Suppr超能文献

四种不同组织学染色技术对心肌梗死的检测、分离与定量分析

Detection, Isolation and Quantification of Myocardial Infarct with Four Different Histological Staining Techniques.

作者信息

Wu Xiaobo, Meier Linnea, Liu Tom X, Toldo Stefano, Poelzing Steven, Gourdie Robert G

机构信息

Center for Heart and Reparative Medicine Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA 24016, USA.

Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA.

出版信息

Diagnostics (Basel). 2024 Oct 18;14(20):2325. doi: 10.3390/diagnostics14202325.

Abstract

BACKGROUND/OBJECTIVES: The precise quantification of myocardial infarction is crucial for evaluating therapeutic strategies. We developed a robust, color-based semi-automatic algorithm capable of infarct region detection, isolation and quantification with four different histological staining techniques, and of the isolation and quantification of diffuse fibrosis in the heart.

METHODS

Our method is developed based on the color difference in the infarct and non-infarct regions after histological staining. Mouse cardiac tissues stained with Masson's trichrome (MTS), hematoxylin and eosin (H&E), 2,3,5-Triphenyltetrazolium chloride and picrosirius red were included to demonstrate the performance of our method.

RESULTS

We demonstrate that our algorithm can effectively identify and produce a clear visualization of infarct tissue in the four staining techniques. Notably, the infarct region on an H&E-stained tissue section can be clearly visualized after processing. The MATLAB-based program we developed holds promise for infarct quantification. Additionally, our program can isolate and quantify diffuse fibrotic elements from an MTS-stained cardiac section, which suggests the algorithm's potential for evaluating pathological cardiac fibrosis in diseased cardiac tissues.

CONCLUSIONS

We demonstrate that this color-based algorithm is capable of accurately identifying, isolating and quantifying cardiac infarct regions with different staining techniques, as well as diffuse and patchy fibrosis in MTS-stained cardiac tissues.

摘要

背景/目的:心肌梗死的精确量化对于评估治疗策略至关重要。我们开发了一种强大的、基于颜色的半自动算法,该算法能够通过四种不同的组织学染色技术对梗死区域进行检测、分离和量化,并能对心脏中的弥漫性纤维化进行分离和量化。

方法

我们的方法是基于组织学染色后梗死区域和非梗死区域的颜色差异开发的。纳入用Masson三色染色法(MTS)、苏木精和伊红染色法(H&E)、2,3,5-氯化三苯基四氮唑和苦味酸天狼星红染色的小鼠心脏组织,以证明我们方法的性能。

结果

我们证明,我们的算法能够在这四种染色技术中有效地识别梗死组织并使其清晰可视化。值得注意的是,经过处理后,H&E染色组织切片上的梗死区域能够清晰地可视化。我们开发的基于MATLAB的程序有望用于梗死量化。此外,我们的程序能够从MTS染色的心脏切片中分离并量化弥漫性纤维化成分,这表明该算法在评估患病心脏组织中的病理性心脏纤维化方面具有潜力。

结论

我们证明,这种基于颜色的算法能够通过不同的染色技术准确识别、分离和量化心脏梗死区域,以及MTS染色心脏组织中的弥漫性和斑片状纤维化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6ce/11507200/dd51fd76a442/diagnostics-14-02325-g005.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验