
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.16.608294
preprint
1
Article
Detection, Isolation and Quantification of Myocardial Infarct with Four Different Histological Staining Techniques
Wu Xiaobo http://orcid.org/0000-0002-3136-5059

Meier Linnea
Liu Tom X
Toldo Stefano
Poelzing Steven
Gourdie Robert G. http://orcid.org/0000-0001-6021-0796

19 8 2024
2024.08.16.608294https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
http://biorxiv.org/lookup/doi/10.1101/2024.08.16.608294
nihpp-2024.08.16.608294.pdf
Abstract

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