Quantification of Alzheimer-Type Neurofibrillary Lesions by Automated Image Analysis

Jeanette E. McKenzie , Gareth W. Roberts , M.Claire Royston
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引用次数: 5

Abstract

Neurofibrillary pathology is seen in a wide variety of disorders such as Alzheimer's disease (AD), progressive supranuclear palsy and the Parkinsonism-dementia amyotrophic lateral sclerosis complex of Guam. To assess the pathological importance of these lesions quantitative studies need to be undertaken. To date, most neuropathological studies have been based on qualitative, or at best semi-quantitative, data reporting the presence or absence of specific lesion types. To obtain such data traditionally involves laborious manual measurements, which rely heavily on the skill of the investigator and tend to have low inter- and intra-rater reliabilities. We have developed a novel analysis technique, using colour image analysis, which can accurately quantify the total amount of neurofibrillary damage present. Furthermore we have developed a set of mathematically defined morphological criteria to allow objective discrimination between the three types of neurofibrillary damage seen in the cortex immunostained with Alz–50. Use of this novel technique provides a reliable, rational means for the classification of neurofibrillary lesions.

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阿尔茨海默病型神经原纤维病变的自动图像分析定量
神经原纤维病变见于各种疾病,如阿尔茨海默病(AD)、进行性核上性麻痹和关岛帕金森-痴呆肌萎缩侧索硬化症。为了评估这些病变的病理重要性,需要进行定量研究。迄今为止,大多数神经病理学研究都是基于定性的,或者充其量是半定量的,报告特定病变类型存在或不存在的数据。要获得这些数据,传统上需要费力的手工测量,这在很大程度上依赖于研究者的技能,并且往往具有较低的内部和内部可靠性。我们开发了一种新的分析技术,使用彩色图像分析,可以准确地量化目前神经原纤维损伤的总量。此外,我们还开发了一套数学定义的形态学标准,以便客观区分在Alz-50免疫染色的皮层中看到的三种类型的神经原纤维损伤。这种新技术的应用为神经原纤维病变的分类提供了一种可靠、合理的方法。
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