TY - JOUR
T1 - An ultrastructural 3D reconstruction method for observing the arrangement of collagen fibrils and proteoglycans in the human aortic wall under mechanical load
AU - Pukaluk, Anna
AU - Wittgenstein, Anna-Sophie
AU - Leitinger, Gerd
AU - Kolb, Dagmar
AU - Pernitsch, Dominique
AU - Schneider, Sarah Anna
AU - Knöbelreiter, Patrick
AU - Horak, Verena
AU - Bredies, Kristian
AU - Holzapfel, Gerhard
AU - Pock, Thomas
AU - Sommer, Gerhard
PY - 2022
Y1 - 2022
N2 - An insight into changes of soft biological tissue ultrastructures under loading conditions is essential to understand their response to mechanical stimuli. Therefore, this study offers an approach to investigate the arrangement of collagen fibrils and proteoglycans (PGs), which are located within the mechanically loaded aortic wall. The human aortic samples were either fixed directly with glutaraldehyde in the load-free state or subjected to a planar biaxial extension test prior to fixation. The aortic ultrastructure was recorded using electron tomography. Collagen fibrils and PGs were segmented using convolutional neural networks, particularly the ESPNet model. The 3D ultrastructural reconstructions revealed a complex organization of collagen fibrils and PGs. In particular, we observed that not all PGs are attached to the collagen fibrils, but some fill the spaces between the fibrils with a clear distance to the collagen. The complex organization cannot be fully captured or can be severely misinterpreted in 2D. The approach developed opens up practical possibilities, including the quantification of the spatial relationship between collagen fibrils and PGs as a function of the mechanical load. Such quantification can also be used to compare tissues under different conditions, e.g., healthy and diseased, to improve or develop new material models.
AB - An insight into changes of soft biological tissue ultrastructures under loading conditions is essential to understand their response to mechanical stimuli. Therefore, this study offers an approach to investigate the arrangement of collagen fibrils and proteoglycans (PGs), which are located within the mechanically loaded aortic wall. The human aortic samples were either fixed directly with glutaraldehyde in the load-free state or subjected to a planar biaxial extension test prior to fixation. The aortic ultrastructure was recorded using electron tomography. Collagen fibrils and PGs were segmented using convolutional neural networks, particularly the ESPNet model. The 3D ultrastructural reconstructions revealed a complex organization of collagen fibrils and PGs. In particular, we observed that not all PGs are attached to the collagen fibrils, but some fill the spaces between the fibrils with a clear distance to the collagen. The complex organization cannot be fully captured or can be severely misinterpreted in 2D. The approach developed opens up practical possibilities, including the quantification of the spatial relationship between collagen fibrils and PGs as a function of the mechanical load. Such quantification can also be used to compare tissues under different conditions, e.g., healthy and diseased, to improve or develop new material models.
KW - Human aorta
KW - Collagen fibrils and proteoglycans
KW - Biaxial extension test
KW - Electron tomography
KW - Segmentation
U2 - 10.1016/j.actbio.2022.01.036
DO - 10.1016/j.actbio.2022.01.036
M3 - Article
VL - 141
SP - 300
EP - 314
JO - Acta Biomaterialia
JF - Acta Biomaterialia
SN - 1742-7061
ER -