Evidence map›Paper›PMID 40194594›Full record

ArticleBrain stimulation

Personalized models of Beam/F3 targeting in transcranial magnetic stimulation for depression: Implications for precision clinical translation.

Divya Rajasekharan, Michelle R Madore, Paul Holtzheimer, Kelvin O Lim, Leanne M Williams, Noah S Philip

Abstract read
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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. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Divya RajasekharanDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd, Stanford, CA 94305, USA; Mental Illness Research, Education and Clinical Center, VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, CA 94304, USA. Electronic address: rdivya@stanford.edu.
Michelle R MadoreDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd, Stanford, CA 94305, USA; Mental Illness Research, Education and Clinical Center, VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, CA 94304, USA. Electronic address: mmadore@stanford.edu.
Paul HoltzheimerGeisel School of Medicine at Dartmouth, Hanover, NH, 03755, USA; National Center for PTSD, VA Medical Center, U.S. Department of Veterans Affairs, 215 N Main St, White River Junction, VT 05009, USA. Electronic address: paul.holtzheimer@dartmouth.edu.
Kelvin O LimDepartment of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, 55455, USA; Minneapolis VA Health Care System, 1 Veterans Drive, Minneapolis, MN 55417, USA. Electronic address: kolim@umn.edu.
Leanne M WilliamsDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd, Stanford, CA 94305, USA; Mental Illness Research, Education and Clinical Center, VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, CA 94304, USA. Electronic address: leawilliams@stanford.edu.
Noah S PhilipDepartment of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, 02903, USA; Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, 830 Chalkstone Ave, Providence, RI 02908, USA. Electronic address: noah_philip@brown.edu.

Funding

Mechanistic circuit markers of transcranial magnetic stimulation outcomes in pharmacoresistant depressionR01MH120126 · NIMH · STANFORD UNIVERSITY · PI WILLIAMS, LEANNE · 2019 to 2023
$3.4M
NIMH NIH HHS R01 MH120126RRD VA I50 RX002864
6 · The paper itself

Abstract

backgroundClinical transcranial magnetic stimulation (TMS) for depression routinely relies on the scalp-based Beam/F3 targeting method to identify stimulation targets in the dorsolateral prefrontal cortex (dLPFC). Scalp-based targeting offers a low-cost and easily implemented method for TMS coil placement, enhancing treatment availability. However, limited anatomical and functional specificity of the Beam/F3 method may affect treatment outcomes, motivating assessment of the clinical standard.

methodsIn a naturalistic clinical trial of TMS conduced at four Veterans Affairs hospitals, the authors evaluate the Beam/F3 method using neuroimaging incorporated before TMS, after five treatment sessions, and after all thirty sessions. Personalized anatomical and electric field (E-field) models were developed to assess target location and network engagement, as well as subsequent effects on clinical outcomes.

resultsAnatomical models demonstrate that the Beam/F3 method produced reliable targets in the dLPFC across individuals and repeated treatment sessions. E-field models revealed that baseline anticorrelation between the stimulation center and the sgACC was associated with antidepressant symptom response after five TMS sessions (p=0.032,r

conclusionsThis work establishes that scalp-based targeting can produce reliable targets in the dLPFC and be successfully evaluated using a combination of neuroimaging and E-field modeling in pragmatic, multisite applications. Importantly, this investigation also found that significant network effects occur early in treatment and that Beam/F3 targets can engage functional mechanisms in TMS.

Indexed as

DepressionDorsolateral Prefrontal CortexMajor Depressive DisorderTranscranial Magnetic StimulationAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPrecision MedicineTranslational Research, BiomedicalBeam/F3DepressiondLPFCE-fieldModelingsgACCTMS

Identifiers

PMID40194594
PMCPMC12119053

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.