Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis

Polyxeni Gkontra, Kerri Ann Norton, Magdalena M. Zak, Cristina Clemente, Jaume Agüero, Borja Ibáñez, Andrés Santos, Aleksander S. Popel, Alicia G. Arroyo

Research output: Contribution to journalArticle

Abstract

The microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge's potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns.

Original languageEnglish (US)
Article number1854
JournalScientific reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis'. Together they form a unique fingerprint.

  • Cite this

    Gkontra, P., Norton, K. A., Zak, M. M., Clemente, C., Agüero, J., Ibáñez, B., Santos, A., Popel, A. S., & Arroyo, A. G. (2018). Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis. Scientific reports, 8(1), [1854]. https://doi.org/10.1038/s41598-018-19758-4