将全景 X 光片上的牙齿特征作为无创年龄估算参数:一项试点研究。

IF 1.4 Q3 ANATOMY & MORPHOLOGY
Anatomy & Cell Biology Pub Date : 2023-12-31 Epub Date: 2023-09-11 DOI:10.5115/acb.23.140
Harin Cheong, Akiko Kumagai, Sehyun Oh, Sang-Seob Lee
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引用次数: 0

摘要

后天牙科治疗所形成的牙齿特征可用作年龄估计指标。这项试验性研究旨在分析牙齿特征观察到的牙齿数量与实际年龄之间的相关性,并开发新的非侵入性年龄估计模型。研究人员对全景X光片上的牙齿特征进行了分类和编码(420张20-89岁受试者的X光片)。观察每个选定代码(代码 V、X、T、F、P 和 L)的牙齿数量与年龄之间的相关性,并进行多元回归分析它们之间的关系。结果显示了 11 个不同牙齿六分仪组合的回归模型。使用双侧颌骨后牙数据的模型表现最佳(均方根误差为 14.78 岁,调整后 R2 为 0.461)。包含所有牙齿的模型次之。基于这些结果,我们证实了某些牙齿特征与年代年龄之间存在统计学意义上的显著相关性。我们还发现,一些回归模型的表现足以在法医实践中作为辅助方法使用。这些结果为今后全面研究的设计和实施提供了宝贵的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dental characteristics on panoramic radiographs as parameters for non-invasive age estimation: a pilot study.

The dental characteristics created by acquired dental treatments can be used as age estimators. This pilot study aimed to analyze the correlation between the number of teeth observed for dental characteristics and chronological age and to develop new non-invasive age estimation models. Dental features on panoramic radiographs (420 radiographs of subjects aged 20-89 years) were classified and coded. The correlation between the number of teeth for each selected code (codes V, X, T, F, P, and L) and age was observed, and multiple regression was performed to analyze the relationship between them. Eleven regression models with various combinations of dental sextants were presented. The model with the data from both sides of the posterior teeth on both jaws showed the best performance (root mean square error of 14.78 years and an adjusted R2 of 0.461). The model with all teeth was the second-best. Based on these results, we confirmed statistically significant correlations between certain dental features and chronological age. We also observed that some regression models performed sufficiently well to be used as adjunctive methods in forensic practice. These results provide valuable information for the design and performance of future full-scale studies.

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来源期刊
Anatomy & Cell Biology
Anatomy & Cell Biology ANATOMY & MORPHOLOGY-
CiteScore
1.80
自引率
9.10%
发文量
75
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