Purpose It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.
Most failures in endodontic treatment of mandibular incisors are due to the presence of a missed canal specifically the lingual. This investigation aimed to examine the root morphology and number of canals in mandibular incisors using cone beam computed tomography (CBCT). Two hundred and seven patients were assessed in terms of their mandibular central and lateral incisors of CBCT. The inclusion criteria were absence of root resorption, coronal restoration or root filling and clarity and optimal resolution of images. According to the Vertucci's classification, number of roots and canals and type of canal were evaluated by two oral and maxillofacial radiologists. In order to data analysis SPSS version 16 and descriptive statistics were implemented. All mandibular incisors had one root. Most central (84.5%) and lateral (78.2%) incisors had a single canal (p= 0.065). The majority of central (54.5%) and lateral (56.5%) incisors were Vertucci's type I (p= 0.102). Prevalence of one canal in males: central (84.8%), lateral (77.9%) and in females: central (84.2%), lateral (78.5%) (p= 0.518). Prevalence of Vertucci's type I in males: central (52.3%), lateral (45.3%) and in females: central (56.1%), lateral (64.4%) (p=0.188). The prevalence of two canals was 15.5% (central) and 21.8% (lateral) in mandibular incisors. The Vertucci's type I was the most typical kinds of mandibular incisors. Considering the limitations of periapical radiography in determining canal morphology, CBCT can be helpful in case of any concern regarding root canal morphology.
To assess the prevalence of soft tissue calcifications and their panoramic radiographic characteristics. Material and Methods: This descriptive retrospective study evaluated 2027 panoramic radiographs. The type and location of calcifications and the age and gender of patients were evaluated by two radiologists. Data were analyzed via SPSS and the Chi-square, Fisher's exact and Kappa tests were used to compare the categorical demographic variables among the groups. The confidence interval was set to 95% and p<0.05 was considered statistically significant. Results: The prevalence of calcified stylohyoid ligament was 11.24%. This value was 3.99% for tonsillolith, 1.33% for calcified carotid plaque, 0.69% for antrolith, 0.39% for calcified lymph node, 0.29% for phleboliths, and 0.19% for sialoliths. The prevalence of these conditions had no significant association with gender or age (p=0.102). The prevalence of bilateral calcified stylohyoid ligament, tonsillolith, and a calcified carotid plaque was significantly higher (p<0.001). The most prevalent type of calcified stylohyoid ligament, according to O'Carroll's classification, belonged to types 1, 4, 3 and 2 (p<0.001). The most commonly observed radiographic pattern was multiple, well-defined tonsilloliths (75.3%, p<0.001). Conclusion: The prevalence of soft tissue calcifications on panoramic radiographs was relatively low in this Iranian population. The most calcifications were respectively calcified stylohyoid ligament, tonsillolith, calcified carotid plaque, antrolith, calcified lymph node, phleboliths and sialoliths. Calcified stylohyoid ligament, tonsillolith and calcified carotid plaque were more bilaterally. Thereby panoramic imaging can help in primary assessment, epidemiologic and screening evaluation of these calcifications.
Background This study aimed to estimate the chronological age of individuals according to the correlation of age with morphological variables of the maxillary canine teeth using cone-beam computed tomography (CBCT) based on Kvaal’s method. Method This study was conducted on CBCT scans of 300 patients in Hamadan city, including 142 females and 158 males between 14 and 60 years of age. To measure the morphological variables, cross-sectional views of the maxillary right canine tooth were studied. The pulp to tooth area ratio (AR), the pulp to tooth length ratio (P), the mesiodistal and the buccolingual pulp to tooth width ratio at the cementoenamel junction (CEJ) (A1, A2), the mesiodistal and buccolingual pulp to tooth width ratio at the mid-root (C1, C2), and the mesiodistal and buccolingual pulp to tooth width ratio at the midpoint between the CEJ and the mid-root (B1, B2) were measured on CBCT scans. Results A significant inverse correlation was noted between age and all measured variables. No significant difference was found in the mean variables between males and females. The correlation between the actual age and estimated age in the regression model was 0.88. The mean square error (MSE) of prediction was 5.89 years; also, the mean absolute error (MAE) was 4.46 years. Conclusion The fitted regression model suggested in this study can estimate the age of individuals with acceptable accuracy and mean absolute error of lower than 5 years.
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