[18F]-MK6240 PET的空间配准评价

James Zou, Aubrey Johnson, Jeanelle France, S. Bharadwaj, Zeljko Tomljanovic, Y. Stern, A. Brickman, D. Devanand, J. Luchsinger, W. Kreisl, F. Provenzano
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摘要

图像配准是神经成像中一个重要的预处理步骤,它允许在模式和对象之间匹配解剖和功能信息。如果在图像几何形状或信号强度上存在明显差异,例如在一些分子PET放射配体的情况下,对照受试者显示相对于颅内区域的噪声相对缺乏信号,并且可能与其他区域混淆,并且可能因受试者而异。在这种情况下,使用中间图像或卷已被证明有助于注册。为了在我们自己的纵向老龄化队列中解释这一现象,我们从30个淀粉样蛋白阴性受试者的广泛分布中生成了一个特定人群的MRI和PET模板。然后,我们使用三套不同的配准参数和程序,将这些受试者的PET图像,以及一组由30名“未使用模板”的受试者组成的保留组与他们相应的MRI图像进行配准,使用模板图像作为中间物。为了评估常规配准和我们的方法的性能,我们将它们与作为参考的衰减CT(在PET采集时获得)与MRI的配准进行了比较。然后,我们使用我们的模板直接导出SUVR值,而不使用MRI。我们发现传统的配准与现有的基于CT的标准相当,所有测试方法的总体误差没有显著差异。此外,现有的tau PET定量方法与无mr的方法之间没有显著差异。我们得出结论,基于模板的方法是一种可行的替代方案,或挽救,直接登记和无磁共振量化;并且,在对两个图像模态之间的相似性有疑问的情况下,可以优选。
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Spatial Registration Evaluation of [18F]-MK6240 PET
Image registration is an important preprocessing step in neuroimaging which allows for the matching of anatomical and functional information between modalities and subjects. This can be challenging if there are gross differences in image geometry or in signal intensity, such as in the case of some molecular PET radioligands, where control subjects display relative lack of signal relative to noise within intracranial regions, and may have off target binding that may be confused as other regions, and may vary depending on subject. The use of intermediary images or volumes have been shown to aide registration in such cases. To account for this phenomena within our own longitudinal aging cohort, we generated a population specific MRI and PET template from a broad distribution of 30 amyloid negative subjects. We then registered the PET image of each of these subjects, as well as a holdout set of thirty 'template-naive' subjects to their corresponding MRI images using the template image as an intermediate using three different sets of registration parameters and procedures. To evaluate the performance of both conventional registration and our method, we compared these to the registration of the attenuation CT (acquired at time of PET acquisition) to MRI as the reference. We then used our template to directly derive SUVR values without the use of MRI. We found that conventional registration was comparable to an existing CT based standard, and there was no significant difference in errors collectively amongst all methods tested. In addition, there were no significant differences between existing and MR-less tau PET quantification methods. We conclude that a template-based method is a feasible alternative to, or salvage for, direct registration and MR-less quantification; and, may be preferred in cases where there is doubt about the similarity between two image modalities.
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