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使用随机森林算法分析扩散张量成像数据:健康衰老过程中白质完整性的研究

Using CForest to Analyze Diffusion Tensor Imaging Data: A Study of White Matter Integrity in Healthy Aging.

作者信息

McWhinney Sean R, Tremblay Antoine, Chevalier Thérèse M, Lim Vanessa K, Newman Aaron J

机构信息

1 Department of Psychology & Neuroscience, Dalhousie University , Halifax, Canada .

2 Department of Linguistics, Saint Mary's University , Halifax, Canada .

出版信息

Brain Connect. 2016 Dec;6(10):747-758. doi: 10.1089/brain.2016.0451. Epub 2016 Nov 28.

Abstract

Healthy aging has been associated with a global reduction in white matter integrity, which is thought to reflect cognitive decline. The present study aimed to investigate this reduction over a broad range of the life span, using diffusion tensor imaging analyzed with conditional inference random forest modeling (CForest). This approach is sensitive to subtle and potentially nonlinear effects over the age continuum and was used to characterize the progression of decline in greater detail than has been possible in the past. Data were collected from 45 healthy individuals ranging in age from 19 to 67 years. Fractional anisotropy (FA) was estimated using probabilistic tractography for a number of major tracts across the brain. Age coincided with a nonlinear decrease in FA, with onset beginning at ∼30 years of age and the steepest declines occurring later in life. However, several tracts showed a transient increase before this decline. The progression of decline varied by tract, with steeper but later decline occurring in more anterior tracts. Finally, strongly right-handed individuals demonstrated relatively preserved FA until more than a decade following the onset of decline of others. These results demonstrate that using a novel, nonparametric analysis approach, previously reported reductions in FA with healthy aging were confirmed, while at the same time, new insight was provided into the onset and progression of decline, with evidence suggesting increases in integrity continuing into adulthood.

摘要

健康老龄化与白质完整性的整体下降有关,这被认为反映了认知能力的衰退。本研究旨在使用条件推断随机森林建模(CForest)分析的扩散张量成像,在广泛的寿命范围内研究这种下降情况。这种方法对年龄连续体上的细微和潜在非线性效应敏感,并且用于比过去更详细地描述衰退的进展。数据收集自45名年龄在19至67岁之间的健康个体。使用概率纤维束成像对大脑中的多个主要纤维束估计分数各向异性(FA)。年龄与FA的非线性下降同时出现,起始于约30岁,最陡峭的下降发生在生命后期。然而,几条纤维束在这种下降之前显示出短暂的增加。衰退的进展因纤维束而异,更靠前的纤维束下降更陡峭但更晚。最后,强烈右利手个体在其他人开始衰退十多年后,其FA相对保持不变。这些结果表明,使用一种新颖的非参数分析方法,证实了先前报道的健康老龄化导致FA下降,同时,对衰退的起始和进展提供了新的见解,有证据表明完整性增加持续到成年期。

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