Multimodal Neuroimaging in the Prediction of Deep TMS Response in OCD

dc.authorid0009-0009-3363-4900
dc.authorid0000-0002-4628-8391
dc.authorid0000-0003-1500-6555
dc.authorid0000-0002-8271-9662
dc.authorid0000-0002-2117-8276
dc.authorid0000-0003-0529-2789
dc.contributor.authorAsik, Murat
dc.contributor.authorIlhan, Reyhan
dc.contributor.authorGunver, Mehmet Guven
dc.contributor.authorOrhan, Ozden
dc.contributor.authorEsmeray, Muhammed Taha
dc.contributor.authorKalaba, Oznur
dc.contributor.authorArikan, Mehmet Kemal
dc.date.accessioned2025-05-10T19:34:07Z
dc.date.issued2024
dc.departmentİstanbul Medeniyet Üniversitesi
dc.description.abstractBackgrounds: .Brain morphological biomarkers could contribute to understanding the treatment response in patients with obsessive-compulsive disorder (OCD). Multimodal neuroimaging addresses this issue by providing more comprehensive information regarding neural processes and structures. Objectives. The present study aims to investigate whether patients responsive to deep Transcranial Magnetic Stimulation (TMS) differ from non-responsive individuals in terms of electrophysiology and brain morphology. Secondly, to test whether multimodal neuroimaging is superior to unimodal neuroimaging in predicting response to deep TMS. Methods. Thirty-two OCD patients who underwent thirty sessions of deep TMS treatment were included in the study. Based on a minimum 50% reduction in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores after treatment, patients were grouped as responders (n = 25) and non-responders (n = 7). The baseline resting state qEEG and magnetic resonance imaging (MRI) records of patients were recorded. Independent sample t-test is used to compare the groups. Then, three logistic regression model were calculated for only QEEG markers, only MRI markers, and both QEEG/MRI markers. The predictive values of the three models were compared. Results. OCD patients who responded to deep TMS treatment had increased Alpha-2 power in the left temporal area and increased volume in the left temporal pole, entorhinal area, and parahippocampal gyrus compared to non-responders. The logistic regression model showed better prediction performance when both QEEG and MRI markers were included. Conclusions. This study addresses the gap in the literature regarding new functional and structural neuroimaging markers and highlights the superiority of multimodal neuroimaging to unimodal neuroimaging techniques in predicting treatment response.
dc.identifier.doi10.1177/15500594241298977
dc.identifier.issn1550-0594
dc.identifier.issn2169-5202
dc.identifier.pmid39563493
dc.identifier.scopus2-s2.0-85209754297
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1177/15500594241298977
dc.identifier.urihttps://hdl.handle.net/20.500.14730/8395
dc.identifier.wosWOS:001359122800001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSage Publications Inc
dc.relation.ispartofClinical Eeg and Neuroscience
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250302
dc.subjectdeep transcranial magnetic stimulation
dc.subjectmagnetic resonance imaging
dc.subjectobsessive compulsive disorder
dc.subjectquantitative EEG
dc.subjectmultimodal neuroimaging
dc.titleMultimodal Neuroimaging in the Prediction of Deep TMS Response in OCD
dc.typeArticle

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