Soft tissue sample thickness measurement is one of the major sources of differences between mechanical responses published by different groups. New method for the estimation of unloaded sample thickness of soft tissues is proposed in this study. Ten 30 × 30 mm and ten 20 × 20 mm samples of porcine anterior thoracic aortas were loaded by gradually increased radial force. Their deformed thickness was then recorded in order to generate a pressure-thickness response. Next, the limit pressure to which the response can be considered linear was estimated. Line was fitted to the linear part of the curve and extrapolated towards zero pressure to estimate unloaded thickness (7 kPa fit). For comparison, data near zero pressure were fitted separately and extrapolated towards zero (Near Zero fit). The limit pressure for the linearity of the response was around 7 kPa. The Unloaded thickness for 30 × 30 mm samples was 2.68 ± 0.31 mm and 2.68 ± 0.3 mm for Near Zero fit and 7 kPa fit, respectively. The Unloaded thickness for 20 × 20 mm samples was 2.60 ± 0.35 mm and 2.59 ± 0.35 mm for Near Zero fit and 7 kPa fit, respectively. The median of thickness difference between smaller and larger samples was not found statistically different. Proposed method can estimate unloaded undeformed sample thickness quickly and reliably.

• MeSH
• aorta thoracica * MeSH
• mechanický stres MeSH
• prasata MeSH
• tlak MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

A novel method for semiautomated assessment of directions of collagen fibers in soft tissues using histological image analysis is presented. It is based on multiple rotated images obtained via polarized light microscopy without any additional components, i.e., with just two polarizers being either perpendicular or nonperpendicular (rotated). This arrangement breaks the limitation of 90° periodicity of polarized light intensity and evaluates the in-plane fiber orientation over the whole 180° range accurately and quickly. After having verified the method, we used histological specimens of porcine Achilles tendon and aorta to validate the proposed algorithm and to lower the number of rotated images needed for evaluation. Our algorithm is capable to analyze 5·105 pixels in one micrograph in a few seconds and is thus a powerful and cheap tool promising a broad application in detection of collagen fiber distribution in soft tissues.

• MeSH
• Achillova šlacha metabolismus   MeSH
• algoritmy MeSH
• extracelulární matrix metabolismus   MeSH
• kolagen metabolismus   MeSH
• mikroskopie metody   MeSH
• optické zobrazování metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• polarizační mikroskopie metody   MeSH
• prasata MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• kolagen MeSH