Modelling the differential effects of age on transcranial magnetic stimulation induced electric fields

Female sex and age-based advantage of simulated electric field in TMS to the prefrontal cortex in schizophrenia and mood disorders

This study investigates computational models of electric field strength for transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex (DLPFC) based on individual MRI data of patients with schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder (BP), and healthy controls (HC). In addition, it explores the association of electric field intensities with age, gender and intracranial volume. The subjects were 23 SZ (12 male, mean age = 45.30), 24 MDD (16 male, mean age = 43.57), 23 BP (16 male, mean age = 39.29), 23 HC (13 male, mean age = 40.91). Based on individual MRI sequences, electric fields were computationally modeled by two independent investigators using SimNIBS ver. 2.1.1. There was no significant difference in electric field strength between the groups (HC vs SZ, HC vs MDD, HC vs BP, SCZ vs MDD, SCZ vs BP, MDD vs BP). Female subjects showed higher electric field intensities in widespread areas than males, and age was positively significantly associated with electric field strength in the left parahippocampal area as observed. Our results suggest differences in electric field strength of left DLPFC TMS for gender and age. It may open future avenues for individually modeling TMS based on structural MRI data.

Safety of noninvasive brain stimulation in children

PURPOSE OF REVIEW

Noninvasive brain stimulation (NIBS) is a promising method for altering cortical excitability with clinical implications. It has been increasingly used in children, especially in neurodevelopmental disorders. Yet, its safety and applications in the developing brain require further investigation. This review aims to provide an overview of the safety of commonly used NIBS techniques in children, including transcranial electrical stimulation (tES) and transcranial magnetic stimulation (TMS). Safety data for other NIBS methods is not reported in this review.

RECENT FINDINGS

In line with studies from the last decade, findings in the last 2 years (2022-2023) support the safety of NIBS in children and adolescents within the currently applied protocols. Both tES and TMS are well tolerated, if safety rules, including exclusion criteria, are applied.

SUMMARY

We briefly discussed developmental aspects of stimulation parameters that need to be considered in the developing brain and provided an up-to-date overview of tES/TMS applications in children and adolescents. Overall, the safety profile of tES/TMS in children is good. For both the tES and TMS applications, epilepsy and active seizure disorder should be exclusion criteria to prevent potential seizures. Using child-sized earplugs is required for TMS applications. We lack large randomized double-blind trialsand longitudinal studies to establish the safety of NIBS in children.

VIDEO ABSTRACT

http://links.lww.com/YCO/A78 .

Short-term and long-term efficacy of accelerated transcranial magnetic stimulation for depression: a systematic review and meta-analysis

BACKGROUND

In recent years, accelerated transcranial magnetic stimulation (aTMS) has been developed, which has a shortened treatment period. The aim of this study was to evaluate the efficacy and long-term maintenance effects of aTMS in patients with major depressive disorder (MDD).

METHODS

We systematically searched online databases for aTMS studies in patients with MDD published before February 2023 and performed a meta-analysis on the extracted data.

RESULTS

Four randomized controlled trials (RCTs) and 10 before-and-after controlled studies were included. The findings showed that depression scores significantly decreased following the intervention (SMD = 1.80, 95% CI (1.31, 2.30), p < 0.00001). There was no significant difference in antidepressant effectiveness between aTMS and standard TMS (SMD = -0.67, 95% CI (-1.62, 0.27), p = 0.16). Depression scores at follow-up were lower than those directly after the intervention based on the depression rating scale (SMD = 0.22, 95% CI (0.06, 0.37), p = 0.006), suggesting a potential long-term maintenance effect of aTMS. Subgroup meta-analysis results indicated that different modes of aTMS may have diverse long-term effects. At the end of treatment with the accelerated repetitive transcranial magnetic stimulation (arTMS) mode, depressive symptoms may continue to improve (SMD = 0.29, 95% CI (0.10, 0.49), I2 = 22%, p = 0.003), while the accelerated intermittent theta burst stimulation (aiTBS) mode only maintains posttreatment effects (SMD = 0.01, 95% CI (-0.45, 0.47), I2 = 66%, p = 0.98).

CONCLUSIONS

Compared with standard TMS, aTMS can rapidly improve depressive symptoms, but there is no significant difference in efficacy. aTMS may also have long-term maintenance effects, but longer follow-up periods are needed to assess this possibility.

TRIAL REGISTRATION

This article is original and not under simultaneous consideration for publication. The study was registered on PROSPERO ( https://www.crd.york.ac.uk/prospero/ ) (number: CRD42023406590).

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study

BACKGROUND

Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing.

OBJECTIVES

This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures.

METHODS

Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals.

RESULTS

In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model.

CONCLUSIONS

Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

Optimizing TMS Coil Placement Approaches for Targeting the Dorsolateral Prefrontal Cortex in Depressed Adolescents: An Electric Field Modeling Study

High-frequency repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) shows promise as a treatment for treatment-resistant depression in adolescents. Conventional rTMS coil placement strategies include the 5 cm, the Beam F3, and the magnetic resonance imaging (MRI) neuronavigation methods. The purpose of this study was to use electric field (E-field) models to compare the three targeting approaches to a computational E-field optimization coil placement method in depressed adolescents. Ten depressed adolescents (4 females, age: 15.9±1.1) participated in an open-label rTMS treatment study and were offered MRI-guided rTMS five times per week over 6-8 weeks. Head models were generated based on individual MRI images, and E-fields were simulated for the four targeting approaches. Results showed a significant difference in the induced E-fields at the L-DLPFC between the four targeting methods (χ2=24.7, p<0.001). Post hoc pairwise comparisons showed 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±17.4V/m), followed by the F3 method (87.4±35.4V/m), followed by MRI-guided (112.1±14.6V/m), and followed by the computational approach (130.1±18.1V/m). Variance analysis showed that there was a significant difference in sample variance between the groups (K2=8.0, p<0.05), with F3 having the largest variance. Participants who completed the full course of treatment had median E-fields correlated with depression symptom improvement (r=-0.77, p<0.05). E-field models revealed limitations of scalp-based methods compared to MRI guidance, suggesting computational optimization could enhance dose delivery to the target.

A Systematic Review and Large-Scale tES and TMS Electric Field Modeling Study Reveals How Outcome Measure Selection Alters Results in a Person- and Montage-Specific Manner

Background

Electric field (E-field) modeling is a potent tool to examine the cortical effects of transcranial magnetic and electrical stimulation (TMS and tES, respectively) and to address the high variability in efficacy observed in the literature. However, outcome measures used to report E-field magnitude vary considerably and have not yet been compared in detail.

Objectives

The goal of this two-part study, encompassing a systematic review and modeling experiment, was to provide an overview of the different outcome measures used to report the magnitude of tES and TMS E-fields, and to conduct a direct comparison of these measures across different stimulation montages.

Methods

Three electronic databases were searched for tES and/or TMS studies reporting E-field magnitude. We extracted and discussed outcome measures in studies meeting the inclusion criteria. Additionally, outcome measures were compared via models of four common tES and two TMS modalities in 100 healthy younger adults.

Results

In the systematic review, we included 118 studies using 151 outcome measures related to E-field magnitude. Structural and spherical regions of interest (ROI) analyses and percentile-based whole-brain analyses were used most often. In the modeling analyses, we found that there was an average of only 6% overlap between ROI and percentile-based whole-brain analyses in the investigated volumes within the same person. The overlap between ROI and whole-brain percentiles was montage- and person-specific, with more focal montages such as 4Ã-1 and APPS-tES, and figure-of-eight TMS showing up to 73%, 60%, and 52% overlap between ROI and percentile approaches respectively. However, even in these cases, 27% or more of the analyzed volume still differed between outcome measures in every analyses.

Conclusions

The choice of outcome measures meaningfully alters the interpretation of tES and TMS E-field models. Well-considered outcome measure selection is imperative for accurate interpretation of results, valid between-study comparisons, and depends on stimulation focality and study goals. We formulated four recommendations to increase the quality and rigor of E-field modeling outcome measures. With these data and recommendations, we hope to guide future studies towards informed outcome measure selection, and improve the comparability of studies.

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

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 6-8 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 ( χ 2 = 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.