Automated optimization of TMS coil placement for personalized functional network engagement

Lynch, Charles J.; Elbau, Immanuel; Ng, Tommy Hock Beng; Wolk, Danielle; Zhu, Shasha; Ayaz, Aliza; Power, Jonathan D.; Zebley, Benjamin; Gunning, Faith M.; Liston, Conor

doi:10.1016/j.neuron.2022.08.012

Cited by 58 publications

(56 citation statements)

References 103 publications

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“…In this work, we showed that given a target of interest, computational optimization can be used maximize the E-field delivery to the target. More sophisticated algorithms have been proposed to combine individual functional connectivity patterns, and E-field optimization, to determine coil placements that would not only maximize local stimulation, but also account for downstream effects of TMS, i.e., to maximize brain network engagement [58, 59, 60, 61]. Systematic clinical trials are needed to prospectively compare the antidepressant efficacy of these strategies in adults and adolescents.…”

Section: Discussionmentioning

confidence: 99%

Comparison of coil placement approaches targeting dorsolateral prefrontal cortex in depressed adolescents receiving repetitive transcranial magnetic stimulation: an electric field modeling study

Deng¹,

Robins²,

Dannhauer³

et al. 2023

Preprint

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Background: A promising treatment option for adolescents with treatment-resistant depression is high-frequency repetitive transcranial magnetic stimulation (rTMS) delivered to the left dorsolateral prefrontal cortex (L-DLPFC). Conventional coil placement strategies for rTMS in adults include the 5-cm rule, the Beam F3 method, and the magnetic resonance imaging (MRI) neuronavigation method. The purpose of this study was to compare the three targeting approaches to a computational E-field optimization coil placement method in depressed adolescents. Methods: Ten consenting and assenting depressed adolescents (4 females, age: 15.9 +/- 1.1) participated in an open-label rTMS treatment study. Participants were offered MRI-guided rTMS 5 times per week over 6 to 8 weeks. To compute the induced E-field, a head model was generated based on MRI images, and a figure-8 TMS coil (Neuronetics) was placed over the L-DLPFC using the four targeting approaches. Results: Results show that there was a significant difference in the induced E-field at the L-DLPFC between the four targeting methods (chi-squared = 24.7, p < 0.001). Post hoc pairwise comparisons show that there was a significant difference between any two of the targeting methods (Holm adjusted p < 0.05), with the 5-cm rule producing the weakest E-field (46.0 +/- 17.4 V/m), followed by the F3 method (87.4 +/- 35.4 V/m), followed by the MRI-guided (112.1 +/-14.6 V/m), and followed by the computationally optimized method (130.1 +/- 18.1 V/m). The Bartlett test of homogeneity of variances show that there was a significant difference in sample variance between the groups (K^2 = 8.0, p < 0.05), with F3 having the largest variance. In participants who completed the full course of treatment, the median E-field strength in the L-DLPFC was correlated with the change in depression severity (r = -0.77, p < 0.05). Conclusions: The E-field models revealed inadequacies of scalp-based targeting methods compared to MRI-guidance. Computational optimization may further enhance E-field dose delivery to the treatment target.

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Section: Discussionmentioning

confidence: 99%

Comparison of coil placement approaches targeting dorsolateral prefrontal cortex in depressed adolescents receiving repetitive transcranial magnetic stimulation: an electric field modeling study

Deng¹,

Robins²,

Dannhauer³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…When TMS is applied in this way, however, different functional networks are stimulated across individuals, and often multiple functionally discrete networks are simultaneously targeted within an individual. 1 If the efficacy of TMS depends on engaging specific functional networks underlying a patient’s symptoms, widely used “one-size-fits-all” targeting approaches are unlikely to selectively engage any specific functional network across patients, which might prevent TMS from reaching its full therapeutic potential.…”

Section: Before You Beginmentioning

confidence: 99%

“…16 ) was empirically validated by 17 and found by our group to improve the reliability of resting-state FC measurements and functional network maps. 1 , 18 Other denoising algorithms, such as ICA-AROMA, 19 can be used instead in the case of single-echo data. Manually review and revise ICA component classifications if necessary following the criteria described in.…”

Section: Before You Beginmentioning

confidence: 99%

“…Previous work indicates that acquiring 30 or more minutes of resting-state multi-echo fMRI data per-subject can help ensure reliable mapping of individual-specific functional neuroanatomy for individualized TMS targeting. 1 , 18 Note: Code for performing PFM in this way is maintained in the same online repository containing TANS ( https://github.com/cjl2007/Targeted-Functional-Network-Stimulation/tree/main/PFM ). …”

Section: Before You Beginmentioning

confidence: 99%

Section: Before You Beginmentioning

confidence: 99%

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Precision mapping and transcranial magnetic stimulation of individual-specific functional brain networks in humans

et al. 2023

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Repetitive Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations in Schizophrenia

Hua,

Wang,

et al. 2024

JAMA Netw Open

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ImportanceAuditory verbal hallucinations (AVH) are a common symptom of schizophrenia, increasing the patient’s risks of suicide and violence. Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment for AVH.ObjectiveTo investigate the effect of imaging-navigated rTMS on AVH in patients with schizophrenia.Design, Setting, and ParticipantsThis 6-week, double-blind, sham-controlled, randomized clinical trial was performed at the Anhui Mental Health Center, Hefei, China, from September 1, 2016, to August 31, 2021. Participants included 66 patients with AVH and schizophrenia. Data were analyzed from May 1, 2022, to March 31, 2023.InterventionsParticipants were randomly assigned 1:1 to either imaging-navigated active or sham rTMS over the left temporoparietal junction for 2 weeks.Main Outcomes and MeasuresThe primary outcome measured improvements in AVH from baseline to week 2 and week 6 using the Auditory Hallucination Rating Scale (AHRS) scores. In addition, the TMS-induced electric field strength was used to estimate improvements in AVH as a secondary outcome.ResultsA total of 62 participants (33 women [53%]; mean [SD] age, 27.4 [9.2] years) completed the 2-week treatments. Of these, 32 were randomized to the active rTMS group (18 women [56%]; mean [SD] age, 26.9 [9.2] years) and 30 to the sham treatment group (15 women [50%]; mean [SD] age, 27.8 [9.4] years). In the intention-to-treat analyses, patients receiving active rTMS showed a significantly greater reduction in AHRS scores compared with those receiving sham treatment at week 2 (difference, 5.96 [95% CI, 3.42-8.50]; t = 4.61; P &lt; .001; Cohen d, 1.17 [95% CI, 0.62-1.71]). These clinical effects were sustained at week 6. Additionally, a stronger TMS-induced electric field within a predefined AVH brain network was associated with greater reductions in AHRS scores (B = 3.12; t = 3.58; P = .002). No serious adverse event was observed.Conclusions and RelevanceThe findings of this randomized clinical trial suggest that imaging-navigated rTMS may effectively and safely alleviate AVH in patients with schizophrenia. Findings also suggest that the electric field strength in the individualized AVH network is a vital parameter for optimizing the efficacy of the rTMS protocol.Trial RegistrationClinicalTrials.gov Identifier: NCT02863094

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Automated optimization of TMS coil placement for personalized functional network engagement

Cited by 58 publications

References 103 publications

Comparison of coil placement approaches targeting dorsolateral prefrontal cortex in depressed adolescents receiving repetitive transcranial magnetic stimulation: an electric field modeling study

Comparison of coil placement approaches targeting dorsolateral prefrontal cortex in depressed adolescents receiving repetitive transcranial magnetic stimulation: an electric field modeling study

Precision mapping and transcranial magnetic stimulation of individual-specific functional brain networks in humans

Repetitive Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations in Schizophrenia

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