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使用 ADNI 前后衔接的 MP-RAGE MRI 扫描评估 SienaX 和 Siena 脑萎缩测量的可重复性。

Assessing the reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-to-back MP-RAGE MRI scans.

机构信息

Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands.

出版信息

Psychiatry Res. 2011 Sep 30;193(3):182-90. doi: 10.1016/j.pscychresns.2011.02.012. Epub 2011 Jul 18.

DOI:10.1016/j.pscychresns.2011.02.012
PMID:21764565
Abstract

SienaX and Siena are widely used and fully automated algorithms for measuring whole brain volume and volume change in cross-sectional and longitudinal MRI studies and are particularly useful in studies of brain atrophy. The reproducibility of the algorithms was assessed using the 3D T1 weighted MP-RAGE scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The back-to-back (BTB) MP-RAGE scans in the ADNI data set makes it a valuable benchmark against which to assess the performance of algorithms of measuring atrophy in the human brain with MRI scans. A total of 671 subjects were included for SienaX and 385 subjects for Siena. The annual percentage brain volume change (PBVC) rates were -0.65±0.82%/year for the healthy controls, -1.15±1.21%/year for mild cognitively impairment (MCI) and -1.84±1.33%/year for AD, in line with previous findings. The median of the absolute value of the reproducibility of SienaX's normalized brain volume (NBV) was 0.96% while the 90th percentile was 5.11%. The reproducibility of Siena's PBVC had a median of 0.35% and a 90th percentile of 1.37%. While the median reproducibility for SienaX's NBV was in line with the values previously reported in the literature, the median reproducibility of Siena's PBVC was about twice that reported. Also, the 90th percentiles for both SienaX and Siena were about twice the size that would be expected for a Gaussian distribution. Because of the natural variation of the disease among patients over a year, a perfectly reproducible whole brain atrophy algorithm would reduce the estimated group size needed to detect a specified treatment effect by only 30% to 40% as compared to Siena's.

摘要

SienaX 和 Siena 是广泛使用且完全自动化的算法,用于测量横断面和纵向 MRI 研究中的全脑体积和体积变化,特别适用于脑萎缩研究。该算法的可重复性使用阿尔茨海默病神经影像学倡议 (ADNI) 研究的 3D T1 加权 MP-RAGE 扫描进行评估。ADNI 数据集中的背靠背 (BTB) MP-RAGE 扫描使其成为评估 MRI 扫描测量人脑萎缩算法性能的有价值基准。共有 671 名受试者用于 SienaX,385 名受试者用于 Siena。健康对照组的年脑容量变化率 (PBVC) 为 -0.65±0.82%/年,轻度认知障碍 (MCI) 为 -1.15±1.21%/年,阿尔茨海默病为 -1.84±1.33%/年,与之前的发现一致。SienaX 归一化脑体积 (NBV) 可重复性的中位数为 0.96%,90%分位数为 5.11%。Siena 的 PBVC 可重复性中位数为 0.35%,90%分位数为 1.37%。虽然 SienaX 的 NBV 可重复性中位数与文献中之前报道的值一致,但 Siena 的 PBVC 可重复性中位数大约是其两倍。此外,SienaX 和 Siena 的 90%分位数大约是高斯分布的两倍。由于疾病在患者之间的自然变化,与 Siena 相比,一个完全可重复的全脑萎缩算法只会将检测特定治疗效果所需的估计组大小减少 30%至 40%。

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