Tooth Coronal Index: A Novel Tool For Age Estimation on Cone-Beam Computed Tomography

ABSTRACT

Objective:

To evaluate dental age assessment reliability through Tooth Coronal Index (TCI) method.

Material and Methods:

The cone-beam computed tomography (CBCT) scans of 160 individuals aged between 20-70 years were analyzed in the present study. The height of the crown, i.e., coronal height, and the height of the coronal pulp cavity, i.e., coronal pulp cavity height, of mandibular second premolars and first molars were calculated and then TCI was measured. The actual age of a subject was compared with TCI of tooth and the acquired data were subjected to Pearson’s correlation and unpaired t-tests.

Results:

Negative correlation was observed between the real age and TCI of mandibular first molar (r = -0.094, p=0.382) and second premolar (r = -0.176, p=0.0961. Statistically significant difference was observed between actual age and TCI for mandibular second premolar and first molar (p<0.001).

Conclusion:

Tooth coronal index has the potential to estimate age of an individual on CBCT scans. It is simple, cost-effective than histological methods and can be applied to both living and unknown dead.

Keywords:
Diagnostic Imaging; Cone-Beam Computed Tomography; Age Determination by Skeleton

Introduction

Assessment of an individual's age in forensic odontology is a significant aspect of biological identification. In recent times, skeletal and dental age estimation has become progressively significant in legal cases for determining an individual's age. Age estimation of an individual is a somewhat difficult task, which needs an interdisciplinary methodology [¹]. The selection of methods to be employed in age estimation depends on the materials available for examination, their condition, and the individual's age category [²]. Even though skeletal methods could be used to estimate the age of an individual, changes in bone maturation are regulated by various environmental factors. Tooth development shows minor changes than other developmental features and shows minimal discretion corresponding to chronological age [³]. Also, dental tissues are more impervious to various environmental stimuli and are minimally influenced by endocrinal disorders or nutritional deficiency state than other body tissues. In this manner, teeth form an exclusive and appropriate parameter for dental age assessment [⁴]. According to the age group to which the individual belongs, different methods of age estimation can be used. In this way, dental development could be used in age estimation of younger persons [²,⁵].

"Secondary dentin" is the calcified nontubular substance deposited by the pulp on the pulp chamber walls and root canal and continues throughout life. Continuous deposition of secondary dentin on the primary dentin's pulpal surface leads to narrowing the pulpal cavity with increasing age. The secondary dentin is deposited all over the pulpal cavity uniformly, i.e., in the molars, it is higher over the roof and floor,, leading to a decrease in height comparison to the width of the pulpal cavity [⁴].

In younger individuals, age estimation from teeth is uncomplicated and precise and is based primarily on stages of tooth formation and its eruption. In older population, numerous approaches have been proposed for age estimation from dental tissue and tooth morphology [⁶]. Most common and popular among these are radiologic and morphologic methods. Various morphologic methods include clinical, histological, and biochemical assessment. Radiographic approaches are simple and require a relatively less time and expertise than morphologic approaches [⁴].

Previous studies in the literature used cuspids, bicuspids using intraoral periapical and panoramic radiographs to assess dental age as these teeth have a well recognizable outline of pulp cavity chamber [⁴,⁷-¹¹]. Studies using lower first molar for dental age estimation have also been reported in the literature [¹²-¹⁴] and limited data is available regarding studies performed on lower second molars for dental age estimation [¹²,¹⁵]. This study was carried out to evaluate reliability of dental age assessment through tooth coronal index (TCI) on cone-beam computed tomography (CBCT) images in mandibular second premolar and mandibular first molars.

Material and Methods

Participants

One hundred sixty CBCT scans were selected for the study from the archives of Radiology Department based on the inclusion and exclusion criteria. The CBCT scans of individuals aged between 20-70 years were assessed for the following criteria: 1) Should be of ideal quality (no artefacts); and 2) Should present ideal image and ideal morphology (no developmental anomalies) of mandibular second premolar and mandibular first molar.

The following exclusion criteria have been adopted: Scans with grossly carious teeth or with periapical pathologies, prosthesis, restorations, severely attrited, rotated or fractured teeth and teeth with any developmental anomalies and teeth with gross evidence of hypercementosis were excluded.

CBCT Measurements

All the CBCT scans were taken for various needs of the patients. The CBCT unit used in this study was Scanora 3D (Soredex, Tuusula, Finland) with 6 mA and 89 kVp and the evaluation of the scans were carried out by two maxillofacial radiologists with the dedicated software (NewTom 3G: NT, QR SRL; Scanora 3D: OnDemand^®, Cypermed Inc., Irvine, CA, USA).

Measurement of TCI

On the saggital section of the scan, a straight line (cervical line) was traced from the cementoenamel junction, which is the division between anatomical crown and root. Coronal height (CH) was calculated vertically from the cervical line to the tip of the highest cusp (Figures 1 and 2) [¹⁶]. Coronal pulp cavity height (CPCH) was calculated vertically from the cervical line to the tip of the highest pulp horn (Figures 1 and 2) [¹⁷]. The measurements provided the TCI of each tooth, which was then calculated as follows: TCI = CPCH × 100/CH. The mean estimated age by TCI was correlated with the subject's real age.

Figure 1
Saggital section of CBCT with measurements on left mandibular first 147x143 mm (150 x 150 DPI).

Figure 2
Pearson correlation test showing a correlation between actual age and TCI of mandibular second premolar 171x142 mm (150 x 150 DPI).

Statistical Analysis

Statistical analysis was carried out using Statistical Package for the Social Sciences, Version 21.0 (SPSS Inc., Chicago, IL, USA). Pearson’s correlation coefficient was applied between the actual age and TCI of lower second premolar and first molar. Unpaired t-test was applied to compare the difference between the actual age and TCI for both lower first molar and second premolar. A p-value of ≤ 0.05 was considered statistically significant. Twenty percent of the CBCT scan were randomly selected and reevaluated after 14 days of interval. The intra-class correlation coefficient (ICC) was used to test the error.

Results

The average ICC value of all the variables was 0.931, which reveals excellent reliability of the measurements. CBCT images of 160 individuals were assessed, and by using TCI, a negative correlation was noted between the actual age and TCI of mandibular first molar (r = -0.094, p=0.0384) (Table 1) and second premolar (r = -0.176, p=0.091) (Table 2).

Table 1
Pearson correlation test showing a correlation between actual age and TCI of mandibular first molar.

Variables		Original Age	TCI Mandibular First Molar
Actual Age	Pearson Correlation	1	-0.094
	Sig. (two-tailed)		0.0382
	N	160	160
TCI Mandibular First Molar	Pearson Correlation	-0.094	1
	Sig. (two-tailed)	0.382
	N	160	160

Table 2
Pearson correlation test showing a correlation between actual age and TCI of mandibular second premolar.

Variables		Original Age	TCI Mandibular First Molar
Actual Age	Pearson Correlation	1	-0.176
	Sig. (two‑tailed)		0.091
	N	160	160
TCI Mandibular First Molar	Pearson Correlation	-0.176	1
	Sig. (two‑tailed)	0.091
	N	160	160

By applying unpaired t-test, a significant difference was noted between the mean actual age (36.5 ± 11.13 years) and TCI (35.3 ± 9.12 years) for mandibular first molar with a (p<0.001) (Table 3).

Table 3
Comparison between mean actual age and TCI of mandibular second premolar.

Variables	N	Mean (SD)	Std. Error Mean	t-value	p-value
Actual Age	160	36.5 ± 11.13	1.2615	31.562	0.001
TCI Mandibular First Molar	160	35.3 ± 9.12	0.9432	39.346

Similarly, for mandibular second premolar, the difference between TCI (36.1 ± 8.54 years) and mean actual age (37.2 ± 9.38 years) was significant (p<0.001) (Table 4).

Table 4
Comparison between mean actual age and TCI of mandibular first molar.

Variables	N	Mean (SD)	Std. Error Mean	t-value	p-value
Actual Age	160	36.1 ± 8.54	0.9654	25.573	<0.001
TCI Mandibular Second Premolar	160	37.2 ± 9.38	0.8124	36.217

Discussion

Age alludes to a time of human life, estimated by years, from birth, and is generally set apart by a specific mental or physical development phase and includes lawful responsibility and capacity. The human body grows and matures with age, particularly in youngsters and teenagers. In this way, the fundamental thought behind the different strategies for age assessment is to compare and contrast the measurements of physical development of the body with age. In any case, because of individual varieties in skeletal and dental maturity, the inference of any modality is subject to ambiguity when applied to a solitary person.

There are also issues concerning the available, accessible reference populations [¹⁸]. Be that as it may, there will always be biological deviations and ambiguity related to age estimation methods. The indelible research objectives are to evolve, corroborate, and expedite the utilization of the most precise techniques for age assessment.

Several studies have implied that the size of dental pulp reduces with advancing age because secondary dentin deposition, along these lines making secondary dentin deposition as the perfect modality to assess the age even past 25 years [⁴,¹²]. Previous studies used digital panoramic radiographs to assess age [⁴,¹¹,¹²,¹⁴], but the panoramic images are subjected to magnification, unsharpness and distortion [¹⁴,¹⁹], so we used CBCT in the present study.

Paewinsky et al. [¹⁶] estimated the size of pulp chamber of six types of teeth on digital panoramic radiographs of subjects in the age group of 14-81 years and observed a significant correlation between reduced size of pulp chamber with age with r² higher for upper lateral incisors. Talabani et al. [¹⁴] calculated TCI of 96 lower first molars on digital panoramic radiographs and noted a strong negative correlation between TCI and age (r² = 0.49, p<0.001).

The use of secondary dentin as an age estimation was introduced by Ikeda et al. [²⁰]. In the study by Koranne et al. [²¹], the correlation coefficient “r” was −0.865 (for premolar combined sample) and -0.850 (for molar combined sample). The observations of the present study were in accordance with previous studies in the literature, which suggested a negative correlation between actual age and TCI for both lower premolars and molars (p<0.001), thus confirming that the height of pulpal cavity reduces with increasing age [⁴,¹¹,¹⁴,²²-²⁶]. Talabani et al. [¹⁴] noted a strong negative correlation (r² = 0.49) between age and TCI regarding the lower first molar. Analogous results were found in the studies by Igbigbi and Nyirenda [²⁴] (r ranged from -0.650 to -0.799) for premolars and molars and Veera et al. [⁴] observed decreasing TCI values with increasing age.

In this study, lower premolars and molars are primarily considered to estimate TCI as a measure of pulpal cavity is precisely observed in these teeth, which was also justified in the previous studies [¹¹,²²]. We observed a highly negative correlation for lower second premolar (-0.176) than first molar (r = -0.0094), which suggests that lower second premolar can be used to estimate dental age more precisely. A statistically significant difference between actual age and TCI of lower second premolar and first molar assert TCI as a reliable indicator of age. This was similar to previous studies [¹¹,¹⁴]. In the present study, a much lower correlation coefficient than studies on two-dimensional radiographs like periapical or panoramic radiographs, this discrepancy may be seen due to limited sample size, but the values are comparable with a similar CBCT study.

Conclusion

This study's observations confirm that TCI is a reliable marker of dental age. TCI in CBCT showed a negative correlation with age, i.e., when age increased, the TCI values decreased. Future studies on diverse populations among different races and in different geographical locations may be carried out, taking into account various environmental, dietary, genetic, and cultural factors.

• Financial Support
  None.
• Data Availability
  The data used to support the findings of this study can be made available upon request to the corresponding author.

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Edited by

Academic Editor: Catarina Ribeiro Barros de Alencar

Publication Dates

• Publication in this collection
  02 Apr 2021
• Date of issue
  2021

History

• Received
  01 Oct 2020
• Reviewed
  09 Nov 2020
• Accepted
  19 Nov 2020