Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
Neuroimage. 2013 May 1;71:207-15. doi: 10.1016/j.neuroimage.2013.01.015. Epub 2013 Jan 24.
An important research application of amyloid imaging with positron emission tomography (PET) is detection of the earliest evidence of fibrillar amyloid-beta (Aβ) deposition. Use of amyloid PET for this purpose, requires a reproducible method for defining a cutoff that separates individuals with no significant Aβ deposition from those in which Aβ deposition has begun. We previously reported the iterative outlier approach (IO) for the analysis of Pittsburgh Compound-B (PiB) PET data. Developments in amyloid imaging since the initial report of IO have led us to re-examine the generalizability of this method. IO was developed using full-dynamic atrophy-corrected PiB PET data obtained from a group of control subjects with a fairly distinct separation between PiB-positive [PiB(+)] and PiB-negative [PiB(-)] subjects.
We tested the performance of IO using late-summed tissue ratio data with atrophy correction or with an automated template method without atrophy correction and tested the robustness of the method when applied to a cohort of older subjects in which separation between PiB(+) and PiB(-) subjects was not so distinct.
The IO method did not perform consistently across analyses and performed particularly poorly when separation was less clear. We found that a sparse k-means (SKM) cluster analysis approach performed significantly better; performing more consistently across methods and subject cohorts. We also compared SKM to a consensus visual read approach and found very good correspondence.
The visual read and SKM methods, applied together, may optimize the identification of early Aβ deposition. These methods have the potential to provide a standard approach to the detection of PiB-positivity that is generalizable across centers.
正电子发射断层扫描（PET）淀粉样蛋白成像的一个重要研究应用是检测纤维状淀粉样蛋白-β（Aβ）沉积的最早证据。出于此目的使用淀粉样蛋白 PET 需要一种可重复的方法来定义一个截止值，该截止值将无明显 Aβ沉积的个体与已开始 Aβ沉积的个体区分开来。我们之前报道了用于分析匹兹堡化合物-B（PiB）PET 数据的迭代异常值方法（IO）。自首次报告 IO 以来，淀粉样蛋白成像的发展促使我们重新检查该方法的通用性。IO 是使用从一组具有相当明显 PiB 阳性 [PiB(+)] 和 PiB 阴性 [PiB(-)]受试者之间分离的控制受试者中获得的全动态萎缩校正 PiB PET 数据开发的。
我们使用具有萎缩校正的晚期总和组织比数据或使用无萎缩校正的自动模板方法来测试 IO 的性能，并在一个年龄较大的受试者队列中测试该方法的稳健性，其中 PiB(+) 和 PiB(-) 受试者之间的分离不那么明显。
IO 方法在分析中并未一致执行，当分离不那么明显时，其性能特别差。我们发现稀疏 k-均值（SKM）聚类分析方法表现更好；在方法和受试者队列中更一致地执行。我们还将 SKM 与共识视觉读取方法进行了比较，发现非常好的对应关系。
视觉读取和 SKM 方法结合使用，可能会优化对早期 Aβ沉积的识别。这些方法有可能为在各中心之间具有通用性的 PiB 阳性检测提供一种标准方法。
