Prakash Poonam
Classified Specialist (Prosthodontics & Crown & Bridge), Command Military Dental Centre (NC), Udhampur, India.
Med J Armed Forces India. 2024 Jul-Aug;80(4):458-465. doi: 10.1016/j.mjafi.2024.04.016. Epub 2024 May 27.
The objective of this study was to investigate the utility of Cone Beam Computed Tomography (CBCT)-based pulp tooth volume- ratio of maxillary anterior teeth for accurate age estimation. The project aimed to utilize the HOROS software for image analysis and develop prediction models using regression analysis.
1800 male patients in the age group of 20 to 40 years were selected, and maxillary anterior teeth were picked. High-resolution CBCT scans were collected, and image analysis in terms of pulp volume (PV), tooth volume (TV), and pulp-volume-to-tooth-volume ratio (PV/TV) was calculated using HOROS software. Simple linear regression analysis was used to develop prediction models correlating the PV/TV with chronological age.
PV/TV of all teeth ranged between 0.073 and 0.214. Pearson correlation coefficient was used to evaluate the correlation between the chronological age and the PV/TV. It shows a statistically significant (positive) but low correlation between age and PV/TV 13 and 22 (combined), respectively, and the highest Pearson correlation (0.849) for maxillary canine (13). This study presents four models for age estimation with maximum standard error ranging between 3.5 and 4.3 and an accuracy of 96%.
This study illustrates the effectiveness of CBCT-based PV/TV of maxillary anterior teeth for age assessment. Accurate prediction models were constructed by using regression analysis and the HOROS software. These findings enhance the study of forensic odontology and have potential applications in forensic investigations, archaeological research, and legal-age assessment. Further research is necessary to validate and refine the prediction models, expanding their applicability to larger and more diverse population samples.
本研究的目的是调查基于锥束计算机断层扫描(CBCT)的上颌前牙髓腔牙体积比在准确年龄估计中的效用。该项目旨在利用HOROS软件进行图像分析,并使用回归分析开发预测模型。
选取1800名年龄在20至40岁之间的男性患者,并挑选出上颌前牙。收集高分辨率CBCT扫描图像,使用HOROS软件计算牙髓体积(PV)、牙齿体积(TV)以及牙髓体积与牙齿体积之比(PV/TV)。采用简单线性回归分析建立将PV/TV与实际年龄相关联的预测模型。
所有牙齿的PV/TV范围在0.073至0.214之间。使用Pearson相关系数评估实际年龄与PV/TV之间的相关性。结果显示,年龄与13号和22号牙(联合)的PV/TV之间存在统计学上显著的(正)但较低的相关性,而上颌尖牙(13号)的Pearson相关性最高(0.849)。本研究提出了四个年龄估计模型,最大标准误差在3.5至4.3之间,准确率为96%。
本研究说明了基于CBCT的上颌前牙髓腔牙体积比在年龄评估中的有效性。通过使用回归分析和HOROS软件构建了准确的预测模型。这些发现加强了法医牙科学的研究,并在法医调查、考古研究和法定年龄评估中具有潜在应用。有必要进行进一步研究以验证和完善预测模型,将其适用性扩展到更大且更多样化的人群样本。