Department of General Surgery, Visceral, Thoracic and Vascular Surgery, University Medical Center Greifswald, Greifswald, Germany.
University of Heidelberg, BioQuant Center, Heidelberg, Germany.
PLoS One. 2024 Apr 16;19(4):e0298830. doi: 10.1371/journal.pone.0298830. eCollection 2024.
Cryosectioning is known as a common and well-established histological method, due to its easy accessibility, speed, and cost efficiency. However, the creation of bone cryosections is especially difficult. In this study, a cryosectioning protocol for trabecular bone that offers a relatively cheap and undemanding alternative to paraffin or resin embedded sectioning was developed. Sections are stainable with common histological dying methods while maintaining sufficient quality to answer a variety of scientific questions. Furthermore, this study introduces an automated protocol for analysing such sections, enabling users to rapidly access a wide range of different stainings. Therefore, an automated 'QuPath' neural network-based image analysis protocol for histochemical analysis of trabecular bone samples was established, and compared to other automated approaches as well as manual analysis regarding scattering, quality, and reliability. This highly automated protocol can handle enormous amounts of image data with no significant differences in its results when compared with a manual method. Even though this method was applied specifically for bone tissue, it works for a wide variety of different tissues and scientific questions.
冷冻切片是一种常见且成熟的组织学方法，因其易于获取、速度快且成本效益高而被广泛应用。然而，骨组织的冷冻切片制备特别困难。在这项研究中，我们开发了一种用于小梁骨的冷冻切片方案，与石蜡或树脂包埋切片相比，该方案提供了一种相对廉价且不苛刻的替代方法。用常规的组织学染色方法对切片进行染色，同时保持足够的质量以回答各种科学问题。此外，本研究还介绍了一种用于分析此类切片的自动化方案，使用户能够快速访问各种不同的染色方法。因此，我们建立了一个基于自动化“QuPath”神经网络的用于小梁骨样本组织化学分析的图像分析协议，并与其他自动化方法以及手动分析进行了比较，包括散射、质量和可靠性。与手动方法相比，该高度自动化的方案可以处理大量的图像数据，其结果没有显著差异。尽管该方法专门应用于骨组织，但它适用于广泛的不同组织和科学问题。
