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基于 CT 图像开发新型小鼠 PET-CT 脑图像分析工具箱及其在 PD 小鼠模型中的验证。

Development of a new toolbox for mouse PET-CT brain image analysis fully based on CT images and validation in a PD mouse model.

机构信息

Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Milan Centre for Neuroscience, University of Milano - Bicocca, Milan, Italy.

出版信息

Sci Rep. 2022 Sep 22;12(1):15822. doi: 10.1038/s41598-022-19872-4.

Abstract

Automatic analysis toolboxes are popular in brain image analysis, both in clinical and in preclinical practices. In this regard, we proposed a new toolbox for mouse PET-CT brain image analysis including a new Statistical Parametric Mapping-based template and a pipeline for image registration of PET-CT images based on CT images. The new templates is compatible with the common coordinate framework (CCFv3) of the Allen Reference Atlas (ARA) while the CT based registration step allows to facilitate the analysis of mouse PET-CT brain images. From the ARA template, we identified 27 volumes of interest that are relevant for in vivo imaging studies and provided binary atlas to describe them. We acquired 20 C57BL/6 mice with [F]FDG PET-CT, and 12 of them underwent 3D T2-weighted high-resolution MR scans. All images were elastically registered to the ARA atlas and then averaged. High-resolution MR images were used to validate a CT-based registration pipeline. The resulting method was applied to a mouse model of Parkinson's disease subjected to a test-retest study (n = 6) with the TSPO-specific radioligand [F]VC701. The identification of regions of microglia/macrophage activation was performed in comparison to the Ma and Mirrione template. The new toolbox identified 11 (6 after false discovery rate adjustment, FDR) brain sub-areas of significant [F]VC701 uptake increase versus the 4 (3 after FDR) macro-regions identified by the Ma and Mirrione template. Moreover, these 11 areas are functionally connected as found by applying the Mouse Connectivity tool of ARA. In conclusion, we developed a mouse brain atlas tool optimized for PET-CT imaging analysis that does not require MR. This tool conforms to the CCFv3 of ARA and could be applied to the analysis of mouse brain disease models.

摘要

自动分析工具在脑影像分析中很受欢迎,无论是在临床还是在临床前实践中。在这方面,我们提出了一种新的用于小鼠 PET-CT 脑影像分析的工具包,包括一个新的基于统计参数映射的模板和一个基于 CT 图像的 PET-CT 图像配准管道。新模板与 Allen 参考图谱(ARA)的常见坐标框架(CCFv3)兼容,而基于 CT 的配准步骤允许方便地分析小鼠 PET-CT 脑图像。从 ARA 模板中,我们确定了 27 个与体内成像研究相关的感兴趣区,并提供了二进制图谱来描述它们。我们获得了 20 只 C57BL/6 小鼠的 [F]FDG PET-CT,并对其中 12 只进行了 3D T2 加权高分辨率磁共振扫描。所有图像都被弹性配准到 ARA 图谱上,然后进行平均。高分辨率磁共振图像用于验证基于 CT 的配准管道。该方法应用于帕金森病小鼠模型的测试-再测试研究(n=6),使用 TSPO 特异性放射性配体 [F]VC701。与 Ma 和 Mirrione 模板相比,对小胶质细胞/巨噬细胞激活的区域进行了识别。新工具包识别出 11 个(经假发现率调整后为 6 个,FDR)大脑亚区的 [F]VC701 摄取增加,而 Ma 和 Mirrione 模板识别出 4 个(经 FDR 后为 3 个)宏观区域。此外,这些 11 个区域通过应用 ARA 的 Mouse Connectivity 工具被发现是功能连接的。总之,我们开发了一种用于 PET-CT 成像分析的优化小鼠脑图谱工具,该工具不需要磁共振成像。该工具符合 ARA 的 CCFv3,可应用于小鼠脑部疾病模型的分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53e1/9500043/3454da12baf4/41598_2022_19872_Fig1_HTML.jpg

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