Scarapicchia Vanessa, Mazerolle Erin L, Fisk John D, Ritchie Lesley J, Gawryluk Jodie R
Department of Psychology, University of Victoria, Victoria, BC, Canada.
Department of Radiology and The Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Front Aging Neurosci. 2018 Feb 21;10:39. doi: 10.3389/fnagi.2018.00039. eCollection 2018.
Alzheimer's disease (AD) is a neurodegenerative disorder that may benefit from early diagnosis and intervention. Therefore, there is a need to identify early biomarkers of AD using non-invasive techniques such as functional magnetic resonance imaging (fMRI). Recently, novel approaches to the analysis of resting-state fMRI data have been developed that focus on the moment-to-moment variability in the blood oxygen level dependent (BOLD) signal. The objective of the current study was to investigate BOLD variability as a novel early biomarker of AD and its associated psychophysiological correlates. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 2 database from 19 participants with AD and 19 similarly aged controls. For each participant, a map of BOLD signal variability (SD) was computed as the standard deviation of the BOLD timeseries at each voxel. Group comparisons were performed to examine global differences in resting state SD in AD versus healthy controls. Correlations were then examined between participant SD maps and (1) ADNI-derived composite scores of memory and executive function and (2) neuroimaging markers of cerebrovascular status. Between-group comparisons revealed significant ( < 0.05) increases in SD in patients with AD relative to healthy controls in right-lateralized frontal regions. Lower memory scores and higher WMH burden were associated with greater SD in the healthy control group ( < 0.1), but not individuals with AD. The current study provides proof of concept of a novel resting state fMRI analysis technique that is non-invasive, easily accessible, and clinically compatible. To further explore the potential of SDBOLD as a biomarker of AD, additional studies in larger, longitudinal samples are needed to better understand the changes in SDBOLD that characterize earlier stages of disease progression and their underlying psychophysiological correlates.
阿尔茨海默病(AD)是一种神经退行性疾病,早期诊断和干预可能对其有益。因此,有必要使用功能磁共振成像(fMRI)等非侵入性技术来识别AD的早期生物标志物。最近,已经开发出了新的静息态fMRI数据分析方法,这些方法聚焦于血氧水平依赖(BOLD)信号的逐时变化。本研究的目的是探讨BOLD信号变化作为AD的一种新型早期生物标志物及其相关的心理生理关联。数据取自阿尔茨海默病神经成像计划(ADNI)2数据库,包括19名AD患者和19名年龄相仿的对照者。对于每位参与者,计算BOLD信号变化图(SD),即每个体素处BOLD时间序列的标准差。进行组间比较以检查AD患者与健康对照者在静息态SD方面的整体差异。然后检查参与者的SD图与(1)ADNI得出的记忆和执行功能综合评分以及(2)脑血管状态的神经影像学标志物之间的相关性。组间比较显示,相对于健康对照者,AD患者右侧额叶区域的SD显著增加(<0.05)。在健康对照组中,较低的记忆评分和较高的白质高信号负担与更大的SD相关(<0.1),但在AD患者中并非如此。本研究提供了一种新型静息态fMRI分析技术的概念验证,该技术具有非侵入性、易于获取且与临床兼容的特点。为了进一步探索BOLD信号标准差(SDBOLD)作为AD生物标志物的潜力,需要在更大的纵向样本中进行更多研究,以更好地了解表征疾病进展早期阶段的SDBOLD变化及其潜在的心理生理关联。