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在有记忆缺陷的三级临床人群中,皮质淀粉样蛋白与皮质厚度之间相关性的空间模式。

Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit.

机构信息

Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, USA.

Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.

出版信息

Sci Rep. 2020 Nov 26;10(1):20717. doi: 10.1038/s41598-020-77503-2.

DOI:10.1038/s41598-020-77503-2
PMID:33244036
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7693188/
Abstract

To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.

摘要

为了在临床上估计区域阿尔茨海默病(AD)病理学负担,需要分析方法来跟踪大脑淀粉样蛋白或tau 正电子发射断层扫描(PET)与磁共振成像(MRI)测量的相关性。因此,我们开发了一种强大的 MRI 分析方法来识别与 PET 图像中区域淀粉样蛋白负担线性相关的大脑区域。该方法旨在通过使用全脑建模、非线性图像配准和部分体积校正来减少数据方差并提高皮质厚度-淀粉样蛋白相关性检测的灵敏度。使用该方法对 75 名三级记忆诊所 AD 患者进行了横断面分析,以检验我们的假设,即内侧颞叶新皮质区域的区域淀粉样蛋白负担与皮质厚度呈负相关。内侧颞叶皮质厚度与区域淀粉样蛋白负担无关,而外侧颞叶、外侧顶叶和额叶区域的皮质厚度与淀粉样蛋白负担呈负相关。这项研究证明了我们的技术的稳健性,该技术结合了全脑建模、非线性图像配准和部分体积校正,以跟踪特定脑区中区域淀粉样蛋白负担与皮质变薄之间的差异相关性。该方法可与淀粉样蛋白和 tau PET 一起用于评估相应的皮质厚度变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/3efe617b66a4/41598_2020_77503_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/5a0c07457b12/41598_2020_77503_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/945abf5d6b82/41598_2020_77503_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/f4e7f15d784c/41598_2020_77503_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/3efe617b66a4/41598_2020_77503_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/5a0c07457b12/41598_2020_77503_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/945abf5d6b82/41598_2020_77503_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/f4e7f15d784c/41598_2020_77503_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfce/7693188/3efe617b66a4/41598_2020_77503_Fig4_HTML.jpg

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A Comparison of Partial Volume Correction Techniques for Measuring Change in Serial Amyloid PET SUVR.
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