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Full-Field Analysis Indicates Late Reperfusion Therapy Broadens and Mechanically Smooths the Borderzone During Post-Infarction Inflammation

Pearce, D. P.; Zheng, T.; Campagnola, P. J.; Witzenburg, C. M.

2025-09-07 bioengineering
10.1101/2025.09.02.673841 bioRxiv
Show abstract

Late reperfusion therapy (LRT; [&ge;] 3 hours post-MI) significantly reduces the risk of ventricular rupture following myocardial infarction (MI), yet the structural and mechanical mechanisms behind this protection remain unclear. We hypothesized that LRT would alter the biomechanical properties of the infarct borderzone and to investigate this, we utilized laser micrometry, planar biaxial testing, and quantitative polarized light imaging (QPLI) to quantify spatial variations in the geometric, mechanical, and structural properties of the left ventricle extracellular matrix (LV ECM) in adult male Sprague-Dawley rats. Rats received permanent occlusion (PO), LRT, or a sham surgery and tissue was collected 1-day post-MI, during the inflammatory phase of healing. LRT generated a larger infarct borderzone (LRT: 31.5 {+/-} 7.6 mm2; PO: 22.5 {+/-} 4.2 mm2; p < 0.05) in comparison to PO. Infarct core and borderzone stiffness was reduced post-MI, and LRT samples exhibited smoother, more consistent stiffness gradients between infarct core and remote regions than PO samples. In general, infarcted LV ECM from were thicker and more spatially variable than sham samples, but less stiff. Additionally, dynamic QPLI revealed decreased collagen fiber alignment in infarct cores relative to borders, though this did not differ between PO and LRT groups. Complementary second harmonic generation imaging revealed more gradual, consistent transitions in collagen fiber alignment throughout LV ECMs subjected to LRT, although this was limited to one sample from each group. Ultimately, these results further justify LRT and may inform future therapeutic strategies aimed at spatially modulating post-MI tissue mechanics to improve patient outcomes.

Published in Acta Biomaterialia (predicted rank #1) · training set

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