
EMG activity for facial nerve monitoring has been a matter of debate for many years, and it remains controversial nowadays for the other motor cranial nerves. Although several criteria have been proposed to identify EMG activity patterns suspicious for nerve injury, the terminology remains somewhat confusing. For cranial nerves other than the facial, convincing data regarding a clinical correlation between EMG activity and clinical outcome are still lacking (Grabb et al., 1997; Schlake et al., 2001). Paradoxically, the same electrical silence (no EMG activity) suggesting that no significant changes are occurring in the functional integrity of the nerve can be observed after complete section of a peripheral nerve. On the other hand, the same irritative EMG activity that persists behind the surgical manipulation of the nerve – and that is often considered indicative of a potential injury to the nerve – can be elicited by simply irrigating the surgical field with cold saline. Free running EMG still lacks sensitivity and, to a larger extent, specificity, to the point that strongly tailoring the surgical strategy on the basis of the different patterns of EMG activity may be hazardous. So called corticobulbar MEP monitoring is a technique that can be combined with free running EMG monitoring not only for the facial but also for other motor cranial nerves. So far, the experience with MEPs for facial nerve monitoring suffers a similar degree of low specificity (namely significant drop in MEP amplitude without major functional impairment) (Dong et al., 2005; Fukuda et al., 2008; Matthies et al., 2011). On the other hand, the use of MEPs for lower cranial nerve monitoring is still limited, and there is a lack of published data on the correlation with post-operative nerve function, although some preliminary experience is encouraging (Sala et al., 2004; Ito et al., 2013). Future studies will clarify the value of MEPs for cranial nerve monitoring and their reliability in comparison to free running EMG. The evidence is not there yet. Overall, free running EMG as an intraoperative monitoring modality for motor cranial nerve has been criticized, especially for a lack of specificity, but not discarded. At least for the facial nerve, the work of this group of German colleagues has, over the past fifteen years, prevented free running EMG from being discarded, and has resulted in compelling evidence for the value of this technique. Looking forward to their next achievement, we may wish their ‘‘A-train’’ the same luck as Strayhorn’s and Ellington’s one. Conflict of interest statement None.
1649
References Alfieri A, Fleischhammer J, Peschke E, Strauss C. The nervus intermedius as a variable landmark and critical structure in cerebellopontine angle surgery: an anatomical study and classification. Acta Neurochir (Wien) 2012;154:1263–8. Alfieri A, Rampp S, Strauss C, Fleischhammer J, Rachinger J, Scheller C, et al. The relationship between nervus intermedius anatomy, ultrastructure, electrophysiology, and clinical function. Usefulness in cerebellopontine microsurgery. Acta Neurochir (Wien) 2014;156:403–8. Ashram YA, Jackler RK, Pitts LH, Yingling CD. Intraoperative electrophysiologic identification of the nervus intermedius. Otol Neurotol 2005;26:274–9. Dong CC, MacDonald DB, Akagami R, Westerberg B, Alkhani A, Kanaan I, et al. Intraoperative facial motor evoked potential monitoring with transcranial electrical stimulation during skull base surgery. Clin Neurophysiol 2005;116:588–96. Fukuda M, Oishi M, Takao T, Saito A, Fujii Y. Facial nerve motor-evoked potential monitoring during skull base surgery predicts facial nerve outcome. J Neurol Neurosurg Psychiatry 2008;79:1066–70. Grabb PA, Albright L, Sclabassi RJ, Pollack IF. Continuous intraoperative electromyographic monitoring of cranial nerves during resection of fourth ventricular tumors in children. J Neurosurg 1997;86:1–4. Ito E, Ichikawa M, Itakura T, Ando H, Matsumoto Y, Oda K, et al. Motor evoked potential monitoring of the vagus nerve with transcranial electrical stimulation during skull base surgeries. J Neurosurg 2013;118:195–201. Matthies C, Raslan F, Schweitzer T, Hagen R, Roosen K, Reiners K. Facial motor evoked potentials in cerebellopontine angle surgery: technique, pitfalls and predictive value. Clin Neurol Neurosurg 2011;113:872–9. Prell J, Rachinger J, Scheller C, Alfieri A, Strauss C, Rampp S. A real-time monitoring system for the facial nerve. Neurosurgery 2010;66:1064–73. Prell J, Rampp S, Romstock J, Fahlbusch R, Strauss C. Train time as a quantitative electromyographic parameter for facial nerve function in patients undergoing surgery for vestibular schwannoma. J Neurosurg 2007;106:826–32. Prell J, Strauss C, Rachinger J, Alfieri A, Scheller C, Herfurth K, et al. Facial nerve palsy after vestibular schwannoma surgery: dynamic risk-stratification based on continuous EMG-monitoring. Clin Neurophysiol 2014;125:415–21. Prell J, Strauss C, Rachinger J, Scheller C, Alfieri A, Herfurth K et al. The intermedius nerve as a confounding variable for monitoring of the free-running electromyogram. Clin Neurophysiol 2015;126:1833–9. Romstock J, Strauss C, Fahlbusch R. Continuous electromyography monitoring of motor cranial nerves during cerebellopontine angle surgery. J Neurosurg 2000;93:586–93. Sala F, Lanteri P, Bricolo A. Intraoperative neurophysiological monitoring of motor evoked potentials during brain stem and spinal cord surgery. In: Pickard JD (Editor in Chief), Dolenc VV, Lobo Antunes J, Reulen HJ, Sindou M, Strong AJ et al. (Eds.), Advanced and technical standards in neurosurgery, vol. 29; 2004. pp. 133–169. Schlake HP, Goldbrunner RH, Milewski C, Krauss J, Trautner H, Behr R, et al. Intraoperative electromyographic monitoring of the lower cranial motor nerves (LCN IX–XII) in skull base surgery. Clin Neurol Neurosurg 2001;103:72–82. Smithsonian Documents Gallery. April 4–June 28, 2009. Duke Ellington and Billy Strayhorn, Jazz Composers: Take the ‘‘A’’ Train, p. 6.
Francesco Sala Section of Neurosurgery, Department of Neurological and Movement Sciences, University of Verona, Italy Available online 16 January 2015