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高通量基于对象的人类和转基因小鼠脑内β-淀粉样斑块图像分析。

High throughput object-based image analysis of β-amyloid plaques in human and transgenic mouse brain.

机构信息

Neuroscience Biology, Pfizer Global Research & Development, Eastern Point Road, Groton, CT 06340, USA.

Investigative Pathology, Pfizer Global Research & Development, USA.

出版信息

J Neurosci Methods. 2012 Feb 15;204(1):179-188. doi: 10.1016/j.jneumeth.2011.10.003. Epub 2011 Oct 12.

Abstract

Advances in imaging technology have enabled automated approaches for quantitative image analysis. In this study, a high content object based image analysis method was developed for quantification of β-amyloid (Aβ) plaques in postmortem brains of Alzheimer's disease (AD) subjects and in transgenic mice over overexpressing Aβ. Digital images acquired from immunohistochemically stained sections of the superior frontal gyrus were analyzed for Aβ plaque burden using a Definiens object-based segmentation approach. Blinded evaluation of Aβ stained sections from AD and aged matched human subjects accurately identified AD cases with one exception. Brains from transgenic mice overexpressing Aβ (PS1APP mice) were also evaluated by our Definiens object based image analysis approach. We observed an age-dependent increase in the amount of Aβ plaque load that we quantified in both the hippocampus and cortex. From the contralateral hemisphere, we measured the amount of Aβ in brain homogenates biochemically and observed a significant correlation between our biochemical measurements and those that we measured by our object based Definiens system in the hippocampus. Assessment of Aβ plaque load in PS1APP mice using a manual segmentation technique (Image-Pro Plus) confirmed the results of our object-based image analysis approach. Image acquisition and analysis of 32 stained human slides and 100 mouse slides were executed in 8 h and 22 h, respectively supporting the relatively high throughput features of the Definiens platform. The data show that digital imaging combined with object based image analysis is a reliable and efficient approach to quantifying Aβ plaques in human and mouse brain.

摘要

成像技术的进步使得自动化定量图像分析成为可能。在这项研究中,我们开发了一种基于高通量对象的图像分析方法,用于定量分析阿尔茨海默病(AD)患者和过表达 Aβ 的转基因小鼠死后大脑中的β-淀粉样蛋白(Aβ)斑块。使用基于 Definiens 的对象分割方法对免疫组织化学染色的额上回切片的数字图像进行 Aβ 斑块负担分析。对 AD 和年龄匹配的人类受试者 Aβ 染色切片进行的盲法评估准确地识别了除一个例外之外的 AD 病例。我们还通过基于 Definiens 的对象的图像分析方法评估了过表达 Aβ(PS1APP 小鼠)的转基因小鼠的大脑。我们观察到,随着年龄的增长,Aβ 斑块负荷量逐渐增加,我们在海马体和皮质中对其进行了定量。从对侧大脑半球,我们通过生物化学方法测量了脑匀浆中的 Aβ 含量,并观察到我们通过基于对象的 Definiens 系统在海马体中测量的生物化学测量值与我们测量的生物化学测量值之间存在显著相关性。使用手动分割技术(Image-Pro Plus)对 PS1APP 小鼠中的 Aβ 斑块负荷进行评估,证实了我们基于对象的图像分析方法的结果。对 32 个人类染色幻灯片和 100 个小鼠幻灯片的图像采集和分析分别在 8 小时和 22 小时内完成,支持了 Definiens 平台的相对高通量特性。数据表明,数字成像结合基于对象的图像分析是一种可靠且高效的方法,可用于定量分析人类和小鼠大脑中的 Aβ 斑块。

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