Maxillary canine teeth were used in this study because they are single-rooted and have a single canal as well as a well-defined pulp chamber. Moreover, most individuals retain their maxillary canines until old ages and these teeth are less worn over time. Indira et al. (2015) chose the maxillary left central incisors in their study. Cameriere et al. (2012) chose the mandibular premolars. Afify et al. evaluated mandibular canines and premolars (Afify et al., 2014).
The Kvaal’s method is the gold standard of age estimation using pulp to tooth ratio, which was used as the basis in our study. This method has been used in other studies as well (Kvaal et al. 1995; Cameriere et al. 2007; Babshet et al. 2010). Assessment of the pulp to tooth area ratio, in particular, is an indirect indicator of secondary dentin deposition. In the current study, the Pearson’s correlation coefficient indicated an inverse correlation between age and all morphological variables. This finding indicated that the mean of different variables decreased by aging. These results were in agreement with those of Cameriere et al. (2007). Kvaal et al. (1995) also showed that the correlation coefficient for the correlation between age and most of the measured ratios was negative. Jeon et al. (2015) reported that the ratio of height from the pulp chamber floor to the furcation area to the crown length was the only variable that had a positive correlation with age. These results indicate that the deposition of secondary dentin is a continuous, age-dependent phenomenon. By an increase in age and deposition of secondary dentin, the size of the pulp chamber decreases.
In the current study, the strongest negative correlation was noted between age and AR while the weakest negative correlation was noted between age and P. Juneja et al. (2014) reported that AR had the strongest negative correlation with age. Moreover, horizontal ratios compared with longitudinal ratios had a stronger correlation with age and it can be stated that they are more accurate indices for age estimation. These results were in line with those of Kvaal et al., Indira et al., Bosmans et al., and Cameriere et al. (Kvaal et al., 1995; Indira et al., 2015; Bosmans et al., 2005; Cameriere et al., 2009). It seems that longitudinal ratios cannot serve as acceptable indices for age estimation due to the confounding effect of factors such as attrition, type of occlusion, or behavioral habits. Cameriere et al. reported that the pulp to tooth AR in mandibular premolars was a suitable variable for age estimation with acceptable accuracy, and this ratio decreased with aging, which was in line with the current findings (Cameriere et al. 2012).
In our study, no significant difference was noted between males and females in the mean variables. Saxena found no significant difference in morphological variables between males and females (Saxena 2011). Cameriere et al., Babshet et al., Afify et al., and Mathew et al. found no significant difference between males and females either (Cameriere et al. 2012; Babshet et al. 2010; Afify et al. 2014; Mathew et al., 2013). Their findings were in agreement with ours. Yayun et al. found a significant difference between males and females in a Chinese population and reported that in males, the canal/root diameter ratio had a greater correlation with the estimated age compared with females (Wu et al., 2016). Zaher et al. found a significant difference between males and females as well (Zaher et al. 2011). Angles et al. showed a moderate correlation between the pulp to tooth volume ratio and estimated age in females while this correlation was weak in males; however, this difference did not reach statistical significance (De Angelis et al., 2015). Star et al. showed that the correlation between pulp to tooth volume ratio and age in females was stronger than that in males, but it was not significant (Star et al. 2011). Thus, there would be no reason to justify using gender along with ratio and type of tooth for age estimation. Data analysis by Azrak et al. revealed that using the obtained models, age estimation in females was slightly more accurate than in males (Azrak et al. 2007). Kvaal et al. reported that gender was a predictive factor only for the mandibular lateral incisors, and since this value was negative, they concluded that pulpal changes in males occur faster than in females (Kvaal et al. 1995). According to the aforementioned studies, taking into account the race and type of tooth, gender may be an influential factor in age estimation.
In the current study, the regression model obtained by using the forward method showed that only P, B1, A1, A2, and AR had a significant correlation with age. In a study by Saxena, of all the measured variables, only AR and C had significant correlations with age (Saxena 2011). In the study by Cameriere et al., a significant correlation was noted between AR of mandibular premolars and age, and this ratio was considered as a valuable variable for age estimation with acceptable accuracy (Cameriere et al. 2012). Juneja et al. evaluated the maxillary canine teeth and showed that AR and B parameters were more influential and were used in the regression model (Juneja et al., 2014).
Landa et al. reported the highest correlation for B ratio in the first premolars of both males and females (Landa et al. 2009). All the abovementioned findings are in agreement with our results. However, we did further evaluations and measured the pulp width at three levels of A, B, and C from both the buccolingual and mesiodistal directions, which has not been performed in any previous study. Thus, our study enabled further assessment of changes in pulp chamber dimensions that occur by aging. All variables measured in buccolingual direction (A2, B2, and C2) and one of the variables measured in mesiodistal dimension (B1) showed a significant association with age. This indicates that secondary dentin deposition does not occur uniformly on all the pulp cavity walls and may even vary depending on the type of tooth. Jeon et al., in 2015, evaluated the longitudinal ratios in mandibular first molars and concluded that the pulp chamber/crown height ratio had a greater correlation with the estimated age (Jeon et al. 2015). Mathew et al., in their study in 2016, showed that the ratio of pulp chamber to root height in the mandibular first molars had a stronger negative correlation with age (Mathew et al., 2013).
In our study, the regression model included significant variables namely the root of the MSE of prediction of 5.89 years and the MAE of 4.46 years. Cameriere et al. reported the MAE to be 4.34 to 6.02 years (Cameriere et al., 2012). They indicated that the pulp to tooth ratio was a beneficial variable for age estimation with acceptable accuracy. Jagannathan et al. in India reported the MAE of 8.54 years, which was significantly lower than the error in the Belgian formula (Jagannathan et al. 2011). The MAE of the model in the study by Jeon et al. was found to be 6.07–6.58 years. This value was 6.96 years in the study by Mathew et al. (Jeon et al. 2015; Mathew et al. 2013). The standard error of estimate was 3.0186 years in the study by Juneja et al., 0.6 years in the study by Saxena, 5.35 years in the study by Cameriere et al., 2.28–3.05 years in the study by Yang et al., 1.2–5.08 years in the study by Zaher et al., and 4.10–5.66 years in the study by Afify et al. (Juneja et al., 2014; Saxena 2011; Cameriere et al. 2012; Yang et al., 2006; Zaher et al. 2011; Afify et al. 2014). These values indicate that population-specific formula should be employed for age estimation in different communities. Also, the obtained regression equation may vary depending on the geographical location, race, type of tooth, and the significant variables. Babshet et al. indicated that the Italian formula was not suitable for the Indian population (Babshet et al. 2010).
In our study, except for the age group of 30 to 40 years, a significant difference existed between the actual age and predicted age in other age groups. In the age groups of younger than 20 years, 20 to 30 years and 30 to 40 years, the mean estimated values were higher than the actual values. In fact, estimations made by the regression model for different age groups were averagely higher than the actual age. For the age groups of 40 to 50 years and 50 to 60 years, the mean of predicted values was lower than the actual values. The regression model suggested by Babshet et al. overestimated the values for adolescents and underestimated the values for the elderly (Babshet et al. 2010). It should be mentioned that although the difference between the actual and estimated age in many age groups was statistically significant, this difference in the worst situation was 5 years for the oldest age group. This finding was in line with that of studies by Cameriere et al., Bosmans et al., and Saxena et al. In the study by Juneja et al., no significant difference was found between the actual and estimated age, which was in line with the results of Singaraju et al. and Mathew et al., which was the same for the three age groups (Singaraju and Sharada, 2009; Mathew et al. 2013).
Most studies using CBCT for age estimation measured the pulp volume. However, the CBCT software we used did not allow for volumetric measurement; thus, we only measured the pulp surface area and the buccolingual and mesiodistal dimensions of the pulp.
Last but not least, it should be mentioned that age estimation by measurement of dental pulp dimensions has some limitations. This method cannot be used for multi-rooted teeth because accurate measurements in such teeth are very difficult. On the other hand, it should be noted that the results of a study on a specific population cannot be generalized to other communities. Therefore, similar studies should be performed on a larger sample size to assess the effect of influential factors other than age and gender.