Analysis of new bone, cartilage, and fibrosis tissue in healing murine allografts using whole slide imaging and a new automated histomorphometric algorithm

作者：Zhang Longze; Chang Martin; Beck Christopher A; Schwarz Edward M; Boyce Brendan F^*

来源：Bone Research, 2016, 4(1): 15037.

DOI：10.1038/boneres.2015.37

Histomorphometric analysis of histologic sections of normal and diseased bone samples, such as healing allografts and fractures, is widely used in bone research. However, the utility of traditional semi-automated methods is limited because they are labor-intensive and can have high interobserver variability depending upon the parameters being assessed, and primary data cannot be re-analyzed automatically. Automated histomorphometry has long been recognized as a solution for these issues, and recently has become more feasible with the development of digital whole slide imaging and computerized image analysis systems that can interact with digital slides. Here, we describe the development and validation of an automated application (algorithm) using Visiopharm's image analysis system to quantify newly formed bone, cartilage, and fibrous tissue in healing murine femoral allografts in high-quality digital images of H&E/alcian blue-stained decalcified histologic sections. To validate this algorithm, we compared the results obtained independently using OsteoMeasure (TM) and Visiopharm image analysis systems. The intraclass correlation coefficient between Visiopharm and OsteoMeasure was very close to one for all tissue elements tested, indicating nearly perfect reproducibility across methods. This new algorithm represents an accurate and labor-efficient method to quantify bone, cartilage, and fibrous tissue in healing mouse allografts.

• 出版日期2016-1-19