Gumpangseth Treerat, Komutrattananont Pornhatai, Palee Patison, Lekawanvijit Suree, Kanchai Chaturong, Prasitwattanaseree Sukon, Mahakkanukrauh Pasuk
Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
Excellence Center in Osteology Research and Training Center (ORTC), Chiang Mai University, Chiang Mai, 50200, Thailand.
Forensic Sci Med Pathol. 2024 Sep;20(3):920-932. doi: 10.1007/s12024-023-00775-3. Epub 2024 Apr 18.
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.
该研究调查了三尖瓣、肺动脉瓣、二尖瓣和主动脉瓣的组织学组成与年龄之间的关系。所有85颗新鲜人类心脏均取自年龄在20至90岁之间的个体。利用图像分析程序对瓣膜的中心区域进行分析,以测定胶原纤维和弹性纤维的密度。使用MATLAB中的神经网络功能对数据进行分类,并对年龄预测模型进行准确性测试。总体而言,所有瓣膜类型中,胶原纤维和弹性纤维的密度均随年龄逐渐增加。肺动脉瓣叶的胶原和弹性成分密度最低,而二尖瓣叶中的胶原密度最高。三尖瓣、二尖瓣和主动脉瓣的弹性纤维情况相似。在主动脉瓣无冠瓣叶中,胶原纤维(r = 0.629)和弹性纤维(r = 0.713)与年龄的相关性最高。利用无冠瓣叶中的胶原纤维和弹性纤维建立的预测方程,其标准误差分别为±14.0岁和12.5岁。在所有年龄组中,使用胶原纤维进行预测的准确率为60.9%,而在使用神经网络的分类过程中,弹性纤维的准确率为70.0%。本研究提供了有关泰国人心脏瓣膜中胶原纤维和弹性纤维与年龄相关变化的更多数据,以及在年龄法医鉴定中的益处和应用。