Abstract
Background:
Age estimation is integral to science of forensic odontology and plays an important role in human identification. Pulp volume estimation using cone-beam computed tomography (CBCT) to derive age can be very useful as it is noninvasive and can be applied on individuals of all ages.
Aims and Objectives:
The study aimed to estimate the chronological age-based pulp and tooth volume (PTV) ratios in adults from Uttar Pradesh, India, using CBCT and voxel counting dental software.
Materials and Methods:
Thirty-six CBCT scans were allocated into three Groups, I, II, and III (12 in each group) randomly to study the pulp volume of lateral incisor, canine, and first premolar, respectively. PTV was calculated by image segmentation method using Xelis Dental software. A correlation between chronological age with PTV was established using derived regression equations.
Statistical Analysis:
All the data were subjected to statistical analysis using Statistical Package for Social Sciences version 16.0.
Results:
Estimated age and standard error were determined. Standard errors of estimates were 11.24 years (LI), 7.78 years (C), 9.89 years (PM) group, lowest being for canines. The estimated age was compared with the chronological age. The difference between the chronological age and the estimated age by the derived equation for the present study was statistically nonsignificant (P = 1.00).
Conclusions:
The results of the study show the feasibility of calculation of PTV ratios on CBCT to estimate the age for the set population with canine as the best predictor of age for the present study population.
Keywords: Cone-beam computed tomography, dental age estimation, Indian adults, pulp and tooth volume ratio, volumetric analysis
Introduction
Age estimation as a subdiscipline of the forensic sciences forms an important facet of medicolegal scenarios which includes identification of both the living and the deceased and can be divided into morphological, biochemical, and radiological methods.[1-3]
Dental age estimation by measuring pulp volume is valuable as the size of dental pulp cavity decreases secondary to deposition of secondary dentin and thus it can be correlated with age and can be used even in cases beyond 25 years of age.[4]
Age estimation based on measurement of the pulp area on conventional dental radiographs is a validated method.[5] The accuracy of measurements of regression in pulp area on two-dimensional (2D) imaging, may be affected by inherent limitations such as magnification, distortion, superimposition, misrepresentation of structures, and also by structural variations due to the position, morphology, angulations of tooth, and nonuniform apposition of secondary dentin throughout the pulp chamber. Hence, measurement of the regression in the pulp volume using three-dimensional (3D) imaging may provide accurate estimates of dental age.
An study on Indian population done on mandibular canines yielded a mean error of 8.54 years in estimating the chronological age, but they had certain drawbacks such as it was an in vitro study, had a single tooth as predictor, and had inherent ethnic variation in the study sample which was used for dental age estimation.[6] As the age-related changes in teeth are unique for any given population and ethnicity, regression equations need to be derived for every population.
Thus, this study was designed with an aim to establish the chronological age by calculating the pulp and tooth volume (PTV) ratios of mandibular monoradicular teeth from cone-beam computed tomography (CBCT) scans of the set population.
Materials and Methods
The CBCT-based cross-sectional study was conducted at I.T.S Dental College, Muradnagar, Uttar Pradesh, India. The reproducibility and accuracy of the method was evaluated in the pilot study done on six extracted mandibular monoradicular teeth as described by Yang et al.[4,7] The actual tooth and pulp volumes of these teeth were determined and compared with those determined using CBCT [Figure 1].
Figure 1.
Stages of Pilot study, (a) endodontically prepared extracted tooth with, (b) cone-beam computed tomography image of the endodontically filled tooth, showing pulp volume marked with different colors, (c) image representation postsegmentation process using Xelis Dental s/w enabled calculation of ROI histogram for radiographic volume assessment of the pulp cavity, and (d) tooth decalcification in 30% HCl and postdecalcification remnant silicone core for the actual volume measurement
A total of 36 CBCT scans of subjects visiting the outpatient department requiring CBCT of the mandible for various reasons were included after considering the inclusion and exclusion criteria in the study. The study sample was allocated into three Groups, I, II, and III, with 12 scans in each group through a computer-generated sequence using Trek’s random number generator software. Scans in Group I were analyzed for mandibular lateral incisor, in Group II for mandibular canine, and in Group III for mandibular first premolar. The sample size for the present size was calculated based on the data obtained from a pilot study conducted on six teeth who were not included in the main study. The effect size was estimated to be 0.25 and the sample size was determined using 95% confidence interval and 80% power of the study. The sample size came to be 34 which was rounded off to 36 for equal distribution in three groups.
The inclusion criteria were: (a) subjects with intact and fully developed teeth, i.e., mandibular lateral incisor, mandibular canine, and mandibular first premolar, either on the right or left side of the lower jaw, and (b) teeth free from any morphological abnormalities and completely erupted clinical crowns in the oral cavity. Exclusion criteria were: (a) teeth with restorations, prosthetic rehabilitation, caries, attrition, abrasion, erosion, periapical pathology, root resorption, and developmental anomalies; (b) subjects with any systemic disorders; (c) subjects on any medications/drugs for illness/radiation that can transiently alter/affect the development of teeth; and (d) pregnant or nursing women.
Ethical clearance for the study was obtained from the institutional ethical committee under the protocol number ITSCDSR/IIEC/RP/2018/023 dated October 24, 2018. Written Informed consent was obtained from each participant as per the principles laid down by the Helsinki Declaration. Chronological age of all subjects was supported by a valid document.
The CBCT images were obtained using CBCT Unit – CS9300-C 3D (Carestream Health, Inc. Rochester, NY) in the high-resolution dental mode (90 microns) at 84 kV, 5mA, and 20 s.
Study images were reconstructed from the volumetric dataset using Xelis Dental software (Infinitt Inc., Seoul, Korea) and were reoriented along the tooth long axis, i.e., (True and oblique axial, coronal, and sagittal). Cross-sectional images with a thickness of 1.0 mm at an interval of 1.0 mm were also prepared. Image assessment was performed by an oral radiologist trained for volume estimation using the CBCT and Xelis software.
Tooth segmentation was done by creating a mask and selecting an optimal separating grayscale showing the tooth root in bone. The mask was cropped in all three axes to limit it to the closest region of the chosen tooth, and a 3D image was obtained after selectively removing the regions not belonging to the tooth. Then, sequential slice by slice manual erases and correcting draws were performed to remove the cortical bone along the tooth root length and also along the adjoining teeth at the level of the crown. This separation was not possible by selecting a specific threshold value because there is too small, separable gray value difference between the involved structures. On this created mask with all adapted slices, tooth volume was obtained by the software. Finally, the “Merge” tool was selected to display the volume of the segmented tooth [Figure 2].
Figure 2.
Post Segmentation Tooth Volume
Pulp volume was calculated using the segmentation tool by selecting multiple Region of Interest’s (ROIs) on selected sequential slices within the pulp cavity.[4] Then the “Grow” tool was used to segment the pulp cavity from the rest of tooth structure, which was saved as a new object rendering a different color. Total volume of the segmented pulp was obtained using “Merge” tool [Figure 3].
Figure 3.
Post Segmentation Pulp Volume
ROI histogram was evaluated using the object analysis tool for assessment of tooth and pulp cavity volume.[4] Then in each group, the PTV ratios were calculated for individual teeth [Figures 4 and 5].
Figure 4.
Post Segmentation Tooth Volume Histogram Analysis
Figure 5.
Post Segmentation Pulp Volume Histogram Analysis
The measurements were performed by the oral radiologist at two different times to eliminate the intraobserver bias. The findings were subjected to statistical analysis using the Statistical Package for Social Sciences version 16.0 (SPSS for Windows, Chicago: SPSS Inc; 2007).
A correlation between chronological age with PTV ratio as the predictor of age was thus established for all the three teeth separately. Regression equations were derived for all study groups, for combination of groups, and for the whole sample, with age as a dependent variable, and the pulp–tooth ratio as a predictor.
The PTV ratio values for the present study were used to estimate the dental age using the regression equation given by the Belgian study by Yang et al.[7] and Indian study by Jagannathan et al.[6] and the mean difference was calculated and statistical significance was determined.
Results
The age of the 36 study participants ranged from 17 to 55 years (mean of 30.42 years). Of 36 subjects, 19 were males (mean age = 28.47 years) and 17 were females (mean age = 32.59 years). In each subject, a single mandibular tooth was analyzed either of the left or the right side.
The difference between mean PTV ratios calculated for males, females, and total sample (P = 0.113), between three tooth types on either side for right and left mandibular quadrant, respectively, and between right mandibular quadrant and left mandibular quadrant were not statistically significant (P = 0.868, P = 0.496) [Tables 1 and 2].
Table 1.
Mean pulp and tooth volume ratios in male and females among study subjects
| Sex | Mean±SD | P |
|---|---|---|
| Male | 0.059±0.012 | 0.113 |
| Female | 0.052±0.013 | |
| Total sample | 0.0554±0.0126 |
SD: Standard deviation
Table 2.
Mean pulp and tooth volume ratios within left and right mandibular quadrants
| Quadrant | Tooth | Mean±SD | P |
|---|---|---|---|
| Right lower | Lateral incisor | 0.054±0.013 | 0.868 |
| Canine | 0.055±0.015 | ||
| Premolar | 0.058±0.008 | ||
| Left lower | Lateral incisor | 0.059±0.017 | 0.496 |
| Canine | 0.049±0.015 | ||
| Premolar | 0.058±0.010 |
SD: Standard deviation
A negative correlation was found between PTV ratio and age for all the teeth (R) in the three Groups I, II, and III and combination of groups and the strongest negative correlation was found with Group II (canines) [Table 3 and Graph 1].
Table 3.
Correlation between chronological age and ratio for all teeth, the three groups and combination of Groups (R)
| All teeth | LI | C | 1 PM | LI+C | LI+1 PM | C+1 PM | |
|---|---|---|---|---|---|---|---|
| PTV ratio | −0.241 | −0.259 | −0.362 | −0.299 | −0.242 | −0.274 | −0.249 |
LI: Lateral incisor, C: Canine, I PM: 1st premolar, PTV: Pulp and tooth volume
Graph 1.
Graph showing the relation between age and pulp–tooth volume ratio for whole study sample. The PTV ratio had a negative correlation with age, R (Pearson’s correlation coefficient) was −0.188 for males and −0.208 for females
The PTV ratio values of the present study were used to estimate the dental age by the regression equation given by Yang et al.[7] and Jagannathan et al.[6] The mean age is estimated by the regression equation given by Yang et al.[7] significantly underestimated the chronological age by 6.8 years for the present population. (P = 0.00) and by the regression equation given by Jagannathan et al.[6] overestimated the chronological age by 3.8 years for the present population (P = 0.00) [Table 4].
Table 4.
Difference between estimated age in years with formula given by Yang et al., Jagannathan et al., and present study
| Estimated age | Mean±SD | Mean difference | P |
|---|---|---|---|
| By present study | 30.417±2.410 | ||
| Yang et al. | 23.5694±6.91558 | 6.84784 | 0.000 |
| Jagannathan et al. | 34.284±5.215 | -3.86700 | 0.000 |
SD: Standard deviation
From the regression analysis, it was observed that the coefficient of determination R2 is highest (0.131) for canine group among the studied teeth, when PTV ratio is considered the predictor. This was followed by premolar group (R2 = 0.090), lateral incisor (R2 = 0.067), respectively, in decreasing order of predictability. The coefficient of determination R2 when calculated for males and females was 0.188 and 0.208, respectively, but the difference between the two was not statistically significant (P = 0.08) [Table 5].
Table 5.
Regression analysis with coefficient of determination (R2) for each study group, combination of groups and all groups taken together
| Teeth | Equation | R 2 | SEE (years) |
|---|---|---|---|
| LI | Age: 44.63+(−204.63) × ratio | 0.067 | 11.24 |
| C | Age: 37.51+(−195.59) × ratio | 0.131 | 7.78 |
| I PM | Age: 51.763+(−361.29) × ratio | 0.090 | 9.80 |
| LI+C | Age: 39.39+(−169.24) × ratio | 0.059 | 9.83 |
| C+I PM | Age: 39.29+(−185.70) × ratio | 0.062 | 8.83 |
| LI+I PM | Age: 46.32+(−251.33) × ratio | 0.075 | 10.13 |
| Males | Age: 38.313+(−167.862) × ratio | 0.188 | 10.61 |
| Females | Age: 39.924+(−141.106) × ratio | 0.208 | 8.684 |
| All teeth | Age: 40.85+(−188.027) × ratio | 0.058 | 9.59 |
LI: Lateral incisor, C: Canine, I PM: 1st premolar, SEE: Standard error of estimation
Estimated age was calculated using the linear regression equations, and the standard error of the calculated ages was obtained. Standard error of estimation (SEE) was least for the canines, followed by Groups C+1PM and LI+C+1PM [Table 5].
The estimated age was compared with the chronological age of the subject using Student’s t-test. The difference between the chronological age and the estimated age by the derived equation for the present study was statistically nonsignificant (P = 1.00) [Table 6].
Table 6.
The comparison of chronological mean age with mean of estimated age for all study groups, combination of groups and all teeth taken together in years
| Mean±SD | P | |||
|---|---|---|---|---|
|
| ||||
| Chronological age | Estimated age | Residuals | ||
| All teeth | 30.42±9.74 | 30.42±2.346 | 0.000±9.45 | 1.000 |
| Lateral | 33.16±11.09 | 33.16±2.869 | 0.000±10.72 | 1.000 |
| Canine | 27.25±7.95 | 27.25±2.876 | 0.000±7.42 | 1.000 |
| Premolar | 30.83±9.79 | 30.83±2.933 | 0.000±9.35 | 1.000 |
| LI+C | 30.20±9.91 | 30.20±2.398 | 0.000±9.61 | 1.000 |
| C+1 PM | 29.04±8.91 | 29.04±2.219 | 0.000±8.63 | 1.000 |
| LI+1 PM | 32.00±10.30 | 32.00±2.826 | 0.000±9.91 | 1.000 |
| Males | 28.47±10.59 | 28.47±1.198 | 0.000±10.313 | 1.000 |
| Females | 32.59±8.6 | 32.59±1.786 | 0.000±8.408 | 1.000 |
LI: Lateral incisor, C: Canine, I PM: 1st premolar, SD: Standard deviation
Intraobserver variability was checked by applying the Cronbach’s alpha (0.982) test for reliability, and interclass coefficient correlation was also determined. Intraclass coefficient correlation was also determined, which revealed that the agreement between the observed values was 98.1%.
Discussion
Over the period, dental age estimation has gained popularity and acceptance due to lesser variability in comparison to skeletal and sexual maturity indicators. Since the regression changes in the pulp are not uniform throughout and the conventional methods have their inherent errors, 3D scans of teeth generated by CBCT, allow for the calculation of the volume of each tooth and corresponding pulp chamber.[8]
In this study, one tooth was selected for analysis for each subject because taking multiple tooth samples per subject into account was not possible within a regression model for age. In fact, each repeated pulp–tooth volume ratio measurement would function as another predictor which was not feasible because the number of repeated measurements differed between the subjects.
A pilot study was done to evaluate the accuracy of the developed method as described by Yang et al.[7] The actual tooth volume (TV1), tooth volume by CBCT (TV2), actual pulp volume (PV1), pulp volume by CBCT (PV2), actual pulp–tooth ratio (R1), and pulp–tooth ratio by CBCT (R2) were calculated. The results showed a percentage error of 8.84% for TV1 and TV2, 2.6% for PV1 and PV2, and 12.7% for R1 and R2, respectively, and were in accordance with the results given by Yang et al.,[7] who obtained a percentage error of ±7.8%. The estimated error was quite less than that reported by Star et al.[8] who reported the maximum percentage error to be 21% and 16% for PTVs, respectively.
In this study, only monoradicular mandibular teeth were selected as they have a low morphological diversity among all teeth. The multirooted teeth pose many problems during the segmentation process due to the complex root anatomy which makes separation difficult as there is too small or no grayscale difference between the involved structures.[7] Also, the pulp anatomy of multirooted teeth is complex due to small, fine, and bifurcated canals and which makes the calculation of pulp volume difficult and less precise.
The Cronbach’s alpha was acceptable statistically, and the intraobserver variability revealed 98.1% agreement between the observed values.
The PTV ratio was chosen as an age predictor to minimize the variability in tooth sizes and to eliminate any possible dimensional changes due to CBCT acquisition, the volume calculations, and the segmentation process. The pulp volume was used as the numerator in the PTV ratio to avoid a zero value in denominator measured in obliterated or calcified pulp chambers.
Star et al.[8] reported the mean PTV to be 0.027 ± 0.020 which is less in comparison to our study. The reason could be a difference in ethnicity and also a higher mean age in the subjects taken up for study by them which correlates with a decrease in pulp volume and thus a smaller mean PTV ratio for their sample.
The R-value for the total sample was −0.241 and was found to be highest for the canine group (−0.362). The R-value was comparatively weak in our study as compared to the studies by Star et al.,[8] Yang et al.,[7] Jagannathan et al.,[6] and Adisen et al.,[9] which might be due to a small sample size in the present study.
The strongest correlation between age and pulp–tooth volume ratio was found with canines, unlike the mandibular lateral incisors as reported by Kvaal et al.,[5] and Star et al.[8] This could be explained by the fact that all study groups consisted of equal number of teeth in the present study which was not true for other studies. Also, these studies calculated the pulp area on the 2D images which brings into picture horizontal and vertical magnification errors, especially in the teeth considered for the study (position and angulation), while on the contrary, CBCT allows for evaluation of very accurate tooth anatomy and pulp anatomy which may be the reason for the difference in the correlation between the two teeth.
The PTV ratio had a negative correlation with age for both males and females and had a slightly stronger correlation for women, but it was statistically insignificant. Similar results were obtained in the studies conducted by Gulsahi et al.[10] and Adisen et al.[9]
From the results of regression analysis, it was observed that the coefficient of determination R2 was highest for canine which was in correlation with the study conducted by Kazmi et al. (R2 = 0.33).[11]
In studies by Kvaal et al.,[5] and Bosman et al.,[12] the coefficient of determination was strongest for all the six teeth together while Sharma and Srivastava[13] obtained the best value of coefficient of determination with mandibular first premolar (R2 = 0.19). The disparity between R2 calculated on 2D and 3D imaging may be explained as during the segmentation process on 3D images, there are many shortcomings, namely differentiating between tooth and cortical bone at the most apical end, where distinction based on the established grayscale becomes less accurate.
In the present study, the lowest coefficient of determination was observed with mandibular lateral incisor (R2 = 0.067) contrary to Kvaal et al.,[5] who obtained the lowest value with mandibular canine (R2 = 0.56) and Adisen et al.[9] who evaluated maxillary canines and reported a R2 of 0.236 for the whole sample.
In another study by Akay et al.,[14] the highest coefficient of determination was reported in the maxillary second premolar tooth (R2 = 0.550), followed by mandibular teeth model (R2 = 0.471) and the total sample (R2 = 0.296).
Star et al.[8] reported no statistical evidence that the relation between the pulp–tooth volume ratio and age differs between the types of teeth, which was possibly explained by the unequal number of different study teeth in their sample. This was negated in our study by selecting one tooth type per subject and also an equal inclusion of different tooth types in the sample.
Contrary to our results, Gulsahi et al.[10] reported the highest Pearson correlation (0.532) for the maxillary central incisor tooth and lowest value with maxillary canines while Molina et al.[15] reported highest correlation (R2 = 0.366) for the maxillary central incisors. The difference could be due to variability in the anatomical profile of the mandibular and maxillary teeth and the difference in the software employed for volume estimation.
SEE for the age estimated in the present study was lowest with mandibular canine (7.78 years) and highest with mandibular lateral incisor (11.24 years). Contrary results were obtained by Kvaal et al.[5] who concluded that the SEE was least when all six teeth were considered together (SEE = 8.6 years), Bosman et al.[12] who observed best estimates with mandibular first premolar (SEE = 8.1 years), and Asif et al.[16] who reported a mean absolute value of 6.48 years for maxillary right central incisors.
In the present study, canine was the best predictor of age whereas mandibular lateral incisor was the weakest. This could be attributed to the fact that in the present study, there was equal distribution of the study teeth, and also in other studies, pulp area was studied on the 2D images. CBCT allows for evaluation of very accurate tooth anatomy and pulp anatomy which may be the reason for the difference.
There was no significant difference between the actual age and the estimated age in each study group, combination of groups, for males and females, and for all the teeth taken together. The inference is that the age can be estimated by calculating Pulp and Tooth volume ratios utilizing mandibular Lateral Incisors, Canines and First Premolars. Also it can be derived utilizing Pulp and Tooth volume ratios using a combination of teeth ie Lateral Incisor and Canine, Canine and 1st Premolar and Lateral Incisor and 1st Premolar and also when Pulp Tooth ratios are calculated using all teeth together.
Limitations and future prospects
During the segmentation process differentiating between tooth and the cortical bone in the most apical areas and on areas of small tooth and pulp contours, the distinction between tooth parts based on the established grayscale became less accurate. One of the reasons for this problem is the inherent deficiency in the current CBCT technology due to which small structures such as PDL space, voids in root canal fillings are less visible. Also, the contrast when compared to CT is low, thus limiting the accuracy of the segmentation process. Further, this study warrants future studies on a large sample size with adequate representation of samples from different age groups, ethnicities, and sex distribution.
Conclusions
The results of the study show the feasibility of this technique through calculation of PTV ratios on the acquired CBCT images to estimate the age for the set population. It can be concluded that canine is the best predictor of age for the present study population.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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