多模态神经成像在预测强迫症深度 TMS 反应中的应用

Murat Aşık, Reyhan İlhan, Mehmet Güven Günver, Özden Orhan, Muhammed Taha Esmeray, Öznur Kalaba, Mehmet Kemal Arıkan
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摘要

背景:.大脑形态生物标志物有助于了解强迫症(OCD)患者的治疗反应。多模态神经影像学可提供有关神经过程和结构的更全面信息,从而解决这一问题。研究目的本研究旨在调查对深部经颅磁刺激(TMS)有反应的患者与无反应的患者在电生理学和大脑形态学方面是否存在差异。其次,测试多模态神经成像在预测对深度经颅磁刺激的反应方面是否优于单模态神经成像。研究方法32 名强迫症患者接受了 30 次深度 TMS 治疗。根据治疗后耶鲁-布朗强迫症量表(Y-BOCS)评分至少降低50%的标准,患者被分为应答者(n = 25)和非应答者(n = 7)两组。记录患者的基线静息状态 qEEG 和磁共振成像(MRI)记录。采用独立样本 t 检验对两组进行比较。然后,计算了仅 QEEG 标记、仅 MRI 标记和 QEEG/MRI 标记的三个逻辑回归模型。比较三个模型的预测值。结果显示与无反应者相比,对深部TMS治疗有反应的强迫症患者左颞区的Alpha-2功率增加,左颞极、内侧区和海马旁回的体积增加。如果同时纳入 QEEG 和 MRI 标记,逻辑回归模型的预测效果会更好。结论这项研究填补了有关新功能和结构神经影像标记的文献空白,并强调了多模态神经影像技术在预测治疗反应方面优于单模态神经影像技术。
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Multimodal Neuroimaging in the Prediction of Deep TMS Response in OCD.

Backgrounds: .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.

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