Reliability of Age Estimation in Modi Nagar Children using Demirjian’s Eight Teeth Method and Indian Specific Formula

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Reliability of Age Estimation in Modi Nagar Children using Demirjian’s Eight Teeth Method and Indian Specific Formula

   

 Rashi Jaiswal1*, Aarti Niveditha Kodirekkala2 and Anushtha Kushwala3

1DJ College of Dental Sciences & Research, Modinagar, Uttar Pradesh, India

2St. Joseph Dental College, Duggirala, Andhra Pradesh, India

3Institute of Dental Sciences, Bareilly, Uttar Pradesh, India

Corresponding author: Rashi Jaiswal, DJ College of Dental Sciences & Research, Modinagar, Uttar Pradesh, India

Citation: Jaiswal R, Kodirekkala AN, Kushwala A. Reliability of age estimation in Modinagar Children using demirjian’s eight teeth method and indian specific formula. Genesis J Surg Med. 3(1):1-15.

Received: February 26, 2024 | Published: March 09, 2024.

Copyright ©️ 2024 genesis pub by Jaiswal R, et al.  CC BY-NC-ND 4.0 DEED. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives 4.0  International License. This allows others distribute, remix, tweak, and build upon the work, even commercially, as long as they credit the authors for the original creation.

Abstract

Forensic odontology, historically underexplored in dentistry, plays a crucial role in medico-legal contexts, with age estimation being a vital sub-discipline. Accurate and user-friendly age estimation is imperative.

Keywords

Forensic; Odontology; OPGs; Age estimation; French maturity score; Radiograph.

Introduction

Anthropologists have extensively examined age systems, where age serves as a pivotal organizing principle encompassing formal age classes, age grades reflecting social and biological development, and relative age distinctions. Notably, the correlation between body development and chronological age is imperfect. Variances in developmental patterns lead to disparities between chronological and biological age. Consequently, parameters like dental age, bone age, mental age, and milestones such as menarche, voice change, height, and weight are utilized as proxy indicators for biological age and body development. Dental development stands out as a particularly reliable indicator, being less susceptible to influences from nutritional and endocrine factors, making it a pertinent measure of biological maturity in children [1].

Forensic odontology, historically underexplored in dentistry, plays a crucial role in medico-legal contexts, with age estimation being a vital sub-discipline. Accurate and user-friendly age estimation is imperative. Presently, many methods are invasive, time-consuming, and reliant on expensive tools and experienced pathologists, lacking in in-vivo applicability. Radiology emerges as a valuable tool, offering non-invasive insights into dental developmental stages, providing baseline data for precise age estimation in children and adolescents [2].

The universally utilized Demirjian method for age estimation, primarily involving seven left mandibular teeth, has demonstrated variations in estimates across different populations, including Indians. The original method excluded the third molar due to congenital absence and developmental variability. Despite this, the third molar remains a crucial predictor for assessing age in the 16–23 age group. Recognizing this, others have assessed this tooth using Demirjian's criteria, aiming to expand the method's applicability up to the age of 18 years [3].

The widely adapted Demirjian method has undergone numerous modifications, notably replacing centile maturity curves with regression formulas and integrating the third molar to enhance the method's scope and duration for age prediction. In this context, Acharya conducted a regression analysis, devising a formula that incorporates the third molar for age estimation within the Indian population [2].

It has been seen that there is wide range of variations in age estimates and thus a new India specific formula has been adapted by modifying the Demirjian’s original formula by 8 teeth instead of 7 teeth method by including third molar given by Acharya, to use it on a wider range of population.

In this study we evaluated the accuracy of age estimation using Demirjian’s 8 teeth method of age estimation combined with Acharya’s India specific formula in Modinagar.

Aim

To evaluate the accuracy of age estimation using Demirjian's eight teeth approach, which incorporates an Indian formula in addition to the French maturity scores.

Objectives

  1. Predicting age estimation accuracy using an India-specific formula.
  2. To calculate the age estimation's reliability following the third molar's incorporation.

Inclusion and Exclusion Criteria

Inclusion criteria

  1. Patients free of obvious developmental anomalies.
  2. Orthopantomograms (OPG) without any distortions.
  3. Radiographs of patients with the either seven or eight teeth in the mandibular left or right side.
  4. Patient between the ages of 7 - 23 years.

Exclusion criteria

1. Radiographs of patients with developmental anomalies

2. Crowding and tooth distortion in cases when the teeth's root structures were not easily visible

3. Diagnosis and treatment of bilaterally absent teeth in the jawbone.

4. Displacement of root due to pathology, such as cyst or tumour.

Methods

Sixty OPGs, collected from 30 males and 30 females who visited the OPD of DJ Dental College, Modinagar were categorized into four groups based on age and sex. Group A comprised males aged 7–16 years, Group B involved males aged 16.1–23 years, Group C included females aged 7–16 years, and Group D consisted of females aged 16.1–23 years. The division by sex aimed to account for gender-specific tooth development rates. Each sex was further divided into subgroups to evaluate the reliability of the third molar for age estimation after 16 years, as it remains the only tooth still developing under normal conditions at this stage. Digital OPG images, acquired in JPEG format from a KODAK 8000 digital panoramic unit, were analyzed using a scoring criterion, yielding the total maturation score (S).

French maturity scores

The OPGs would be interpreted according to the French Maturity Scores given by A Demirjian,

H. Goldstein, and M. Tanner in the year 1973 and each tooth is graded accordingly.

Dental Developmental Stages.

  1. Tooth not yet calcified.
  2. Crypt Stage: Bone crypts are visible without dental germ inside it.
  3. In both uniradicular and multiradicular teeth, a beginning of calcification is seen at the superior level of the crypt in the form of an inverted cone or cones. There is no fusion of these calcified points.
  4. Fusion of the calcified points forms one or several cusps which unite to give a regularly outlined occlusal surface

5a.  Enamel formation is complete at the occlusal surface. It can be seen extending and converging     towards the cervical area

5b.    The beginning of the dentinal deposit is seen.

5c.    At the occlusal boundary, the pulp chamber's contour curvatures.

6a.    Up to the cementoenamel junction, the crown formation is finished.

6b.  In uniradicular teeth, the pulp chamber's superior border is clearly curved and concave in the   direction of the cervical area. If pulp horns are present, their protrusion creates an outline resembling the top of an umbrella. The pulp chamber of molars is trapezoidal in shape.

7.     uniradicular teeth

a.     The wall of the pulp chamber now forms straight lines, horn, which is larger than the previous stage

b.     The crown height is greater than the length of the roots.

Molars

  1. The calcified origin of the bifurcation has developed further down from its semi-lunar
  2. The length of the root equals or exceeds the crown height.

8. The walls of the root canal are now parallel, and its apical end is still partially open.

9. The root canal's apical end is entirely sealed.

The periodontal membrane has a uniform width around the root and the apex.

Using the scoring system:

  1. The developmental stages for each tooth are then scored according to the Demirjian’s individual maturity score of boys and girls (S).
  2. The scores was summed up (S) and substituted in the Indian specific formulae.

India Specific Formula

  1. Males: Age = 27.4351 – (0.0097 X S2) + (0.000089 X S3)
  2. Females: Age = 23.7288 – (0.0088 X S2) + (0.000085 X S3)
  3. The value so obtained was designated as age estimated.
  4. The chronological ages of the children were obtained by subtracting their birthdates from the date of collecting the radiograph.
  5. The further calculation of result and statistical analysis was carried out using Statistical Package for Social Sciences (SPSS) Statistical Software.

Results

The data thus obtained was compiled systematically; master table was prepared. Inferential statistical analysis has been carried out in the present study. Results on continuous measurements are presented on Mean ±SD and results on categorical measurements are presented in Numbers (%). Total 60 OPGs radiographs were collected from 30 males and 30 female subjects. The panoramic radiographs were divided into following four groups based on the age and sex of the subjects. Group A contains males in the age group of 7–16 years; Group B contains males in the age group of 16.1–23 years, Group C containing females in the age group of 7–16 years and Group D containing females in the age group of 16.1–23 years.

Table 2 shows the correlation between the estimated age and actual age of all four groups showing the p – value of Group A = 0.124, Group B = 0.001, Group C = 0.001, Group D = 0.001 respectively and has an overall p – value of 0.001 that is significant.

Discussion

Age estimation is crucial in medico-legal contexts, especially in civil and criminal litigation. Teeth, known for their durability and resistance to decay, fire, and chemicals, contribute significantly to personal identification and age assessment. In living individuals, dental age estimation relies on non-invasive methods that evaluate the timing and sequence of growth stages in developing dentition, as well as modifications in mature dentition and surrounding tissues [2].

The eruption of teeth is a conspicuous transformation in the dynamic progression from tooth formation to eventual shedding. The timing of tooth eruption remains relatively consistent, making the examination of teeth a widely accepted method for determining an individual's age [3].

Demirjian’s method for age estimation has been proved adequate by some researchers in different populations [4, 12]. However, this method has shown inaccuracies with limitations such as overestimation and underestimation of dental age when compared to Willems, Haavikko and Nolla methods [13, 34].

initially classified tooth development into 8 stages, creating an age estimation method for the French population.4 Modified for various regions, this method was expanded by incorporating the third molar for broader age prediction [4]. Acharya introduced an India-specific formula, derived from a regression analysis using Demirjian's 8 teeth method, for age estimation in the Indian population [3].

This study utilized 60 panoramic radiographs (30 males and 30 females) from the Department of Oral Medicine and Radiology at Divya Jyoti College to assess the reliability of age estimation using Demirjian's 8 teeth method combined with Acharya's India-specific formula in the Modinagar population. Subjects were categorized into four groups: Group A (males, 7-16 years), Group B (males, 16.1-23 years), Group C (females, 7-16 years), and Group D (females, 16.1-23 years) (Table 1).

S. No.

Group

Criteria

No. of samples

1

Group A

Males in the age group of 7–16 years

12

2

Group B

Males in the age group of 16.1–23 years

18

3

Group C

Females in the age group of 7–16 years

17

4

Group D

Females in the age group of 16.1–23years

13

Table 1: Showing Group wise Distribution of Study samples.

In the present study, which comprises of 30 males and 30 females of age 7 to 23 years, mean of all the age have been calculated which was 12.08, 19.27, 13.11, 19.3 for actual age in GROUP A, B, C and D respectively and 13.96, 18.48, 13.14 and 17.99 for estimated age in GROUP A, B, C and D respectively (Table 2-5) then after mean values, correlation between estimated and actual age was calculated (Chart 1).

Group A [Males 7-16 Years]

S. No.

Actual Age

Estimated age

1

15

14.6709

2

15

16.6927

3

12

10.3818

4

9

7.1613

5

15

13.58

6

14

12.4786

7

14

14.6708

8

12

11.2396

9

11

11.2396

10

11

12.4235

11

10

14.8911

12

7

19.7481

Mean

12.08

13.96

 
Table 2: Presenting the Mean of ages in Group A.

Group B (Males 16.1 – 23 Years)

S. No

Actual age

Estimated age

1

16

17.3517

2

18

18.2697

3

16

16.692

4

18

18.2697

5

20

19.4351

6

21

19.4351

7

22

19.4351

8

21

19.5351

9

18

18.2697

10

20

18.2697

11

18

17.3516

12

20

18.549

13

19

19.4351

14

22

19.4351

15

17

16.692

16

20

19.4351

17

21

19.4351

18

20

17.35

Mean

19.27

18.48

Table 3: Presenting the Mean of ages in Group B.

Group C (Females 7 – 23 Years)

S.NO

Actual age

Estimated age

1

15

16.5082

2

15

14.7728

3

15

14.7728

4

11

10.0753

5

13

10.5218

6

15

15.5807

7

18

17.8305

8

10

10.2062

9

15

15.1944

10

15

14.7728

11

11

10.5041

12

11

10.1819

13

12

9.7555

14

14

13.8294

15

10

13.4221

16

10

9.8674

17

13

15.652

Mean

13.11

13.14

Table 4: Presenting the Mean of Ages in Group C.

Group D (Females 16.1-23 Years)

S. No.

Actual age

Estimated age

1

16

11.2096

2

19

17.8305

3

16

14.144

4

20

18.2628

5

21

17.8305

6

18

17.8305

7

18

16.3169

8

23

20.7288

9

18

18.5901

10

18

19.0708

11

21

20.72

12

22

20.7288

13

21

20.7288

 Mean

19.31

17.99

 
Table 5: Presenting the Means of Ages in Group D.

Chart 1: correlation Coefficient Between Estimated age and actual age.

Among the 60 samples, Group A (12 samples) exhibited a correlation coefficient of 0.024 and a non-significant p-value of 0.124, indicating an insignificant relationship between estimated age and actual age. Conversely, Group B (18 samples) demonstrated a significant correlation (coefficient: 0.807, p-value: 0.001), as did Group C (17 samples, coefficient: 0.845, p-value: 0.001) and Group D (13 samples, coefficient: 0.829, p-value: 0.001), signifying a meaningful correlation between estimated and actual age in these groups  (Table 6, Graph 1).

Actual age

 Estimated age

 Correlation Coefficient

 Significance (p-value)

Group A

12.08±2.61

13.26±3.24

0.024

0.124 (non-significant)

Group B

19.27±1.87

18.48±1.02

0.807

0.001 (significant)

Group C

13.11±2.36

13.14±2.75

0.845

0.001 (significant)

Group D

19.30±2.21

17.99±2.81

0.829

0.001 (significant)

Overall

17.19±4.11

16.79±3.54

0.858

0.001 (significant)

Table 6: Correlation Coefficient between Estimated Age and Actual Age.

Graph 1: Correlation between estimated age and actual age.

Tandon et al, on comparing calculated age with estimated age using India specific formula, mean estimated age was found to be significantly higher than calculated age for overall as well as both the genders independently. The difference between the estimated age and calculated age was significant for all age groups except the age group 16-18 years. Hence it was in accordance with the present study [35].

Khorate et al, conducted a study on Goan population and concluded significant correlation between estimated age and actual age, they found Acharya’s India specific formula is limited to an age group of 9-22 years in females which agrees with the criteria of present study [36].

Gandhi et al, found that Indian formula was more reliable for age estimation with only slight underestimation (–0.65 years) in males and overestimation (0.68 years) in females of age group below 10 years. Males and females from 13 to 15 years showed that dental development was almost parallel; thus, this result was in accordance with current study [37].

In this study, mean accuracy error (MAE) was calculated in all the group of age estimation (Table 7). Out of 18 samples the MAE was calculated to be 1.97+2.90 which was statistically very high, Group B containing 32 samples shows a MAE of 1.72+1.11 which was permissible. Hence the result obtained was significant. Group C contains 17 samples with MAE of 0.98+1.06. In Group D, 33 samples were present, and MAE calculated was 1.17+0.97; hence the overall result was calculated to be 1.46+1.57 which was statistically significant (Graph 2).

No. of samples

Male

Group A

12

1.97±2.90

Group B

18

1.72±1.11

Group C

17

0.98±1.06

Group D

13

1.17±0.97

Overall Total

60

1.46±1.57

 
 Table 7: Error of Age Estimation in all the Groups during the Study.
 
 

Graph 2: Error of age estimation in all the groups during the study.

Kumar et al, assessed that the mean absolute error in males (7-16 years) was 1.2 years; in males (16.1-23 years) was 1.3 years; in females (7-16 years) was 0.95 years and in females was 1.16 years. Therefore, the overall result was statistically significant and was in accordance with present study [2].

Khorate et al, conducted a study on Goan population and mean absolute error calculated was -1.88 to +1.45 in case of female samples and that of male samples ranging from -1.55 to +1.29, so they found Acharya’s India specific formula is reliable to an age group of 9-22 which agrees with the criteria of present study [36].

Rath et al, tested the accuracy of modified Demirjian’s method and overall mean absolute error in the four subgroups were compared, the least MAE and therefore most accurate estimation was obtained in Group B at 1.1 years followed by Group D at 1.3 years. Therefore, the results were in favour of present study [37].

In this current study, percentage of subjects with different levels of accuracy in different groups has been calculated (Table 8) the difference obtained was divided in three groups (Table 9) i.e. within + 1 year, within 1.1-2 years & 2 years. In group A we found that 44.4% in +1, 33.3% within + 2 and contains 22.2% in >+ 2. This shows that there is not much correlation between the actual age and the calculated age. The difference obtained in group B was found to be 31.2% in +1, 28.1% within + 2 and contains 40.7% in >+ 2. This showed statistically good correlation between the actual age and the calculated age. The difference obtained in group C was found to be 70.6% in +1, 5.9% within + 2 and contains 23.5% in >+ 2. Hence this showed good correlation between the actual age and the calculated age. The difference in group D was calculated 48.5% in +1, 39.4% within + 2 and contains 12.1% in >+ 2. (Graph 3 and 4).

Level of accuracy

No. of samples

Percentage

 

 

±1

31

31%

 

±2

14

14%

 

More than 2

15

15%

Table 8: Percentage of Subjects with Different Levels of Accuracy in the Age estimation.

Groups

Level of Accuracy

 

±1

±2

More than 2

Group A

6

3

3

-44.40%

-33.33%

-22.22%

 Group B

8

6

4

31.20%

-28.10%

-40.70%

Group C

10

5

3

70.60%

-5.90%

-23.50%

Group D

7

4

2

48.50%

-39.40%

-12.10%

Table 9: Percentage of Subjects with Different Levels of Accuracy in Different Groups.

Graph 3: percentage age of subjects with different levels of accuracy in the age estimation.

Graph 4: Percentage of subjects with different levels of Accuracy in different Groups.

In Kumar, et al, study, the reliability of age estimation using Demirjian's 8 teeth method, and an India-specific formula yielded fairly reliable results, narrowing down the prediction error to just over 1 year. This improvement was noted compared to the original method in the Indian population. The incorporation of the third molar, as observed in our study, also contributed to reducing errors in age estimates [2].

Gandhi, et al, concluded that Demirjian’s formula is less reliable as it gave a considerable difference in age, but Indian standard formula showed high reliability and accuracy, the males and females showed that level of accuracy was significantly high and thus gave a result in positive direction and on the same time in accordance with the current study [38].

Rath, et al. tested the accuracy of Indian standard formula in Orissa population and the result showed that majority of the test patients, i.e. approximately 50% were estimated to be within ±1 year while 26.4% age estimates fell within 1.1–2 years from the actual age. In 23.6% samples, age estimates fell outside the ±2 year range, which agrees with the criteria of present study [37].

Based on the study's findings, we conclude that utilizing Demirjian's age estimation method with a modified Indian standard is suitable for estimating the age of individuals in the Modinagar vicinity. However, its accuracy is lower in males aged 7–16 years compared to females of the same age. This aligns with Gandhi et al.'s observations, indicating that dental maturity occurs earlier in females than in males. Nevertheless, for both males and females in the 16.1–23 age group, the modified Demirjian method proves to be reliable and accurate.

Conclusion

This study, conducted at the Department of Oral Medicine and Radiology in Modinagar, UP, aimed to assess the reliability of age estimation using the modified Demirjian's 8 teeth method and Acharya's India-specific formula. The research involved 60 subjects divided into two age groups (7-16 and 16.1-23 years) with soft copies of OPGs collected from archives. The study found a significant relationship between actual and estimated age (P = 0.001) with an overall permissible error of 1.46±1.57. The method proved reliable for age estimation in Modinagar females (7-23 years) and males (16.1-23 years) but not in males aged 7-16. Limitations include applicability only between ages 7-23 and dependence on sample size and radiograph clarity, warranting further studies for enhanced accuracy and reliability.

References

  1. Priyadarshini C, Puranik MP, Uma SR. Dental Age Estimation Methods: A Review METHODS OF AGE ESTIMATION. Int J Adv Heal Sci @BULLET. 2015;1(12).
  2. Kumar VJ, Gopal Ks. Reliability of age estimation using Demirjian′s 8 teeth method and India specific formula. J Forensic Dent Sci. 2011;3(1):19.
  3. Acharya AB. Age Estimation in Indians Using Demirjian’s 8-teeth Method. J Forensic Sci. 2011;56(1):124-127.
  4. Demirjian A, Goldstein H, Tanner JM. A new system of dental age assessment. Hum Biol. 1973;45(2):211-227.
  5. Nykänen R, Espeland L, Kvaal SI, Krogstad O. Validity of the Demirjian method for dental age estimation when applied to Norwegian children. Acta Odontol Scand. 1998;56(4):238-244.
  6. Olmen VA. Dental age estimation in Belgian children: Demirjian"s technique revisited. J Forensic Sci. 2001;46(4):893-895.
  7. Hegde RJ, Sood PB. Dental maturity as an indicator of chronological age: radiographic evaluation of dental age in 6 to 13 years children of Belgaum using Demirjian methods. J Indian Soc Pedod Prev Dent. 2002;20(4):132-138.
  8. Chaillet N, Nyström ME, Kataja M, Demirjian A. Dental maturity curves in Finnish children: Demirjian’s method revisited and polynomial functions for age estimation. J Forensic Sci. 2004;49(6):1324-1331.
  9. Bagic IC, Sever N, Brkic H, Kern J. Dental Age Estimation in Children Using Orthopantomograms.Acta Stomatol Croat. 2008;42(1):11-18.
  10. Bagherian A, Sadeghi M. Assessment of dental maturity of children aged 3.5 to 13.5 years using the Demirjian method in an Iranian population. J Oral Sci. 2011;53(1):37-42.
  11. Caldas IM, Júlio P, Simões RJ, Matos E, Afonso A, Magalhães T. Chronological age estimation based on third molar development in a Portuguese population. Int J Legal Med. 2011;125(2):235-243.
  12. Abesi F, Haghanifar S, Sajadi P, Valizadeh A, Khafri S. Assessment of dental maturity of children aged 7-15 years using demirjian method in a selected Iranian population. J Dent (Shīrāz, Iran). 2013;14(4):165-169.
  13. Koshy S, Tandon S. Dental age assessment: The applicability of Demirjian’s method in South Indian children. Forensic Sci Int. 1998;94(1-2):73-85.
  14. Willems G. A review of the most commonly used dental age estimation techniques. 2016;(July 2001).
  15. Sarnat H, Kaffe I, Porat J, Amir E. Developmental stages of the third molar in Israeli children.PediatrDent.2003;25(4):373-377.
  16. Chaillet N, Demirjian A. Dental maturity in South France: A comparison between Demirjian’s method and polynomial functions. J Forensic Sci. 2004;49(5):1059-1066.
  17. Arany S, Iino M, Yoshioka N. Radiographic survey of third molar development in relation to chronological age among Japanese juveniles. J Forensic Sci. 2004;49(3):534-538.
  18. Chaillet N, Nyström M, Demirjian A. Comparison of dental maturity in children of different ethnic origins: international maturity curves for clinicians. J Forensic Sci. 2005;50(5):1164-1174.
  19. Rai B, Anand S. Tooth developments: an accuracy of age estimation of radiographic methods. World J Med Sci. 2006;3(1):25-27.
  20. Maber M, Liversidge HM, Hector MP. Accuracy of age estimation of radiographic methods using developing teeth. Forensic Sci Int. 2006;159(1):68-73.
  21. Tunc E Sen, Koyuturk AE. ScienceDirect Forensic Sneoce Dental age assessment using Demirjian’s method on northern Turkish children. Forensic Sci Int. 2008;175:23-26.
  22. Cameriere R, Ferrante L, Liversidge HM, Prieto JL, Brkic H. Accuracy of age estimation in children using radiograph of developing teeth. Forensic Sci Int. 2008;176(2-3):173-177.
  23. Al-Emran S. Dental Age Assessment of 8. 5 to 17 Year-old Saudi Children Using Demirjian ’ s Method. J Contemp Dent Pract. 2008;9(3):64-71.
  24. Phillips VM, Van Wyk Kotze TJ. Testing standard methods of dental age estimation by moorrees, fanning and hunt and demirjian, goldstein and tanner on three south african children samples. J Forensic Odontostomatol. 2009;27(2):20-28.
  25. Cruz-Landeira A, Linares-Argote J, Martínez-Rodríguez M, Rodríguez-Calvo MS, Otero XL, Concheiro L. Dental age estimation in Spanish and Venezuelan children. Comparison of Demirjian and Chaillet’s scores. Int J Legal Med. 2010;124(2):105-112.
  26. Galic I, Nakas E, Prohic S, Selimovic E, Obradovic B, Petrovecki M. Dental age estimation among children aged 5-14 years using the demirjian method in Bosnia-Herzegovina. Acta Stomatol Croat. 2010;44(1):17-25.
  27. Celikoglu M, Cantekin K, Ceylan I. Celikoglu 2011.pdf. J Forensic Sci. 2011;56(S1):S220-S222.
  28. Nik-Hussein NN, Kee KM, Gan P. Validity of Demirjian and Willems methods for dental age estimation for Malaysian children aged 5-15 years old. Forensic Sci Int. 2011;204(1-3).
  29. Jayaraman J, King NM, Roberts GJ, Wong HM. Dental age assessment: Are Demirjian’s standards appropriate for southern Chinese children? J Forensic Odontostomatol. 2011;29(2):22-28.
  30. Lee SS, Kim D, Lee S, et al. Validity of Demirjian’s and modified Demirjian’s methods in age estimation for Korean juveniles and adolescents. Forensic Sci Int. 2011;211(1-3):41-46.
  31. Baghdadi ZD, Pani SC. Accuracy of population specific Demirjian curves in the estimation of dental age of Saudi children. Int J Paediatr Dent. 2012;22(2):125-131.
  32. Galić I, Vodanović M, Janković S, et al. Dental age estimation on Bosnian-Herzegovinian children aged 6-14 years: Evaluation of Chaillet’s international maturity standards. J Forensic Leg Med. 2013;20(1):40-45.
  33. Nur B, Kusgoz A, Bayram M, et al. Validity of demirjian and nolla methods for dental age estimation for Northeastern Turkish children aged 5-16 years old. Med Oral Patol Oral Cir Bucal. 2012;17(5):3-9.
  34. Kırzıoğlu Z, Ceyhan D. Accuracy of different dental age estimation methods on Turkish children. Forensic Sci Int. 2012;216(1-3):61-67.
  35. Tandon A, Agarwal V, Arora V. Reliability of India-specific regression formula for age estimation of population in and around Bahadurgarh, Haryana (India). J Oral Biol Craniofacial Res. 2015;5(3):193-197.
  36. Khorate MM, Dinkar AD, Ahmed J. Accuracy of age estimation methods from orthopantomography in forensic odontology: A comparative study. Forensic Sci Int. 2014;234.
  37. Rath H, Rath R, Mahapatra S, Debta T. Assessment of Demirjian’s 8-teeth technique of age estimation and Indian-specific formulas in an East Indian population: A cross-sectional study. J Forensic Dent Sci 2017;9:45.
  38. Gandhi N, Jain S, Kumar M, Rupakar P, Choyal K, Prajapati S. Reliability of third molar development for age estimation in Gujarati population: A comparative study. J Forensic Dent Sci. 2015; 7(2): 107–13.
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