Dementia Research Centre (DRC), Institute of Neurology, University College London, London, UK.
Neuroimage. 2010 Apr 1;50(2):516-23. doi: 10.1016/j.neuroimage.2009.12.059. Epub 2009 Dec 23.
We describe an improved method of measuring brain atrophy rates from serial MRI for multi-site imaging studies of Alzheimer's disease (AD). The method (referred to as KN-BSI) improves an existing brain atrophy measurement technique-the boundary shift integral (classic-BSI), by performing tissue-specific intensity normalization and parameter selection. We applied KN-BSI to measure brain atrophy rates of 200 normal and 141 AD subjects using baseline and 1-year MRI scans downloaded from the Alzheimer's Disease Neuroimaging Initiative database. Baseline and repeat images were reviewed as pairs by expert raters and given quality scores. Including all image pairs, regardless of quality score, mean KN-BSI atrophy rates were 0.09% higher (95% CI 0.03% to 0.16%, p=0.007) than classic-BSI rates in controls and 0.07% higher (-0.01% to 0.16%, p=0.07) higher in ADs. The SD of the KN-BSI rates was 22% lower (15% to 29%, p<0.001) in controls and 13% lower (6% to 20%, p=0.001) in ADs, compared to classic-BSI. Using these results, the estimated sample size (needed per treatment arm) for a hypothetical trial of a treatment for AD (80% power, 5% significance to detect a 25% reduction in atrophy rate) would be reduced from 120 to 81 (a 32% reduction, 95% CI=18% to 45%, p<0.001) when using KN-BSI instead of classic-BSI. We concluded that KN-BSI offers more robust brain atrophy measurement than classic-BSI and substantially reduces sample sizes needed in clinical trials.
我们描述了一种改进的方法,用于从阿尔茨海默病(AD)的多站点成像研究的连续 MRI 中测量脑萎缩率。该方法(称为 KN-BSI)通过执行组织特异性强度归一化和参数选择,改进了现有的脑萎缩测量技术——边界位移积分(经典-BSI)。我们应用 KN-BSI 测量了来自阿尔茨海默病神经影像学倡议数据库的 200 名正常和 141 名 AD 患者的基线和 1 年 MRI 扫描的脑萎缩率。基线和重复图像由专家评估员作为配对进行审查,并给出质量评分。包括所有图像对,无论质量评分如何,KN-BSI 萎缩率在对照组中平均高 0.09%(95%CI 0.03%至 0.16%,p=0.007),在 AD 中高 0.07%(-0.01%至 0.16%,p=0.07)。与经典-BSI 相比,KN-BSI 率的 SD 在对照组中低 22%(15%至 29%,p<0.001),在 AD 中低 13%(6%至 20%,p=0.001)。使用这些结果,对于 AD 治疗的假设试验(80%的功效,5%的显著性以检测萎缩率降低 25%),使用 KN-BSI 而不是经典-BSI 时,每个治疗臂所需的估计样本量(需要)将从 120 减少到 81(减少 32%,95%CI=18%至 45%,p<0.001)。我们得出结论,KN-BSI 提供了比经典-BSI 更稳健的脑萎缩测量,并且大大减少了临床试验所需的样本量。