Hanna Lu, Jing Li, Sandra Sau Man Chan, Suk Ling Ma, Vincent Chung Tong Mok, Lin Shi, Arthur Dun-Ping Mak, Linda Chiu Wa Lam
{"title":"治疗前脑年龄模型对神经认知障碍伴抑郁症患者经颅磁刺激效应的预测价值:随机假对照临床试验的二次分析。","authors":"Hanna Lu, Jing Li, Sandra Sau Man Chan, Suk Ling Ma, Vincent Chung Tong Mok, Lin Shi, Arthur Dun-Ping Mak, Linda Chiu Wa Lam","doi":"10.1080/19585969.2024.2373075","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters.</p><p><strong>Methods: </strong>This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age.</p><p><strong>Results: </strong>The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, <i>p</i> = .045) and by ∼39.5% in remitters (OR = 0.605, <i>p</i> = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3<sup>rd</sup> week) and 84% (12<sup>th</sup> week), respectively were achieved.</p><p><strong>Conclusion: </strong>In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: ChiCTR-IOR-16008191.</p>","PeriodicalId":54343,"journal":{"name":"Dialogues in Clinical Neuroscience","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225634/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive values of pre-treatment brain age models to rTMS effects in neurocognitive disorder with depression: Secondary analysis of a randomised sham-controlled clinical trial.\",\"authors\":\"Hanna Lu, Jing Li, Sandra Sau Man Chan, Suk Ling Ma, Vincent Chung Tong Mok, Lin Shi, Arthur Dun-Ping Mak, Linda Chiu Wa Lam\",\"doi\":\"10.1080/19585969.2024.2373075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters.</p><p><strong>Methods: </strong>This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age.</p><p><strong>Results: </strong>The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, <i>p</i> = .045) and by ∼39.5% in remitters (OR = 0.605, <i>p</i> = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3<sup>rd</sup> week) and 84% (12<sup>th</sup> week), respectively were achieved.</p><p><strong>Conclusion: </strong>In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: ChiCTR-IOR-16008191.</p>\",\"PeriodicalId\":54343,\"journal\":{\"name\":\"Dialogues in Clinical Neuroscience\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225634/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dialogues in Clinical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/19585969.2024.2373075\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dialogues in Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/19585969.2024.2373075","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Predictive values of pre-treatment brain age models to rTMS effects in neurocognitive disorder with depression: Secondary analysis of a randomised sham-controlled clinical trial.
Introduction: One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters.
Methods: This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age.
Results: The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, p = .045) and by ∼39.5% in remitters (OR = 0.605, p = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3rd week) and 84% (12th week), respectively were achieved.
Conclusion: In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment.
期刊介绍:
Dialogues in Clinical Neuroscience (DCNS) endeavors to bridge the gap between clinical neuropsychiatry and the neurosciences by offering state-of-the-art information and original insights into pertinent clinical, biological, and therapeutic aspects. As an open access journal, DCNS ensures accessibility to its content for all interested parties. Each issue is curated to include expert reviews, original articles, and brief reports, carefully selected to offer a comprehensive understanding of the evolving landscape in clinical neuroscience. Join us in advancing knowledge and fostering dialogue in this dynamic field.