2026-06-14T03:33:05Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/66922024-09-27T07:58:38Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605

00925njm 22002777a 4500 dc Gkontra, Polyxeni author Norton, Kerri-Ann author Zak, Magdalena M. author Clemente, Cristina author Aguero, Jaume author Ibáñez, Borja author Santos, Andres author Popel, Aleksander S. author Arroyo, Alicia G author 2018 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. Sci Rep. 2018; 8(1):1854 10.1038/s41598-018-19758-4 2045-2322 Scientific Reports 29382844 http://hdl.handle.net/20.500.12105/6692 Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis