Shetty Divya, Kumari Shanvi, Gulati Nikita, Shetty Devi Charan
Department of Orthodontics and Dentofacial Orthopaedics and Research, I.T.S. Centre for Dental Studies and Research, Muradnagar, Ghaziabad, U.P, 201206, India.
Department of Oral and Maxillofacial Pathology and Microbiology, I.T.S. Centre for Dental Studies and Research, Muradnagar, Ghaziabad, U.P, 201206, India.
J Oral Biol Craniofac Res. 2025 Sep-Oct;15(5):1115-1122. doi: 10.1016/j.jobcr.2025.07.012. Epub 2025 Jul 28.
Forensic odontology has gained prominence due to the reliability of dental evidence in investigations. Tooth enamel, a highly mineralized and durable tissue, resists postmortem degradation. If its histological features can accurately indicate age, species, or gender, it could serve as a valuable forensic tool. This study aimed to evaluate enamel structures histologically for age assessment.
A total of 120 premolar samples (ages 12-55) from the first quadrant were analysed. Linear enamel hypoplasia was examined using a stereomicroscope, followed by ground sections to count lamellae. Hypo-mineralization zones were assessed under a polarizing microscope using Magnus Pro morphometric software.
The best variable for determining age was found by examining three distinct predictive accuracy models; the C5.0 model had the highest accuracy (85.30 %), followed by the CRT model (60.80 %) and the CHAID model (58.30 %). The lamellae number was the most significant predictor of age, with age group 2 (0.853) followed by group 1 (0.790) and group 3 (0.659).
Each individual has a unique enamel profile, which can aid in identifying victims of mass disasters or severely damaged remains. Dentists are encouraged to routinely document enamel defects to support future forensic comparisons with dental records.
由于牙科证据在调查中的可靠性，法医牙科学已变得日益重要。牙釉质是一种高度矿化且耐用的组织，能抵抗死后降解。如果其组织学特征能准确指示年龄、物种或性别，它可作为一种有价值的法医工具。本研究旨在从组织学角度评估牙釉质结构以进行年龄评估。
对来自第一象限的总共120颗前磨牙样本（年龄12 - 55岁）进行分析。使用体视显微镜检查线性牙釉质发育不全，随后制作磨片以计数釉板。使用Magnus Pro形态测量软件在偏光显微镜下评估矿化不足区域。
通过检查三种不同的预测准确性模型，发现了用于确定年龄的最佳变量；C5.0模型的准确性最高（85.30%），其次是CRT模型（60.80%）和CHAID模型（58.30%）。釉板数量是年龄的最显著预测指标，年龄组2（0.853）其次是年龄组1（0.790）和年龄组3（0.659）。
每个人都有独特的牙釉质特征，这有助于识别大规模灾难的受害者或严重受损的遗体。鼓励牙医常规记录牙釉质缺陷，以支持未来与牙科记录进行法医比对。
