Clarkson Matthew J, Ourselin Sébastien, Nielsen Casper, Leung Kelvin K, Barnes Josephine, Whitwell Jennifer L, Gunter Jeffrey L, Hill Derek L G, Weiner Michael W, Jack Clifford R, Fox Nick C
Dementia Research Centre, University College London, Institute of Neurology, London, UK.
Neuroimage. 2009 Oct 1;47(4):1506-13. doi: 10.1016/j.neuroimage.2009.05.045. Epub 2009 May 27.
Rates of brain atrophy derived from serial magnetic resonance (MR) studies may be used to assess therapies for Alzheimer's disease (AD). These measures may be confounded by changes in scanner voxel sizes. For this reason, the Alzheimer's Disease Neuroimaging Initiative (ADNI) included the imaging of a geometric phantom with every scan. This study compares voxel scaling correction using a phantom with correction using a 9 degrees of freedom (9DOF) registration algorithm. We took 129 pairs of baseline and 1-year repeat scans, and calculated the volume scaling correction, previously measured using the phantom. We used the registration algorithm to quantify any residual scaling errors, and found the algorithm to be unbiased, with no significant (p=0.97) difference between control (n=79) and AD subjects (n=50), but with a mean (SD) absolute volume change of 0.20 (0.20) % due to linear scalings. 9DOF registration was shown to be comparable to geometric phantom correction in terms of the effect on atrophy measurement and unbiased with respect to disease status. These results suggest that the additional expense and logistic effort of scanning a phantom with every patient scan can be avoided by registration-based scaling correction. Furthermore, based upon the atrophy rates in the AD subjects in this study, sample size requirements would be approximately 10-12% lower with (either) correction for voxel scaling than if no correction was used.
通过系列磁共振(MR)研究得出的脑萎缩率可用于评估阿尔茨海默病(AD)的治疗方法。这些测量结果可能会因扫描仪体素大小的变化而受到混淆。因此,阿尔茨海默病神经影像学倡议(ADNI)在每次扫描时都纳入了一个几何体模的成像。本研究比较了使用体模进行体素缩放校正与使用九自由度(9DOF)配准算法进行校正的效果。我们获取了129对基线扫描和1年重复扫描数据,并计算了之前使用体模测量的体积缩放校正值。我们使用配准算法来量化任何残留的缩放误差,发现该算法无偏差,对照组(n = 79)和AD患者组(n = 50)之间无显著差异(p = 0.97),但由于线性缩放,平均(标准差)绝对体积变化为0.20(0.20)%。在对萎缩测量的影响方面,9DOF配准与几何体模校正相当,且与疾病状态无关。这些结果表明,通过基于配准的缩放校正可以避免每次对患者进行扫描时扫描体模所带来的额外费用和后勤工作。此外,根据本研究中AD患者的萎缩率,与不进行校正相比,使用(任何一种)体素缩放校正时样本量要求大约低10 - 12%。