van Loenhoud Anna C, Wink Alle Meije, Groot Colin, Verfaillie Sander C J, Twisk Jos, Barkhof Frederik, van Berckel Bart, Scheltens Philip, van der Flier Wiesje M, Ossenkoppele Rik
Department of Neurology and Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Hum Brain Mapp. 2017 Sep;38(9):4703-4715. doi: 10.1002/hbm.23695. Epub 2017 Jun 20.
Cognitive reserve (CR) explains interindividual differences in the ability to maintain cognitive function in the presence of neuropathology. We developed a neuroimaging approach including a measure of brain atrophy and cognition to capture this construct. In a group of 511 Alzheimer's disease (AD) biomarker-positive subjects in different stages across the disease spectrum, we performed 3T magnetic resonance imaging and predicted gray matter (GM) volume in each voxel based on cognitive performance (i.e. a global cognitive composite score), adjusted for age, sex, disease stage, premorbid brain size (i.e. intracranial volume) and scanner type. We used standardized individual differences between predicted and observed GM volume (i.e. W-scores) as an operational measure of CR. To validate this method, we showed that education correlated with mean W-scores in whole-brain (r = -0.090, P < 0.05) and temporoparietal (r = -0.122, P < 0.01) masks, indicating that higher education was associated with more CR (i.e. greater atrophy than predicted from cognitive performance). In a voxel-wise analysis, this effect was most prominent in the right inferior and middle temporal and right superior lateral occipital cortex (P < 0.05, corrected for multiple comparisons). Furthermore, survival analyses among subjects in the pre-dementia stage revealed that the W-scores predicted conversion to more advanced disease stages (whole-brain: hazard ratio [HR] = 0.464, P < 0.05; temporoparietal: HR = 0.397, P < 0.001). Our neuroimaging approach captures CR with high anatomical detail and at an individual level. This standardized method is applicable to various brain diseases or CR proxies and can flexibly incorporate different neuroimaging modalities and cognitive parameters, making it a promising tool for scientific and clinical purposes. Hum Brain Mapp 38:4703-4715, 2017. © 2017 Wiley Periodicals, Inc.
认知储备(CR)解释了在存在神经病理学情况下维持认知功能能力的个体差异。我们开发了一种神经影像学方法,包括测量脑萎缩和认知功能,以捕捉这一概念。在一组511名处于疾病谱不同阶段的阿尔茨海默病(AD)生物标志物阳性受试者中,我们进行了3T磁共振成像,并根据认知表现(即全球认知综合评分)预测每个体素的灰质(GM)体积,同时对年龄、性别、疾病阶段、病前脑大小(即颅内体积)和扫描仪类型进行了校正。我们使用预测和观察到的GM体积之间的标准化个体差异(即W分数)作为CR的操作指标。为了验证该方法,我们发现教育程度与全脑(r = -0.090,P < 0.05)和颞顶叶(r = -0.122,P < 0.01)掩码中的平均W分数相关,表明高等教育与更多的CR相关(即萎缩程度大于根据认知表现预测的程度)。在体素水平分析中,这种效应在右侧颞下和颞中以及右侧枕外侧上回最为显著(P < 0.05,经多重比较校正)。此外,对痴呆前期受试者的生存分析表明,W分数预测了向更晚期疾病阶段的转化(全脑:风险比[HR] = 0.464,P < 0.05;颞顶叶:HR = 0.397,P < 0.001)。我们的神经影像学方法能够以高解剖细节在个体水平上捕捉CR。这种标准化方法适用于各种脑部疾病或CR替代指标,并且可以灵活纳入不同的神经影像学模式和认知参数,使其成为科学和临床应用中有前景的工具。《人类大脑图谱》38:4703 - 4715,2017年。© 2017威利期刊公司。