Jonna Meincke1, Manuel Hewitt1, Giorgi Batsikadze1, David Liebetanz2. 1. Department of Clinical Neurophysiology, Georg August University of Göttingen, University Medical Center, 37075 Göttingen, Germany. 2. Department of Clinical Neurophysiology, Georg August University of Göttingen, University Medical Center, 37075 Göttingen, Germany. Electronic address: dliebet@gwdg.de.
Abstract
BACKGROUND: Although neuronavigation is increasingly used for optimizing coil positioning, the inter-session reliability of hotspot location remains unsatisfactory, probably due to the variability of motor evoked potentials (MEPs) and residual investigator bias. PURPOSE: To increase the reliability and accuracy of hotspot location we introduce a novel automated hotspot-hunting procedure (AHH). METHODS: AHH is based on resting motor thresholds (RMTs) instead of MEP amplitudes. By combining robotic coil positioning with a closed loop target search algorithm AHH runs independently from the investigator. AHH first identifies all targets with an RMT below a defined intensity of stimulator output (MEP-positive) and then locates the motor hotspot of a target muscle by measuring RMTs at all identified MEP-positive targets. Results were compared to robotic MEP amplitude TMS mapping (MAM) using a 7×7 predefined target grid and suprathreshold intensities and manual hotspot search (MHS). Sequence of stimulation was randomized from pulse to pulse in AHH and MAM. Each procedure was tested in 8 subjects. RESULTS: Inter-session CoG shift was significantly reduced with AHH (1.4mm (SEM: 0.4)) as compared to MAM (7.0mm (SEM: 1.8)) (p=0.018) and MHS (9.6mm (SEM: 2.2)) (p=0.007). No statistical difference was observed between MAM and MHS. RMTs were reliable between sessions. CONCLUSION: Our method represents the first fully automated, i.e. investigator-independent, TMS hotspot-hunting procedure. Measuring RMTs instead of MEP amplitudes leads to significantly increased accuracy and reliability of CoG locations. Moreover, by assessing thresholds AHH is the first procedure to fulfill the original hotspot definition.
BACKGROUND: Although neuronavigation is increasingly used for optimizing coil positioning, the inter-session reliability of hotspot location remains unsatisfactory, probably due to the variability of motor evoked potentials (MEPs) and residual investigator bias. PURPOSE: To increase the reliability and accuracy of hotspot location we introduce a novel automated hotspot-hunting procedure (AHH). METHODS: AHH is based on resting motor thresholds (RMTs) instead of MEP amplitudes. By combining robotic coil positioning with a closed loop target search algorithm AHH runs independently from the investigator. AHH first identifies all targets with an RMT below a defined intensity of stimulator output (MEP-positive) and then locates the motor hotspot of a target muscle by measuring RMTs at all identified MEP-positive targets. Results were compared to robotic MEP amplitude TMS mapping (MAM) using a 7×7 predefined target grid and suprathreshold intensities and manual hotspot search (MHS). Sequence of stimulation was randomized from pulse to pulse in AHH and MAM. Each procedure was tested in 8 subjects. RESULTS: Inter-session CoG shift was significantly reduced with AHH (1.4mm (SEM: 0.4)) as compared to MAM (7.0mm (SEM: 1.8)) (p=0.018) and MHS (9.6mm (SEM: 2.2)) (p=0.007). No statistical difference was observed between MAM and MHS. RMTs were reliable between sessions. CONCLUSION: Our method represents the first fully automated, i.e. investigator-independent, TMS hotspot-hunting procedure. Measuring RMTs instead of MEP amplitudes leads to significantly increased accuracy and reliability of CoG locations. Moreover, by assessing thresholds AHH is the first procedure to fulfill the original hotspot definition.
Authors: Stefan M Goetz; S M Mahdi Alavi; Zhi-De Deng; Angel V Peterchev Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2019-07-03 Impact factor: 3.802
Authors: Simone Rossi; Andrea Antal; Sven Bestmann; Marom Bikson; Carmen Brewer; Jürgen Brockmöller; Linda L Carpenter; Massimo Cincotta; Robert Chen; Jeff D Daskalakis; Vincenzo Di Lazzaro; Michael D Fox; Mark S George; Donald Gilbert; Vasilios K Kimiskidis; Giacomo Koch; Risto J Ilmoniemi; Jean Pascal Lefaucheur; Letizia Leocani; Sarah H Lisanby; Carlo Miniussi; Frank Padberg; Alvaro Pascual-Leone; Walter Paulus; Angel V Peterchev; Angelo Quartarone; Alexander Rotenberg; John Rothwell; Paolo M Rossini; Emiliano Santarnecchi; Mouhsin M Shafi; Hartwig R Siebner; Yoshikatzu Ugawa; Eric M Wassermann; Abraham Zangen; Ulf Ziemann; Mark Hallett Journal: Clin Neurophysiol Date: 2020-10-24 Impact factor: 4.861