Collagen and elastic fibers assessment of the human heart valves for age estimation in Thais using image analysis.

IF 1.5 4区 医学 Q2 MEDICINE, LEGAL Forensic Science, Medicine and Pathology Pub Date : 2024-09-01 Epub Date: 2024-04-18 DOI:10.1007/s12024-023-00775-3
Treerat Gumpangseth, Pornhatai Komutrattananont, Patison Palee, Suree Lekawanvijit, Chaturong Kanchai, Sukon Prasitwattanaseree, Pasuk Mahakkanukrauh
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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.

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利用图像分析评估泰国人心脏瓣膜的胶原蛋白和弹性纤维,以估算其年龄。
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。研究人员采集了 85 颗新鲜的人类心脏,其年龄在 20 至 90 岁之间。使用图像分析程序对瓣膜中心区域的胶原蛋白和弹性纤维密度进行了分析。使用 MATLAB 中的神经网络函数对数据进行分类,并测试年龄预测模型的准确性。总体而言,随着年龄的增长,所有类型瓣膜的胶原蛋白和弹性纤维密度都在逐渐增加。肺动脉瓣尖的胶原蛋白和弹性内容物密度最低,而二尖瓣瓣叶的胶原蛋白密度最高。三尖瓣、二尖瓣和主动脉瓣的弹性纤维也有相似之处。主动脉瓣非冠状动脉尖的胶原蛋白(r = 0.629)和弹性纤维(r = 0.713)与年龄的相关性最高。使用非冠状动脉瓣尖的胶原蛋白和弹性纤维建立的预测方程提供的标准误差分别为 ± 14.0 岁和 12.5 岁。使用胶原蛋白对所有年龄组进行分类的准确率为 60.9%,而使用神经网络对弹性纤维进行分类的准确率为 70.0%。本研究提供了有关泰国人心脏瓣膜中胶原蛋白和弹性纤维随年龄变化的更多数据,以及在年龄法医鉴定中的益处和应用。
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来源期刊
Forensic Science, Medicine and Pathology
Forensic Science, Medicine and Pathology MEDICINE, LEGAL-PATHOLOGY
CiteScore
3.90
自引率
5.60%
发文量
114
审稿时长
6-12 weeks
期刊介绍: Forensic Science, Medicine and Pathology encompasses all aspects of modern day forensics, equally applying to children or adults, either living or the deceased. This includes forensic science, medicine, nursing, and pathology, as well as toxicology, human identification, mass disasters/mass war graves, profiling, imaging, policing, wound assessment, sexual assault, anthropology, archeology, forensic search, entomology, botany, biology, veterinary pathology, and DNA. Forensic Science, Medicine, and Pathology presents a balance of forensic research and reviews from around the world to reflect modern advances through peer-reviewed papers, short communications, meeting proceedings and case reports.
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