TMs Outcome Research Articles

Motor threshold parameters do not predict repetitive Transcranial Magnetic Stimulation and intermittent Theta Burst Stimulation outcomes in major depressive disorder

BackgroundRepetitive Transcranial Magnetic Stimulation (rTMS) and intermittent Theta Burst Stimulation (iTBS) are non-invasive treatments for major depressive disorder (MDD). While effective, variability in outcomes necessitates identifying predictors of therapeutic response. This study examined whether motor threshold (MT), percentage of motor threshold (%MT), and treatment intensity could predict clinical outcomes in MDD patients undergoing rTMS and iTBS. MethodsAdult MDD patients treated with NeuroStar rTMS or iTBS at Mayo Clinic from February 2016 to April 2024 were included. MT, %MT, and treatment intensity were recorded. Clinical outcomes were assessed via Patient Health Questionnaire-9 (PHQ-9) score changes, response (PHQ-9 change ≥50 %), remission (PHQ-9 < 5), and a patient-reported outcome (PRO) on treatment helpfulness. Linear and logistic regression models were used to assess predictors of clinical outcomes. ResultsAmong 149 patients analyzed (mean age 45.7, 67.8 % female), response rate was 43.0 % and remission rate was 16.8 %. MT and %MT did not significantly correlate with clinical outcomes. Treatment intensity and TMS type did not predict PHQ-9 score changes. Higher treatment intensity was associated with decreased odds of positive PRO responses. Linear regression showed that age and gender significantly predicted PHQ-9 score changes, with older patients and females showing greater improvement. MT was significantly lower in men and with iTBS compared to rTMS. ConclusionMT, %MT, and treatment intensity did not reliably predict outcomes. Higher intensity was linked to reduced patient-reported helpfulness, suggesting that patient comfort is crucial. iTBS's lower MT may benefit those needing less stimulation. Future research should identify better predictors to improve TMS outcomes.

NIMG-82. DEVELOPMENT AND VALIDATION OF AN MRI-BASED DEEP LEARNING MODEL TO DIFFERENTIATEIDH-WILDTYPE GLIOBLASTOMA AND TUMEFACTIVE MULTIPLE SCLEROSIS

Abstract Clinical management of IDH wildtype glioblastoma (GBM) and tumefactive multiple sclerosis (tMS) is drastically different. GBM requires maximal safe resection followed by chemoradiation, while tMS outcome is worsened by surgery and radiotherapy. Noninvasive methods are needed to help with accurate diagnosis of tumor and non-tumor etiologies. To develop an MRI-based classification model, tMS subjects diagnosed prior to January 1, 2020, were matched to tMS by age at diagnosis, sex, index MRI date, and 2D/3D acquisition. Inclusion criteria included one cm minimal lesion size and pre-operative post-contrast T1 and T2 images available for analysis. A 3D-DenseNet121 was used to develop a classification model using prespecified parameters: 650 epochs, batch size 16, learning rate 10-3, cross-entropy loss, and AdamW optimizer. The stopping rule was defined as three sequential differences in epoch cross-entropy loss &amp;lt;0.02. Models were developed using both T1gd and T2, as well as from only T1gd and only T2. Training included 220 subjects (110 GBM, 110 tMS). A 2-stage validation design was used, which included both retrospective and prospective cohorts. Stage 1 consisted of 272 retrospective GBM (diagnosed prior to January 1, 2020). Stage 2 consisted of 69 and 34 prospective (diagnosed after January 1, 2020) GBM and tMS, respectively. External validation on the 272 retrospective GBM demonstrated accuracy of 91%, 84%, and 78% for T1gd+T2, T1gd only, and T2 only, respectively. External validation on the 69 prospective GBM demonstrated an accuracy of 87%, 64%, and 67% for T1gd+T2, T1gd only, and T2 only, respectively. The 34 prospective tMS demonstrated accuracy of 76%, 76%, and 82% for T1gd+T2, T1gd only, and T2 only, respectively. This shows the feasibility of deep learning to aid in differential diagnosis of brain lesions. Future work entails the integration of germline variants into the classification model, including variants associated with the risk of glioma or MS.

NIMG-26. DIFFERENTIATION OF IDH-WILDTYPE GLIOBLASTOMA AND TUMEFACTIVE MULTIPLE SCLEROSIS USING PRE-OPERATIVE BRAIN MRI AND DEEP LEARNING: RIGOROUS AND UNBIASED EXPERIMENTAL DESIGN AND ANALYTICAL APPROACH

Abstract Clinical management of IDH wildtype glioblastoma (GBM) and tumefactive multiple sclerosis (tMS) is drastically different. GBM requires maximal safe resection followed by chemoradiation, while tMS outcome is worsened by surgery and radiotherapy. Misdiagnosis of brain lesions may expose patients to unnecessary anxiety, surgery, or radiotherapy. Noninvasive methods to help with accurate diagnosis of tumor and non-tumor etiologies are needed. tMS subjects were identified by the Mayo Clinic Center for Multiple Sclerosis and Autoimmune Neurology (CMSAN). GBM subjects were matched to tMS by age at diagnosis, index MRI date, and sex. Inclusion criteria included one cm minimal lesion size and pre-operative post-contrast T1 and T2 images available for analysis. To identify potential experimental design bias, MRI technology and clinical characteristics were compared across groups. A 3D-DenseNet121 was used to develop a classification model using prespecified parameters: 600 epochs, batch size 16, learning rate 10-3, cross entropy loss, and AdamW optimizer. The stopping rule was defined as three sequential epoch cross entropy loss &amp;lt; 0.02. Five-fold cross validation (CV) was utilized to obtain an unbiased estimate of predictive performance (overfitting) and sensitivity of the 3D-DenseNet121 algorithm was evaluated. 224 subjects (114 GBM, 110 tMS) were analyzed: 40% male, median age 46. After one round of CV, the average unbiased estimate of sensitivity and specificity for predicting GBM from the final classification model was 0.86 and 0.73, respectively. To assess the reproducibility of the deep learning algorithm (3D-DenseNet121), the exact same CV folds were rerun resulting in average sensitivity and specificity of 0.82 and 0.75, respectively. Obtaining unbiased estimates of model performance using internal validation is critical before evaluating a final model on an external dataset. Understanding sensitivity of a deep learning algorithm is important for model validity. Differentiation of GBM and tMS appears reasonable with MRI; external validation is in progress.

TMS Targets for Multiple Sclerosis Related Depression Derived Using a Precomputed Functional Connectome (P11-3.014)

TMS Targets for Multiple Sclerosis Related Depression Derived Using a Precomputed Functional Connectome (P11-3.014)

Early non-improvement may predict final TMS outcomes

Background: Prior studies suggested that less than 20% improvement at week 2 predicted worse final response rates but lacked deep Transcranial Magnetic Stimulation (dTMS) data. This study intended to verify whether varying degrees of improvement in Major Depressive Disorder at weeks 2 and 6 accurately predicted response and remission rates at Endpoint, and benefits of treatment past week 6. Methods: All patients (n=169) in this open-label, retrospective study received at least 30 sessions of dTMS using 55 to 95 two-second trains, frequency 18 Hz, 120% motor threshold over the left dorsolateral prefrontal cortex (DLPFC). Augmentation included left DLPFC intermittent Theta Burst Stimulation (iTBS) and right DLPFC Low Frequency dTMS. Responders improved by 50% from baseline on the Hamilton Depression Scale (HAMD). Patients were grouped as “Improvers” or “Non-Improvers” based on improvement at weeks 2 and 6, then compared to Endpoint. Results: After week 2, those improved by over 30% had significantly higher endpoint remission rates. Those improved by 15-40% after week 2 had significantly higher endpoint response rates. After week 6, those improving by 15-40% showed both significantly higher Endpoint response and remission rates. Conclusions: 56% and 35% of Non-Improvers with less than 20% improvement after Weeks 2 and 6, respectively, responded at Endpoint. With such a large portion of patients responding after Week 6, treatment extension beyond week 6 may be warranted on a per patient basis. Conflicts of Interests: None Funding: None Disclosures: Dr. Kinback is the Owner and Medical Director of Advanced TMS Center, a private group psychiatric practice in Ladera Ranch, CA. He is a board member, past Treasurer and Fellow of the Clinical TMS Society. He has received stipends in the past for speaking from the Clinical TMS Society.

A systematic review of TMS and neurophysiological biometrics in patients with schizophrenia.

Background:Transcranial magnetic stimulation can be combined with electromyography (TMS-EMG) and electroencephalography (TMS-EEG) to evaluate the excitatory and inhibitory functions of the cerebral cortex in a standardized manner. It has been postulated that schizophrenia is a disorder of functional neural connectivity underpinned by a relative imbalance of excitation and inhibition. The aim of this review was to provide a comprehensive overview of TMS-EMG and TMS-EEG research in schizophrenia, focused on excitation or inhibition, connectivity, motor cortical plasticity and the effect of antipsychotic medications, symptom severity and illness duration on TMS-EMG and TMS-EEG indices.Methods:We searched PsycINFO, Embase and Medline, from database inception to April 2020, for studies that included TMS outcomes in patients with schizophrenia. We used the following combination of search terms: transcranial magnetic stimulation OR tms AND interneurons OR glutamic acid OR gamma aminobutyric acid OR neural inhibition OR pyramidal neurons OR excita* OR inhibit* OR GABA* OR glutam* OR E-I balance OR excitation-inhibition balance AND schizoaffective disorder* OR Schizophrenia OR schizophreni*.Results:TMS-EMG and TMS-EEG measurements revealed deficits in excitation or inhibition, functional connectivity and motor cortical plasticity in patients with schizophrenia. Increased duration of the cortical silent period (a TMS-EMG marker of γ-aminobutyric acid B receptor activity) with clozapine was a relatively consistent finding.Limitations:Most of the studies used patients with chronic schizophrenia and medicated patients, employed cross-sectional group comparisons and had small sample sizes.Conclusion:TMS-EMG and TMS-EEG offer an opportunity to develop a novel and improved understanding of the physiologic processes that underlie schizophrenia and to assess the therapeutic effect of antipsychotic medications. In the future, these techniques may also help predict disease progression and further our understanding of the excitatory/inhibitory balance and its implications for mechanisms that underlie treatment-resistant schizophrenia.

A Cognitive Biomarker May Optimize TMS Depression Outcomes

Background: Utilizing biomarkers to predict TMS outcomes with major depressive disorder (MDD) could optimize care. One potential cognitive biomarker is reaction time to negative facial expressions, which may be faster in MDD patients compared to controls. The objective of this study was to test whether baseline reaction time to negative faces is predictive of response to TMS in MDD.

P211 Combination of cortical and peripheral TBS with physical therapy in chronic low back pain: After-effects on clinical and TMS outcomes

P211 Combination of cortical and peripheral TBS with physical therapy in chronic low back pain: After-effects on clinical and TMS outcomes

MRI and brain stimulation in common practice: Toward precision medicine

Background Repetitive transcranial magnetic stimulation (rTMS) is a validated treatment for patients with depression resistant to antidepressant medication. To a lesser extent, rTMS is considered as a second-line treatment for auditory hallucinations in patients with schizophrenia resistant to antipsychotic medication. However, roughly 50% of patients with resistant depression are not responding to TMS. Thus, finding predictive factors for rTMS response is key to offer personalized treatment to patients. Drysdale et al. [1] have proposed that combining clinical characteristics and functional MRI could lead to the prediction of TMS outcome in patients with depression. However, there is still a limited access to functional MRI in common practice. Structural MRI is an accessible and short duration exam used in common practice for neuronavigation purposes. Methods We conducted a neuroimaging retrospective study in our center and analyzed structural MRI of patients treated both in open label and randomized trials for resistant depression and hallucinations. We processed structural MRI with FreeSurfer software, which provide an automated segmentation of the brain. All MRI were acquired with the same neuroimaging protocol. We compared both skull and brain anatomical features in patients responding and not responding to rTMS. Results We here present preliminary results of our study and demonstrate the feasibility of analyzing structural MRI in the context of brain stimulation in common practice. We discuss MRI-based potential factors that could be taken into account to understand rTMS response.

Efficacy of Breathing Exercises on daily living activities of patients with Chronic Obstructive Pulmonary Disease

Improving breathing pattern and reducing disease progression including exacerbation frequency is a target goal for all COPD patients. Aim of the present study to assess efficacy of breathing exercises on daily living activities of patients with Chronic Obstructive Pulmonary Disease. Research design: A quasi experimental design. Sample: A convenience sample of 70 patients with COPD. Tool consists of three Part I: Interviewing questionnaire to assess the socio-demographic data. Part II: Physical examination sheet. Part III: An assessment of patient’s difficulty of breathing during daily living activities (DLA). Results: Revealed statistical significant difference of the total mean scores before breathing exercise and after 3 months of breathing exercises training. Conclusion: There was positive efficacy of exercises on respiratory patient’s outcomes with chronic obstructive pulmonary disease as evident with improvement in performing the daily living activities. The study recommended that government officials as well as nongovernmental organizations should encourage and support home-based training especially for patients with insufficient income. Further experimental study is suggested to compare between two groups of COPD one apply breathing exercises and another take antibiotic to demonstrate effect of exercises intervention on of purulent sputum.

Influence of Motor Cortex Stimulation During Motor Training on Neuroplasticity as a Potential Therapeutic Intervention

ABSTRACTRehabilitation options to promote neuroplasticity may be enhanced when patients are engaged in motor practice during repetitive transcranial magnetic stimulation (rTMS). Twelve participants completed 3 separate sessions: motor practice, motor practice with rTMS, and rTMS only: motor practice consisted of 30 isometric contractions and subthreshold rTMS was 30, 3-s trains at 10 Hz. Assessments included the Box and Block Test (BBT), force steadiness (10% of the maximum voluntary contraction), and TMS (cortical excitability, intracortical inhibition, and intracortical facilitation). Participants significantly increased BBT scores following the combined condition. Force steadiness improved after all 3 conditions (p < .05). TMS outcomes depended on intervention condition with significant increases in facilitation following the motor practice plus rTMS condition. All interventions influenced motor control, yet are likely modulated differently when combining motor practice plus rTMS. These results help guide the clinical utility of rTMS as an intervention to influence motor control.

No Modulation of Visual Cortex Excitability by Transcranial Direct Current Stimulation.

Measuring phosphene thresholds (PTs) is often used to investigate changes in the excitability of the human visual cortex through different brain stimulation methods like repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS). In several studies, PT increase or decrease has been shown after rTMS or tDCS application. Recently, using PT measurements we showed that the state of the neurons in the visual cortex after rTMS might have an influence on the modulatory effects of stimulation. In the present study we aimed to investigate whether visual cortex activity following stimulation influences the modulatory effects of tDCS as well. In a between-group design, anodal or cathodal tDCS was applied to the visual cortex twice per subject, with either high or low visual demand following stimulation. We observed no modulation of PT neither directly following both anodal and cathodal tDCS nor following the visual demand periods. We rather found high inter-individual variability in the response to tDCS, and intra-individual reliability in the direction of modulation was observed for cathodal tDCS only. Thus, our results do not confirm the modulatory effects of tDCS on visual cortex excitability published previously. Moreover, they support the confirmation that tDCS effects have little reliability on varied TMS outcome measurements.

TMS-based neuromodulation of evoked and induced gamma oscillations and event-related potentials in children with autism

Gamma oscillations are important for the integration of information and are involved in a variety of perceptual, cognitive, and motor process that are affected in autism spectrum disorder (ASD). We used gamma oscillations along with event-related potentials (ERP) as functional markers of response to repetitive transcranial magnetic stimulation (rTMS). The subjects were age- and gender-matched ASD and typically developing children (TDC). Behavioral evaluations along with evoked and induced gamma and ERPs during oddball task were collected at pre- and post-TMS in ASD group (N = 23) and at baseline in TDC (N = 21). ASD subjects were assigned to 18 sessions of rTMS over the dorsolateral prefrontal cortex. Baseline test showed significant differences between ASD and TDC groups in terms of responses to non-targets where ASD showed excessive gamma oscillations and larger ERPs as compared to the TDC group. Behavioral response differences were manifested in a lower accuracy of motor responses. The rTMS resulted in improved accuracy of response, attenuated evoked gamma responses to non-targets, and increased induced gamma to targets. Behavioral outcomes showed decreased irritability and hyperactivity scores and decreased repetitive and stereotype behaviors. There is discussed utility of gamma oscillations as biomarkers for functional diagnostics and predictions of TMS outcomes in ASD.

Comparison of TMS outcomes in complex major depressive disorder: Brainsway and Neurostar

Comparison of TMS outcomes in complex major depressive disorder: Brainsway and Neurostar

Therapeutic alliance in the initial phase of psychotherapy with adolescents: different perspectives and their association with therapeutic outcomes

Psychotherapy research focusing on adults as well as on children and adolescents has revealed a positive association between the quality of the therapeutic alliance (TA) in the first sessions and therapeutic outcomes. Nevertheless, there is controversy regarding which perspective (of the adolescents, therapists, or parents) and what moment of evaluation (first, second, or third session) is most strongly associated with outcome. This study aims to describe the TA during the initial phase of psychotherapy with adolescents, from several perspectives, and relate it to the intermediate and final outcomes of the therapy. The study is descriptive-correlational and was conducted in naturalistic settings. The sample comprised 20 individual psychotherapeutic processes (15 females, 5 males; average age: 15.8 years; standard deviation=1.04). The variables studied were: TA, measured with the Working Alliance Inventory, applied to adolescents, therapists, and parents, and therapeutic outcomes, measured using Lambert’s Outcome Questionnaire (OQ- 45.2). The results show that the TA improved from session one to session three, both in the adolescents and the therapists. The TA, as perceived by the adolescents in the third session, is positively correlated with final outcomes (r=-.732*, P=.025). The TA evaluated from the therapists’ perspective in the third session, specifically the bond component of the TA, predicts the final success of psychotherapy with adolescent patients [β=0.426, Exp. (B)=1.531, degree of freedom=1, P=0.034]. The importance of the initial construction of the working alliance by both participants is discussed.

Analysis of MDD Patients in Relation to TMS Outcome and Genotype

To determine the link between TMS outcome in patients treated for unipolar depression, and the patient's genetic profile of pharmacokinetic and pharmacodynamic genes.

Efficacy Comparison of NeuroStar TMS and Antidepressant Medications in the Treatment of Pharmacoresistant Major Depression

A recent, large multisite study of acute TMS treatment in clinical practice showed a significant reduction in depression scores at the conclusion of acute treatment (Carpenter, et al., 2012). Here, we used propensity score matching to compare TMS outcomes in real world practice settings to patients enrolled in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study.