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A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume.

机译:使用基于自动图集的头部大小归一化在年轻人,老年人和痴呆症成年人中进行形态计量和功能数据分析的统一方法:可靠性和针对人工测量颅内总体积的验证。

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Atlas normalization, as commonly used by functional data analysis, provides an automated solution to the widely encountered problem of correcting for head size variation in regional and whole-brain morphometric analyses, so long as an age- and population-appropriate target atlas is used. In the present article, we develop and validate an atlas normalization procedure for head size correction using manual total intracranial volume (TIV) measurement as a reference. The target image used for atlas transformation consisted of a merged young and old-adult template specifically created for cross age-span normalization. Automated atlas transformation generated the Atlas Scaling Factor (ASF) defined as the volume-scaling factor required to match each individual to the atlas target. Because atlas normalization equates head size, the ASF should be proportional to TIV. A validation analysis was performed on 147 subjects to evaluate ASF as a proxy for manual TIV measurement. In addition, 19 subjects were imaged onmultiple days to assess test-retest reliability. Results indicated that the ASF was (1) equivalent to manual TIV normalization (r = 0.93), (2) reliable across multiple imaging sessions (r = 1.00; mean absolute percentage of difference = 0.51%), (3) able to connect between-gender head size differences, and (4) minimally biased in demented older adults with marked atrophy. Hippocampal volume differences between nondemented (n = 49) and demented (n = 50) older adults (measured manually) were equivalent whether corrected using manual TIV or automated ASF (effect sizes of 1.29 and 1.46, respectively). To provide normative values, ASF was used to automatically derive estimated TIV (eTIV) in 335 subjects aged 15-96 including both clinically characterized nondemented (n = 77) and demented (n = 90) older adults. Differences in eTIV between nondemented and demented groups were negligible, thus failing to support the hypothesis that large premorbid brain size moderates Alzheimer's disease. Gender was the only robust factor that influenced eTIV. Men showed an approximately approximately 12% larger eTIV than women. These results demonstrate that atlas normalization using appropriate template images provides a robust, automated method for head size correction that is equivalent to manual TIV correction in studies of aging and dementia. Thus, atlas normalization provides a common framework for both morphometric and functional data analysis.
机译:功能图数据分析通常使用的Atlas归一化为解决在区域和全脑形态分析中校正头部尺寸变化而广泛遇到的问题提供了一种自动解决方案,只要使用了适合年龄和人群的目标Atlas。在本文中,我们使用人工总颅内体积(TIV)测量作为参考,开发并验证了用于校正头部大小的图集标准化程序。用于图集转换的目标图像由专门为跨年龄跨度归一化创建的年轻成人模板和合并成人模板组成。自动的图集转换生成了图集缩放因子(ASF),该因子定义为使每个人与图集目标匹配所需的体积缩放因子。因为图集标准化等于头部尺寸,所以ASF应该与TIV成正比。对147位受试者进行了验证分析,以评估ASF作为人工TIV测量的指标。此外,多天对19位受试者进行了成像,以评估重测信度。结果表明,ASF相当于(1)等效于手动TIV归一化(r = 0.93),(2)在多个成像期间均可靠(r = 1.00;平均绝对差值= 0.51%),(3)能够相互关联-性别的头部大小差异,以及(4)患有明显萎缩的老年痴呆症患者的偏倚程度最低。无论是使用手动TIV还是自动ASF校正(无效果的老年人(n = 49)和有痴呆的患者(n = 50))的海马体积差异均相等(效果大小分别为1.29和1.46)。为了提供标准值,ASF被用于自动得出335名15-96岁受试者的估计TIV(eTIV),包括临床特征为非痴呆(n = 77)和痴呆(n = 90)的成年人。非痴呆组和痴呆组之间eTIV的差异可忽略不计,因此无法支持病前大大脑可缓解阿尔茨海默氏病的假说。性别是影响eTIV的唯一稳健因素。男性的eTIV大约比女性高12%。这些结果表明,使用适当的模板图像对地图集进行归一化提供了一种健壮的,自动的头部大小校正方法,该方法等效于在衰老和痴呆症研究中进行手动TIV校正。因此,图集标准化为形态分析和功能数据分析提供了一个通用框架。

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