Classification of amyloid-positivity in controls: comparison of visual read and quantitative approaches.
Classification of amyloid-positivity in controls: comparison of visual read and quantitative approaches.
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DOI：
10.1016/j.neuroimage.2013.01.015
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发表时间：
2013-05-01
期刊：
影响因子：
5.7
通讯作者：
Klunk WE
中科院分区：
文献类型：
--
作者：
Cohen AD;Mowrey W;Weissfeld LA;Aizenstein HJ;McDade E;Mountz JM;Nebes RD;Saxton JA;Snitz B;Dekosky S;Williamson J;Lopez OL;Price JC;Mathis CA;Klunk WE
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。为此目的使用淀粉样蛋白 PET 需要一种可重复的方法来定义界限，将没有显着 Aβ 沉积的个体与已开始 Aβ 沉积的个体分开。我们之前报道了用于分析匹兹堡化合物-B (PiB) PET 数据的迭代离群值方法 (IO)。自 IO 首次报告以来淀粉样蛋白成像的发展促使我们重新审视该方法的普遍性。 IO 是使用从一组对照受试者获得的全动态萎缩校正 PiB PET 数据开发的，PiB 阳性 [PiB(+)] 和 PiB 阴性 [PiB(−)] 受试者之间有相当明显的分离。我们使用带有萎缩校正的后期汇总组织比率数据或没有萎缩校正的自动模板方法测试了 IO 的性能，并测试了该方法在应用于一组老年受试者时的稳健性，其中 PiB(+) 和 PiB(−) 受试者之间的分离不太明显。 IO 方法在分析中的表现并不一致，并且当分离不太清晰时表现尤其差。我们发现稀疏 k 均值 (SKM) 聚类分析方法的性能明显更好；跨方法和受试者群体的表现更加一致。我们还将 SKM 与共识视觉阅读方法进行了比较，发现了非常好的对应关系。视觉读取和 SKM 方法一起应用，可以优化早期 Aβ 沉积的识别。这些方法有可能提供一种可跨中心推广的 PiB 阳性检测标准方法。
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.
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影响因子：
9.9
作者：
Rabinovici, G. D.;Furst, A. J.;Jagust, W. J.
通讯作者：
Jagust, W. J.
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作者：
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4.2
作者：
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通讯作者：
Jagust WJ