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Collagen and elastic fibers assessment of the human heart valves for age estimation in Thais using image analysis.
- Source :
-
Forensic Science, Medicine & Pathology . Sep2024, Vol. 20 Issue 3, p920-932. 13p. - Publication Year :
- 2024
-
Abstract
- The study investigated the relationship between the histological compositions of the tricuspid, pulmonary, mitral, and aortic valves, and age. All 85 fresh human hearts were obtained with an age range between 20 and 90 years. The central area of the valves was conducted to analyze the density of collagen and elastic fibers by using an image analysis program. Neural network function in MATLAB was used for classification data and accuracy test of the age predictive model. Overall, a gradual increase in the density of collagen and elastic fibers was demonstrated with age in all valve types. The pulmonary valve cusps had the least density of collagen and elastic contents, whereas the most dense of collagen was found in the mitral leaflets. A similarity was noted for the elastic fibers in the tricuspid, mitral, and aortic valves. The highest correlation between the collagen (r = 0.629) and elastic fibers (r = 0.713) and age was found in the noncoronary cusp of the aortic valve. The established predictive equations using collagen and elastic fibers in the noncoronary cusp provided the standard error of ± 14.0 and 12.5 years, respectively. A 60.9% of accuracy was found in all age groups using collagen, while accuracy in elastic fibers showed 70.0% in the classification process using the neural networks. The current study provided additional data regarding age-associated changes of collagen and elastic fibers in the human heart valves in Thais and the benefits and application in age forensic identification. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HEART valves
*PULMONARY valve
*AORTIC valve
*IMAGE analysis
*AGE groups
Subjects
Details
- Language :
- English
- ISSN :
- 1547769X
- Volume :
- 20
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Forensic Science, Medicine & Pathology
- Publication Type :
- Academic Journal
- Accession number :
- 180587817
- Full Text :
- https://doi.org/10.1007/s12024-023-00775-3