The Alzheimer Structural Connectome: Changes in Cortical Network Topology with Increased Amyloid Plaque Burden
The Alzheimer Structural Connectome: Changes in Cortical Network Topology with Increased Amyloid Plaque Burden
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DOI：
10.1148/radiol.14132593
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发表时间：
2014-10-01
期刊：
影响因子：
19.7
通讯作者：
Petrella, Jeffrey R.
中科院分区：
文献类型：
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作者：
Prescott, Jeffrey W.;Guidon, Arnaud;Petrella, Jeffrey R.
目的：评估正常认知（NC）、轻度认知障碍（MCI）和阿尔茨海默病（AD）患者之间结构连接体的差异，并确定结构连接体与皮质淀粉样蛋白沉积之间的关联。材料和方法：入组多中心生物标志物研究的患者（阿尔茨海默病神经影像学倡议[ADNI] 2）进行基线扩散张量（DT）和florbetapir正电子发射断层扫描（PET）研究了2012年11月数据分析时的数据。所有机构都得到了机构审查委员会的批准。ADNI 2中有102例患者符合分析标准。患者的T1加权图像被自动分成感兴趣的皮质区域。根据复合皮质区域（额叶、扣带回、顶叶和颞叶）的florbetapir PET图像计算标准化摄取值比率（SUVr）。从DT图像创建结构连接体图，并通过使用图论度量分析每个区域中的连接体拓扑结构。进行了诊断组间结构连接体指标和florbetapir SUVr的方差分析。拟合线性混合效应模型以分析florbetapir SUVr对结构连接体指标的影响。（NC、MCI或AD）与加权结构连接体指标的变化相关，从NC组到MCI组再到AD组，（a）双侧额叶、右顶叶和双侧颞叶区域的强度降低（P < .05）;（B）左颞区的加权局部效率（P < .05）;和（c）双侧额区和左颞区的加权聚类系数（P < .05）。皮质florbetapir SUVr的增加与加权结构连接体指标的降低相关;即强度（P = .00001）、加权局部效率（P = .00001）和加权聚类系数（P = .0006），与大脑区域无关。对于每0.1单位的florbetapir SUVr增加，强度降低14%，加权局部效率降低11%，加权聚类系数降低9%，无论分析的皮质区域或诊断组（在加权局部效率和聚类系数的情况下）如何。用florbetapir PET成像测量的淀粉样蛋白负荷增加与用DTI纤维束成像的图形理论度量测量的大脑大规模皮质网络结构的拓扑结构的变化有关，甚至在AD的临床前阶段。
Purpose: To evaluate differences in the structural connectome among patients with normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer disease (AD) and to determine associations between the structural connectome and cortical amyloid deposition.Materials and Methods: Patients enrolled in a multicenter biomarker study (Alzheimer's Disease Neuroimaging Initiative [ADNI] 2) who had both baseline diffusion-tensor (DT) and florbetapir positron emission tomography (PET) data at the time of data analyses in November 2012 were studied. All institutions received institutional review board approval. There were 102 patients in ADNI 2 who met criteria for analysis. Patients' T1-weighted images were automatically parcellated into cortical regions of interest. Standardized uptake value ratio (SUVr) was calculated from florbetapir PET images for composite cortical regions (frontal, cingulate, parietal, and temporal). Structural connectome graphs were created from DT images, and connectome topology was analyzed in each region by using graph theoretical metrics. Analysis of variance of structural connectome metrics and florbetapir SUVr across diagnostic group was performed. Linear mixed-effects models were fit to analyze the effect of florbetapir SUVr on structural connectome metrics.Results: Diagnostic group (NC, MCI, or AD) was associated with changes in weighted structural connectome metrics, with decreases from the NC group to the MCI group to the AD group shown for (a) strength in the bilateral frontal, right parietal, and bilateral temporal regions (P < .05); (b) weighted local efficiency in the left temporal region (P < .05); and (c) weighted clustering coefficient in the bilateral frontal and left temporal regions (P < .05). Increased cortical florbetapir SUVr was associated with decreases in weighted structural connectome metrics; namely, strength (P = .00001), weighted local efficiency (P = .00001), and weighted clustering coefficient (P = .0006), independent of brain region. For every 0.1-unit increase in florbetapir SUVr, there was a 14% decrease in strength, an 11% decrease in weighted local efficiency, and a 9% decrease in weighted clustering coefficient, regardless of the analyzed cortical region or, in the case of weighted local efficiency and clustering coefficient, diagnostic group.Conclusion: Increased amyloid burden, as measured with florbetapir PET imaging, is related to changes in the topology of the large-scale cortical network architecture of the brain, as measured with graph theoretical metrics of DTI tractography, even in the preclinical stages of AD.