Functional network connectivity patterns predicting the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer’s disease

European Radiology Experimental

Original Article

Zhiyuan Yang¹  Hui Zhao¹  Zheqi Hu¹  Ruomeng Qin¹  Haifeng Chen²  Feng Bai³  Weina Yao⁴  Zhiming Qin⁴  Tingyu Lv⁴  Mengyun Li⁴ 

[1]Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, 210008, Nanjing, Jiangsu, China

[2]Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China

[3]Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China

[4]Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China

[5]Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, 210008, Nanjing, Jiangsu, China

[6]Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China

[7]Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China

[8]Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China

[9]Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China

[10]Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, 210008, Nanjing, Jiangsu, China

[11]Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China

[12]Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China

[13]Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China

[14]Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China

[15]Geriatric Medicine Center, Affiliated Hospital of Medical School, Taikang Xianlin Drum Tower Hospital, Nanjing University, Nanjing, China

[16]Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China

关键词: Alzheimer’s disease;    Brain;    Machine learning;    Magnetic resonance imaging;    Transcranial magnetic stimulation;   

DOI  :  10.1186/s41747-023-00376-3

 received in 2023-05-12, accepted in 2023-08-17,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundNeuro-navigated repetitive transcranial magnetic stimulation (rTMS) is potentially effective in enhancing cognitive performance in the spectrum of Alzheimer’s disease (AD). We explored the effect of rTMS-induced network reorganization and its predictive value for individual treatment response.MethodsSixty-two amnestic mild cognitive impairment (aMCI) and AD patients were recruited. These subjects were assigned to multimodal magnetic resonance imaging scanning before and after a 4-week stimulation. Then, we investigated the neural mechanism underlying rTMS treatment based on static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) analyses. Finally, the support vector regression was used to predict the individual rTMS treatment response through these functional features at baseline.ResultsWe found that rTMS at the left angular gyrus significantly induced cognitive improvement in multiple cognitive domains. Participants after rTMS treatment exhibited significantly the increased sFNC between the right frontoparietal network (rFPN) and left frontoparietal network (lFPN) and decreased sFNC between posterior visual network and medial visual network. We revealed remarkable dFNC characteristics of brain connectivity, which was increased mainly in higher-order cognitive networks and decreased in primary networks or between primary networks and higher-order cognitive networks. dFNC characteristics in state 1 and state 4 could further predict individual higher memory improvement after rTMS treatment (state 1, R = 0.58; state 4, R = 0.54).ConclusionOur findings highlight that neuro-navigated rTMS could suppress primary network connections to compensate for higher-order cognitive networks. Crucially, dynamic regulation of brain networks at baseline may serve as an individualized predictor of rTMS treatment response.Relevance statementDynamic reorganization of brain networks could predict the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer’s disease.Key points• rTMS at the left angular gyrus could induce cognitive improvement.• rTMS could suppress primary network connections to compensate for higher-order networks.• Dynamic reorganization of brain networks could predict individual treatment response to rTMS.Graphical Abstract

【 授权许可】

CC BY   
© European Society of Radiology (ESR) 2023

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