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结构萎缩的远程部位可预测阿尔茨海默病小鼠模型中淀粉样蛋白的后期形成。

Remote sites of structural atrophy predict later amyloid formation in a mouse model of Alzheimer's disease.

机构信息

Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, USA.

出版信息

Neuroimage. 2010 Apr 1;50(2):416-27. doi: 10.1016/j.neuroimage.2009.12.070. Epub 2009 Dec 24.

Abstract

Magnetic resonance (MR) imaging can provide a longitudinal view of neurological disease through repeated imaging of patients at successive stages of impairment. Until recently, the difficulty of manual delineation has limited volumetric analyses of MR data sets to a few select regions and a small number of subjects. Increased throughput offered by faster imaging methods, automated segmentation, and deformation-based morphometry have recently been applied to overcome this limitation with mouse models of neurological conditions. We use automated analyses to produce an unbiased view of volumetric changes in a transgenic mouse model for Alzheimer's disease (AD) at two points in the progression of disease: immediately before and shortly after the onset of amyloid formation. In addition to the cortex and hippocampus, where atrophy has been well documented in AD patients, we identify volumetric losses in the pons and substantia nigra where neurodegeneration has not been carefully examined. We find that deficits in cortical volume precede amyloid formation in this mouse model, similar to presymptomatic atrophy seen in patients with familial AD. Unexpectedly, volumetric losses identified by MR outside of the forebrain predict locations of future amyloid formation, such as the inferior colliculus and spinal nuclei, which develop pathology at very late stages of disease. Our work provides proof-of-principle that MR microscopy can expand our view of AD by offering a complete and unbiased examination of volumetric changes that guide us in revisiting the canonical neuropathology.

摘要

磁共振(MR)成像可以通过在患者受损的连续阶段对其进行反复成像,提供对神经疾病的纵向观察。直到最近,手动勾画的困难限制了磁共振数据集的体积分析仅限于少数选定的区域和少数对象。更快的成像方法、自动化分割和基于变形的形态计量学提供的通量增加,最近已被应用于克服这种限制,以用于神经疾病的小鼠模型。我们使用自动化分析来生成阿尔茨海默病(AD)转基因小鼠模型在疾病进展的两个时间点上的体积变化的无偏视图:在淀粉样蛋白形成之前和之后不久。除了在 AD 患者中已有充分记录的皮质和海马体之外,我们还在脑桥和黑质中发现了体积损失,而这些区域的神经退行性变尚未仔细检查。我们发现,在这种小鼠模型中,皮质体积的缺陷先于淀粉样蛋白的形成,类似于家族性 AD 患者的无症状性萎缩。出乎意料的是,MR 在外脑外识别的体积损失可以预测未来淀粉样蛋白形成的位置,例如下丘和脊髓核,这些位置在疾病的很晚阶段才出现病理学。我们的工作提供了原理证明,即磁共振显微镜可以通过提供全面和无偏的体积变化检查来扩展我们对 AD 的认识,这有助于我们重新审视经典的神经病理学。

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本文引用的文献

3
Analysis of serial magnetic resonance images of mouse brains using image registration.
Neuroimage. 2009 Feb 1;44(3):692-700. doi: 10.1016/j.neuroimage.2008.10.016. Epub 2008 Oct 29.
4
Voxel-based morphometry in Alzheimer's disease.
Expert Rev Neurother. 2008 Nov;8(11):1691-702. doi: 10.1586/14737175.8.11.1691.
6
Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer's disease.
Neuroimage. 2008 Aug 1;42(1):19-27. doi: 10.1016/j.neuroimage.2008.04.252. Epub 2008 May 7.
7
Longitudinal imaging in dementia.
Br J Radiol. 2007 Dec;80 Spec No 2:S92-8. doi: 10.1259/bjr/78981552.
8
Magnetic resonance imaging characterization of brain structure and function in mild cognitive impairment: a review.
J Am Geriatr Soc. 2008 May;56(5):920-34. doi: 10.1111/j.1532-5415.2008.01684.x. Epub 2008 Apr 9.
9
MR microimaging of amyloid plaques in Alzheimer's disease transgenic mice.
Eur J Nucl Med Mol Imaging. 2008 Mar;35 Suppl 1:S82-8. doi: 10.1007/s00259-007-0706-9.

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