Evidence map›Paper›PMID 36031059›Full record

ArticleBrain stimulation

Neuronavigation maximizes accuracy and precision in TMS positioning: Evidence from 11,230 distance, angle, and electric field modeling measurements.

Kevin A Caulfield, Holly H Fleischmann, Claire E Cox, Julia P Wolf, Mark S George, Lisa M McTeague

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Brain stimulation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07278206 (Mitigating Cognitive Problems and Fatigue With Brain Stimulation in Long COVID), which is not on this map. Cited by 63 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 3 pooled it
9.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07278206 narecruitingnot on this map

Mitigating Cognitive Problems and Fatigue With Brain Stimulation in Long COVID

TypeinterventionalSponsorAmsterdam UMC, location VUmcRan2025 to 2029Enrolled66ConditionsLong COVID, PASC Post Acute Sequelae of COVID 19, Post COVID-19 Condition (PCC)ArmsRepetitive Transcranial Magnetic Stimulation, Sham device
3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 3 syntheses or guidelines pooled it, 121 citations in OpenAlex.

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  16. Clinical utility and prospective of TMS-EEG: Updated review from an international expert group.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
    Review
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3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Kevin A CaulfieldDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA. Electronic address: caulfiel@musc.edu.
Holly H FleischmannDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Department of Psychology, University of Georgia, Athens, GA, USA.
Claire E CoxDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA.
Julia P WolfDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA.
Mark S GeorgeDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA.
Lisa M McTeagueDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA.
Medical University of South Carolina · US

Funding

Treating Depression and Enhancing Locomotor Recovery Post-strokeP20GM109040 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KAUTZ, STEVEN A. · 2014 to 2024
$23.5M
Techniques DevelopmentP2CHD086844 · NICHD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KAUTZ, STEVEN A. · 2015 to 2024
$12.7M
Personalizing tDCS Dose in Healthy Adults and Chronic Ischemic StrokeF31NS126019 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI CAULFIELD, KEVIN A. · 2022 to 2023
$81k
NICHD NIH HHS P2C HD086844NIGMS NIH HHS P20 GM109040NINDS NIH HHS F31 NS126019
6 · The paper itself

Abstract

backgroundResearchers and clinicians have traditionally relied on elastic caps with markings to reposition the transcranial magnetic stimulation (TMS) coil between trains and sessions. Newer neuronavigation technology co-registers the patient's head and structural magnetic resonance imaging (MRI) scan, providing the researcher with real-time feedback about how to adjust the coil to be on-target. However, there has been no head to head comparison of accuracy and precision across treatment sessions.

objective/Hypothesis: In this two-part study, we compared elastic cap and neuronavigation targeting methodologies on distance, angle, and electric field (E-field) magnitude values.

methodsIn 42 participants receiving up to 50 total accelerated rTMS sessions in 5 days, we compared cap and neuronavigation targeting approaches in 3408 distance and 6816 angle measurements. In Experiment 1, TMS administrators saved an on-target neuronavigation location at Beam F3, which served as the landmark for all other measurements. Next, the operators placed the TMS coil based on cap markings or neuronavigation software to measure the distance and angle differences from the on-target sample. In Experiment 2, we saved each XYZ coordinate of the TMS coil from cap and neuronavigation targeting in 12 participants to compare the E-field magnitude differences at the cortical prefrontal target in 1106 cap and neuronavigation models.

resultsCap targeting was significantly off-target for distance, placing the coil an average of 10.66 mm off-target (Standard error of the mean; SEM = 0.19 mm) compared to 0.3 mm (SEM = 0.03 mm) for neuronavigation (p < 0.0001). Cap targeting also significantly deviated for angles off-target, averaging 7.79 roll/pitch degrees (SEM = 1.07°) off-target and 5.99 yaw degrees (SEM = 0.12°) off-target; in comparison, neuronavigation targeting positioned the coil 0.34 roll/pitch degrees (SEM = 0.01°) and 0.22 yaw (SEM = 0.004°) off-target (both p < 0.0001). Further analyses revealed that there were significant inter-operator differences on distance and angle positioning for F3 (all p < 0.05), but not neuronavigation. Lastly, cap targeting resulted in significantly lower E-fields at the intended prefrontal cortical target, with equivalent E-fields as 110.7% motor threshold (MT; range = 58.3-127.4%) stimulation vs. 119.9% MT (range = 115-123.3%) from neuronavigated targeting with 120% MT stimulation applied (p < 0.001).

conclusionsCap-based targeting is an inherent source of target variability compared to neuronavigation. Additionally, cap-based coil placement is more prone to differences across operators. Off-target coil placement secondary to cap-based measurements results in significantly lower amounts of stimulation reaching the cortical target, with some individuals receiving only 48.6% of the intended on-target E-field. Neuronavigation technology enables more precise and accurate TMS positioning, resulting in the intended stimulation intensities at the targeted cortical level.

Indexed as

NeuronavigationTranscranial Magnetic StimulationHumansMagnetic Resonance ImagingPrefrontal CortexSoftwareDorsolateral prefrontal cortex (DLPFC)Elastic cap targetingElectric field (E-field) modelingNeuronavigated rTMSNeuronavigationTranscranial magnetic stimulation

Identifiers

PMID36031059
PMCPMC10026380
OpenAlexW4293512447

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.