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  Accuracy and precision of navigated transcranial magnetic stimulation

Nieminen, A. E., Nieminen, J. O., Stenroos, M., Novikov, P., Nazarova, M., Vaalto, S., et al. (2022). Accuracy and precision of navigated transcranial magnetic stimulation. Journal of Neural Engineering, 19: 6. doi:10.1088/1741-2552/aca71a.

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Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-000B-F1E9-E Versions-Permalink: https://hdl.handle.net/21.11116/0000-000C-F0C2-9
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 Urheber:
Nieminen, Aino E1, Autor
Nieminen, Jaakko O.1, Autor
Stenroos, Matti1, Autor
Novikov, Pavel2, Autor
Nazarova, Maria2, Autor
Vaalto, Selja1, Autor
Nikulin, Vadim V.3, Autor                 
Ilmoniemi, Risto J.1, Autor
Affiliations:
1Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland, ou_persistent22              
2National Research University Higher School of Economics, Moscow, Russia, ou_persistent22              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Schlagwörter: TMS; Accuracy; Coregistration; Neuronavigation; Precision; Transcranial magnetic stimulation
 Zusammenfassung: Objective: Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil–head coregistration and the estimated E-field. Approach: By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models. Main results: Average total coregistration accuracies were in the range of 2.2–3.6 mm and 1°; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5–1.9 mm / 0.2–0.4° and precisions 0.5–0.8 mm / 0.1–0.2° better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5–5.0 mm, 0.9–4.8°, and 4.4–8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm / 15° / 25% to about 2 mm / 2° / 5% when increasing realism of the E-field model. Significance: The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.

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Sprache(n): eng - English
 Datum: 2022-09-072022-04-252022-11-292022-11-29
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1088/1741-2552/aca71a
PMID: 36541458
 Art des Abschluß: -

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Projektname : -
Grant ID : 294625; 306845; 327326
Förderprogramm : -
Förderorganisation : Finnish Cultural Foundation, Academy of Finland
Projektname : -
Grant ID : 810377
Förderprogramm : Horizon 2020
Förderorganisation : European Research Council (ERC)
Projektname : -
Grant ID : 1R01NS112183-01A1
Förderprogramm : -
Förderorganisation : NIH Brain Initiative Biology and Biophysics of Neural Stimulation and Recording Technologies
Projektname : -
Grant ID : -
Förderprogramm : -
Förderorganisation : Instrumentarium Science Foundation
Projektname : -
Grant ID : -
Förderprogramm : Basic Research Program
Förderorganisation : HSE University
Projektname : -
Grant ID : -
Förderprogramm : Aalto AScI Visiting Researcher Programme
Förderorganisation : -

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Titel: Journal of Neural Engineering
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Bristol : Institute of Physics Publishing
Seiten: - Band / Heft: 19 Artikelnummer: 6 Start- / Endseite: - Identifikator: ISSN: 1741-2552
CoNE: https://pure.mpg.de/cone/journals/resource/17412552