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利用机器学习算法和磁共振成像研究创伤后应激障碍中阿尔茨海默病的神经标志物。

Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.

作者信息

Yakemow Gabriella, Kolesar Tiffany A, Wright Natalie, Beheshti Iman, Choi Eun Hyung, Ryner Lawrence, Chaulk Sarah, Patel Ronak, Ko Ji Hyun

机构信息

Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB, Canada.

PrairieNeuro Brain Research Centre, Health Sciences Centre, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada.

出版信息

Front Neurol. 2024 Nov 7;15:1470727. doi: 10.3389/fneur.2024.1470727. eCollection 2024.

Abstract

INTRODUCTION

Posttraumatic stress disorder (PTSD) is a mental health disorder caused by experiencing or witnessing traumatic events. Recent studies show that patients with PTSD have an increased risk of developing dementia, including Alzheimer's disease (AD), but there is currently no way to predict which patients will go on to develop AD. The objective of this study was to identify structural and functional neural changes in patients with PTSD that may contribute to the future development of AD.

METHODS

Neuroimaging (pseudo-continuous arterial spin labeling [pCASL] and structural magnetic resonance imaging [MRI]) and behavioral data for the current study ( = 67) were taken from our non-randomized open label clinical trial (ClinicalTrials.gov Identifier: NCT03229915) for treatment-seeking individuals with PTSD ( = 40) and age-matched healthy controls (HC; = 27). Only the baseline measures were utilized for this study. Mean cerebral blood flow (CBF) and gray matter (GM) volume were compared between groups. Additionally, we utilized two previously established machine learning-based algorithms, one representing AD-like brain activity (Machine learning-based AD Designation [MAD]) and the other focused on AD-like brain structural changes (AD-like Brain Structure [ABS]). MAD scores were calculated from pCASL data and ABS scores were calculated from structural T-MRI images. Correlations between neuroimaging data (regional CBF, GM volume, MAD scores, ABS scores) and PTSD symptom severity scores measured by the clinician-administered PTSD scale for DSM-5 (CAPS-5) were assessed.

RESULTS

Decreased CBF was observed in two brain regions (left caudate/striatum and left inferior parietal lobule/middle temporal lobe) in the PTSD group, compared to the HC group. Decreased GM volume was also observed in the PTSD group in the right temporal lobe (parahippocampal gyrus, middle temporal lobe), compared to the HC group. GM volume within the right temporal lobe cluster negatively correlated with CAPS-5 scores and MAD scores in the PTSD group.

CONCLUSION

Results suggest that patients with PTSD with reduced GM volume in the right temporal regions (parahippocampal gyrus) experienced greater symptom severity and showed more AD-like brain activity. These results show potential for early identification of those who may be at an increased risk for future development of dementia.

摘要

引言

创伤后应激障碍(PTSD)是一种因经历或目睹创伤性事件而引发的心理健康障碍。近期研究表明,PTSD患者患痴呆症(包括阿尔茨海默病(AD))的风险增加,但目前尚无方法预测哪些患者会发展为AD。本研究的目的是确定PTSD患者可能导致未来AD发展的神经结构和功能变化。

方法

本研究(n = 67)的神经影像学(伪连续动脉自旋标记[pCASL]和结构磁共振成像[MRI])及行为数据取自我们针对寻求治疗的PTSD患者(n = 40)和年龄匹配的健康对照(HC;n = 27)开展的非随机开放标签临床试验(ClinicalTrials.gov标识符:NCT03229915)。本研究仅使用基线测量数据。比较了两组之间的平均脑血流量(CBF)和灰质(GM)体积。此外,我们使用了两种先前建立的基于机器学习的算法,一种代表类似AD的脑活动(基于机器学习的AD诊断[MAD]),另一种侧重于类似AD的脑结构变化(类似AD的脑结构[ABS])。MAD分数根据pCASL数据计算得出,ABS分数根据结构T-MRI图像计算得出。评估了神经影像学数据(局部CBF、GM体积、MAD分数、ABS分数)与临床医生使用的DSM-5创伤后应激障碍量表(CAPS-5)测量的PTSD症状严重程度分数之间的相关性。

结果

与HC组相比,PTSD组两个脑区(左侧尾状核/纹状体和左侧顶下小叶/颞中叶)的CBF降低。与HC组相比,PTSD组右侧颞叶(海马旁回、颞中叶)的GM体积也降低。PTSD组右侧颞叶簇内的GM体积与CAPS-5分数和MAD分数呈负相关。

结论

结果表明,右侧颞叶区域(海马旁回)GM体积减少的PTSD患者症状严重程度更高,且表现出更多类似AD的脑活动。这些结果显示了早期识别那些未来患痴呆症风险可能增加的人的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9285/11578870/3d929634336c/fneur-15-1470727-g0001.jpg

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