Avants Brian, Cook Philip A, McMillan Corey, Grossman Murray, Tustison Nicholas J, Zheng Yuanjie, Gee James C
Dept. of Radiology, University of Pennsylvania, Philadelphia, PA 19104-6389 USA.
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):324-31. doi: 10.1007/978-3-642-15705-9_40.
We present a new algorithm for reliable, unbiased, multivariate longitudinal analysis of cortical and white matter atrophy rates with penalized statistical methods. The pipeline uses a step-wise approach to transform and personalize template information first to a single-subject template (SST) and then to the individual's time series data. The first stream of information flows from group template to the SST; the second flows from the SST to the individual time-points and provides unbiased, prior-based segmentation and measurement of cortical thickness. MRI-bias correction, consistent longitudinal segmentation, cortical parcellation and cortical thickness estimation are all based on strong use of the subject-specific priors built from initial diffeomorphic mapping between the SST and optimal group template. We evaluate our approach with both test-retest data and with application to a driving biological problem. We use test-retest data to show that this approach produces (a) zero change when the retest data contains the same image content as the test data and (b) produces normally distributed, low variance estimates of thickness change centered at zero when test-retest data is collected near in time to test data. We also show that our approach--when combined with sparse canonical correlation analysis--reveals plausible, significant, annualized decline in cortical thickness and white matter volume when contrasting frontotemporal dementia and normal aging.
我们提出了一种新算法，用于采用惩罚统计方法对皮质和白质萎缩率进行可靠、无偏的多变量纵向分析。该流程采用逐步方法，首先将模板信息转换并个性化到单主体模板（SST），然后再转换到个体的时间序列数据。第一信息流从群体模板流向SST；第二信息流从SST流向各个时间点，并提供基于先验的无偏分割和皮质厚度测量。MRI偏差校正、一致的纵向分割、皮质分区和皮质厚度估计均强烈依赖于基于SST与最佳群体模板之间初始微分同胚映射构建的特定主体先验。我们使用重测数据以及将其应用于一个驱动生物学问题来评估我们的方法。我们使用重测数据表明，当重测数据包含与测试数据相同的图像内容时，该方法产生（a）零变化；当重测数据在时间上接近测试数据收集时，该方法产生以零为中心的正态分布、低方差的厚度变化估计值。我们还表明，当我们的方法与稀疏典型相关分析相结合时，在对比额颞叶痴呆和正常衰老时，揭示了皮质厚度和白质体积合理、显著的年化下降。
