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欧几里得距离映射在哮喘患者基底膜厚度分布评估中的应用。

Application of Euclidean distance mapping for assessment of basement membrane thickness distribution in asthma.

作者信息

Mostaco-Guidolin Leila, Hajimohammadi Soheil, Vasilescu Dragoş M, Hackett Tillie-Louise

机构信息

University of British Columbia, Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.

Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada; and.

出版信息

J Appl Physiol (1985). 2017 Aug 1;123(2):473-481. doi: 10.1152/japplphysiol.00171.2017. Epub 2017 Jun 8.

Abstract

Abnormal thickening of the airway basement membrane is one of the hallmarks of airway remodeling in asthma. The present protocols for measuring the basement membrane involve the use of stained tissue sections and measurements of the basement membrane thickness at certain intervals, followed by the calculation of the geometric mean thickness for each airway. This report describes an automated, unbiased approach which uses color segmentation to identify structures of interest on stained sections and Euclidean distance mapping to measure the thickness distribution of airway structures. This method was applied to study the thickness distribution of the basement membrane and airway epithelium in lungs donated for research from seven nonasthmatic and eight asthmatic age- and sex-matched donors. A total of 60 airways were assessed. We report that the thickness and thickness distribution of the basement membrane and airway epithelium are increased in large and small airways of asthmatics compared with nonasthmatics. Using this method we were able to demonstrate the heterogeneity in the thickness of the basement membrane and airway epithelium within individual airways of asthmatic subjects. This new computational method enables comprehensive and objective quantification of airway structures, which can be used to quantify heterogeneity of airway remodeling in obstructive lung diseases such as asthma and chronic obstructive pulmonary disease. The described application of Euclidean distance mapping provides an unbiased approach to study the extent and thickness distribution of changes in tissue structures. This approach will enable researchers to use computer-aided analysis of structural changes within lung tissue to understand the heterogeneity of airway remodeling in lung diseases.

摘要

气道基底膜异常增厚是哮喘气道重塑的标志性特征之一。目前测量基底膜的方法包括使用染色组织切片,并在特定间隔测量基底膜厚度,然后计算每个气道的几何平均厚度。本报告描述了一种自动化、无偏倚的方法,该方法使用颜色分割来识别染色切片上的感兴趣结构,并使用欧几里得距离映射来测量气道结构的厚度分布。该方法应用于研究7名非哮喘和8名年龄及性别匹配的哮喘供体所捐献肺组织中基底膜和气道上皮的厚度分布。共评估了60个气道。我们报告,与非哮喘患者相比,哮喘患者大、小气道的基底膜和气道上皮厚度及厚度分布均增加。使用该方法,我们能够证明哮喘患者个体气道内基底膜和气道上皮厚度的异质性。这种新的计算方法能够对气道结构进行全面、客观的量化,可用于量化哮喘和慢性阻塞性肺疾病等阻塞性肺疾病中气道重塑的异质性。所描述的欧几里得距离映射的应用为研究组织结构变化的程度和厚度分布提供了一种无偏倚的方法。这种方法将使研究人员能够利用计算机辅助分析肺组织内的结构变化,以了解肺部疾病中气道重塑的异质性。

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