Accepted Manuscript Digitized morphometric analysis of dental pulp of permanent mandibular second molar for age estimation among davangere population Dr. Nerella Narendra Kumar, Dr. Mamatha Gowda Panchaksharappa, Dr. Rajeshwari G. Annigeri PII:

S1752-928X(16)00020-2

DOI:

10.1016/j.jflm.2016.01.019

Reference:

YJFLM 1306

To appear in:

Journal of Forensic and Legal Medicine

Received Date: 12 July 2015 Revised Date:

3 December 2015

Accepted Date: 18 January 2016

Please cite this article as: Kumar NN, Panchaksharappa MG, Annigeri RG, Digitized morphometric analysis of dental pulp of permanent mandibular second molar for age estimation among davangere population, Journal of Forensic and Legal Medicine (2016), doi: 10.1016/j.jflm.2016.01.019. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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ORIGINAL RESEARCH: TITLE:

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DIGITIZED MORPHOMETRIC ANALYSIS OF DENTAL PULP OF PERMANENT MANDIBULAR SECOND MOLAR FOR AGE ESTIMATION AMONG DAVANGERE POPULATION

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FIRST AUTHOR: Dr. NERELLA NARENDRA KUMAR, DEPARTMENT OF ORAL MEDICINE AND RADIOLOGY, COLLEGE OF DENTAL SCIENCES, DAVANGERE, KARNATAKA – 577004. MOB.NO: +91- 9964806228, 9866904885 E-Mail: [email protected]

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SECOND AUTHOR: Dr. MAMATHA GOWDA PANCHAKSHARAPPA, DEPARTMENT OF ORAL MEDICINE AND RADIOLOGY, COLLEGE OF DENTAL SCIENCES, DAVANGERE, KARNATAKA – 577004. MOB.NO: +91- 9449748615 E-Mail: [email protected]

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THIRD AUTHOR: Dr. RAJESHWARI G.ANNIGERI, DEPARTMENT OF ORAL MEDICINE AND RADIOLOGY, COLLEGE OF DENTAL SCIENCES, DAVANGERE, KARNATAKA – 577004. PH.NO: 08192- 231285 E-Mail: [email protected]

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ORIGINAL RESEARCH: TITLE:

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DIGITIZED MORPHOMETRIC ANALYSIS OF DENTAL PULP OF PERMANENT MANDIBULAR SECOND MOLAR FOR AGE ESTIMATION OF DAVANGERE POPULATION Abstract:

Objective: The aim of the present study is to estimate the age of Davangere population by

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evaluating the pulp to tooth area ratio (PTR) by using digitized intraoral periapical radiographs

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of permanent mandibular second molar.

Methods: 400 intraoral periapical radiograph (IOPA) of permanent mandibular 2nd molar of both the sexes aged 14-60 years were used. Digital camera was used to image the radiographs. Images were computed and PTR was calculated by AUTOCAD software. Intra and Inter observer

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variability was also assessed. Regression analysis was used to estimate the age of an individual by taking PTR as dependent variable.

Results: The mean PTR of males and females was 0.10 ± 0.02 and 0.09 ± 0.02 respectively.

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Negative correlation was observed, when age was compared with PTR {r = -0.441, - 0.406 & 0.419) among males, females and total subjects (p < 0.001)}. Regression analysis showed a

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Standard Error of Estimate (SEE) of 12 years. The Kappa coefficient value for the intra and inter examiner variability was 0.85 & 0.83 respectively Conclusion: Our results showed that permanent mandibular 2nd molar can be taken as an index tooth for estimating the age of the adults using digitized periapical radiograph and AUTOCAD software. Also high differences were observed between estimated and chronological age of 12

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years which is not in the acceptable range. But it provides a new window for research in the forensic sciences in estimating the adult age.

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Key words: IOPA, Mandibular 2nd molar, PTR, Digitization, AUTOCAD.

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Introduction: As we entered a new millennium, society is faced with fresh challenges in every

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conceivable area. Despite leaps in modern technology, medical breakthroughs and the geographical changes that the last century has brought, crime still persists in all aspects of our lives. By identifying the victims of crime through dental records, dentists assist those involved in crime investigation.1 Identification is the establishment of a person’s individuality. Age is one of

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the essential factors in establishing the identity of a person.2 The need for the precise and reliable

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method to estimate age, particularly adult age, has become increasingly important.3 Age estimation helps in both civil and criminal cases such as kidnapping, rape, marriage, employment, identification, senior citizen concession, retirement benefits, in old age pension cases. Developmental indicators most commonly used for this purpose are bone maturation,

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secondary sex characteristics, height and weight. More recently, the dental maturation indicator system has gained impetus as a valuable index for age estimation.4 Teeth, the hardest structures in the body can act as a biomarker of aging. The reasons for

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this are they remain intact even when other components of the skeleton have disintegrated and are known to have highly resistant to different external influences as well as mechanical,

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chemical and thermal insults. Also, it has been further observed that the incremental pattern of tooth development or formation is not markedly affected by diseases, drug intake, endocrine status etc. as compared to bone mineralization, making them the favourite tissue in forensic and archaeological investigations.5-7 Various modalities for dental age estimation include morphological, histological, biochemical and radiographic methods. Morphologic and histological changes studied are

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attrition, secondary dentin deposition, recession of the gingiva, cementum apposition, root dentin transparency and root resorption.8 But major drawbacks of these methods require extraction and microscopic preparation which may not be acceptable for cultural, religious or scientific reasons.

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Radiographic evaluation of teeth requires neither tooth extraction nor sectioning. Therefore, techniques are being developed for age estimation in living individuals which mostly rely on

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radiological imaging of teeth.9,10

The study of morphological parameters of teeth on dental radiographs of adults is more

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reliable than other methods of age estimation.3 One such method is assessment of pulp to tooth area ratio which is an indirect quantification of secondary dentin deposition which is clearly seen on radiographs with advancing age that has significant correlation with age.11,12 However, advanced techniques like digitalization of panoramic radiographs, computer assisted image analysis, radiovisiography and volumetric analysis by cone beam computed tomography can be

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utilized, which offer advantages like elimination of bias inherent in observers’ subjectivity and improved reliability, accuracy and precision.3

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Most of the radiographic methods of age estimation have utilized anterior teeth and second premolars and only few studies have been reported where molar teeth have been utilized.

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Due to morphological stability, prolonged retention in oral cavity and easy accessible for radiographic procedure, permanent mandibular second molar is selected for assessment. Thus, the aim of the present study is to estimate age of Davangere population by evaluating the pulp to tooth area ratio using digitized intraoral periapical radiographs of permanent mandibular second molar. Material and Methods:

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The present prospective study was based on 400 digitized intraoral periapical radiographs of permanent mandibular 2nd molar taken from the individuals in the age range of 14-60 years. The subjects for this study were taken from the out patients that attended the Department of Oral

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Medicine and Radiology, College of Dental sciences, Davangere during the period, October 2013 to August 2014 after obtaining written informed consent. Protocol of the study was

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approved by the Ethical committee, College of Dental Sciences, Davangere.

Subjects were selected for the present study with the inclusion criteria of subjects with

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known date of birth and subjects willing to participate in the study with no obvious dental disease and developmental disorders. Exclusion criteria were: impacted teeth, teeth with root canal treatment, teeth with large area of overlap between neighbouring teeth, teeth with vestibular radio opaque fillings visible on radiographs, severe regression changes, teeth which are affected by pulpal calcification, developmental anomalies of teeth and subjects who are

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pregnant.

A total of 430 radiographs were assessed for age estimation. The pulp chamber was not

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able to delineate properly in 30 radiographs and hence they were discarded. Thus, a total of 400 radiographs were analyzed.

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All the subjects were divided into five groups; each group consisting of 80 subjects and

this 80 consists of 40 subjects from each gender based on their chronological age: group I (14 to 20 years); group II (21 to 30 years); group III (31 to 40years); group IV (41 to 50 years) and group V (51 to 60 years). Kvaal et.al (1995) stated that there were no significant differences between permanent teeth from the left or right side of the jaw.9 Consequently in the present study

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teeth were chosen either from the right or left side whichever were best suited for the measurement.

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All the subjects underwent routine clinical examination and the relevant data was entered in the structured proforma. Patients’ birth dates were noted after analyzing their specific identity proofs to record the chronological age. The intra oral periapical radiographs were taken by

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paralleling technique using X-ray equipment (Gendex Oralix with 65 KVP, 7.5 mA and exposure time ranges from 0.50 to 0.64 ms) with manual processing after taking all necessary protective

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measures. According to Koltveit et.al.,13 each radiograph was mounted on X-ray illuminating table and viewed through a digital camera (Sony DSC-WX 150, 18.2 Mega Pixel). Then the radiographic images were converted to a JPEG image file. These digitized images were imported to Adobe Photoshop CS image editing software program wherein the teeth long axis were aligned vertically using the measure tool. A number of horizontal reference lines are marked at

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specific intervals along the length of the tooth, after which the images were once again saved as high resolution JPEG files. The digitized images were processed using computer aided drafting program (AUTOCAD 2012). Using the Spline tool provided in this program and the outline of

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the tooth and its pulp chamber were traced on the digitized image. The tracing of the images was

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done using twenty points for each tooth outline and ten points for the pulp chamber. After completion of the tracing, the program displayed the area of the tooth and its pulp chamber respectively. Then the pulp/tooth area ratio of the tooth was calculated. (Figure 1) To test the intra examiner reproducibility, a random sample of forty digitized images

were re-examined after an interval of 4 weeks. To test the inter examiner reproducibility, a random sample of forty digitized images were re-examined by the second author.

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Statistical Analysis: Statistical analysis was performed using Statistical Program for Social Sciences (SPSS),

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Version 16. Unpaired t-test was used to assess the difference between PTR of males and females. Pearson’s correlation test was used to assess the correlation between the age and PTR. To predict the age of an individual simple linear regression analysis was used. To assess the Intra and Inter

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observer variability, Kappa statistics was used. p value of < 0.05 was considered as significant. Results:

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A total of 400 subjects were included in the present study, among which 200 individuals of each sex in the age range of 14- 60 years were included.

The mean PTR of subjects in each group was shown in table 1. The mean PTR of males and females were 0.10 ± 0.02 and 0.09 ± 0.02, unpaired t- test revealed a p value of 0.008 which

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showed a statistically significant difference suggesting that gender have an effect on the morphological variable (PTR). (Table 2)

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To assess the nature and degree of correlation of morphological variable i.e., PTR with actual age, Pearson’s correlation coefficient was employed. (Table 3) It was found that PTR was

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significantly correlated with age and has an inverse relationship with each other. Scattered plot showing relationship between PTR and age of females, males and combined sample was presented in Figure 2 a, b & c respectively. Linear Regression analysis was done where the age was taken as dependent variable and PTR as an independent variable. Linear regression equation for estimation of age and Standard Error of Estimate (SEE) was presented in Table 4. As there was statistically significant

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difference of PTR between males and females (p = 0.008), separate prediction equation for age estimation was derived for males and females separately. SEE predicts the deviation of estimated age from the actual age, it was 11.9 and 12.0 years in males and females respectively, when

regression plot was presented in Figure 3.

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considered as a whole sample it was 12.0 years. The actual versus predicted age on the

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The data recorded by the examiners was subjected to Kappa statistical analysis in order to find the degree of consistency or variation in judgments made by the examiners. The Kappa

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coefficient value for intra examiner variability was 0.85 and inter examiner variability was 0.83. This value reflects a high degree of conformity in observational judgements among the examiners. Discussion:

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Although the last century has witnessed major breakthroughs in the field of science and technology, crime still persists with increased percentage in all aspects of life. Age is one of the essential factors in establishing the identity of a person.14 Traditionally, forensic specialists are

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required to estimate the age in unidentified cadavers and human remains to create a post-mortem profile. However, in the present global socio-political scenario, an increasing demand also exists

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for age estimation in living persons.15 It may be necessary to estimate an individual’s age in situations such as identification, criminal responsibility, judicial punishment, rape, criminal abortion, employment, attainment of majority, kidnapping etc. for legal requirements.16 In India due to lower literacy status, parents and their children do not have accurate knowledge of their date of birth records which would be required in legal matters concerning the age of the individual.

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Although several parts of the body can be used for age estimation, the poor condition of the remains often prevents their use.4 In search of reliable indicator, most researchers considered teeth as the biomarker for estimating age. This is because it is the most durable part of the

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skeleton even when other skeletal remains are in poor condition and even they can be clinically inspected in living individuals. Most of the age estimation methods using teeth are invasive and warrants extraction of teeth, unless indicated it is not ethical.9,17 Any method used in forensic

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sciences should clarify the issues with significant legal and social ramifications for individuals as well as for the community.18 In search of simple, non- destructive and reliable method using

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dentition which can be used even in the living individuals. The radiographic method of age estimation emerges as a choice of modality.

In 1925, Bodecker established that the apposition of secondary dentine was related to chronological age.19 The study of morphological parameters of teeth on radiographs is

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considered to be more reliable than other methods of age estimation.20 Assessment of PTR which is an indirect quantification of secondary dentin deposition which is clearly seen on radiographs with advancing age which has a significant correlation with age.12 Evaluation of the PTR is

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considered as an ‘internal examination’ with the potential to eliminate the affect of

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environmental factors on human remains. The ratio between tooth and pulp measurements was calculated in order to reduce the variations in magnification.21 Most of the previous studies on the radiographic methods of age estimation using PTR

were performed on single rooted teeth like maxillary and mandibular central incisors, lateral incisors & canines and mandibular premolars.4,10,12,17,20,21,22,23,24,25 Previously only one study conducted by Cameriere R et.al in 2004 which utilized PTR of mandibular 2nd molars for adult age estimation.3 Very few studies were reported on age estimation using multi-rooted teeth. So

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one such attempt has been made in the present study to find out whether the permanent mandibular second molar can act as a marker for age estimation. Permanent mandibular second molar was selected for assessment because of morphological stability, least commonly affected

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by caries and attrition when compared to the first molars, superimposition of radiographic image of teeth by other anatomical structures are minimal, chances of congenitally missing are rare, prolonged retention in oral cavity and easy accessible for radiographic procedure. The result

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showed by the present study was statistically significant (p < 0.001) which is arrived by using the

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PTR of mandibular 2nd molar for assessing the age of an individual.

Previously reported age estimation studies using image analysis software i.e., AUTOCAD showed the fruitful results.3,10,12, 17, 22,23, 25 The imaging analysis software was used inorder to avoid bias inherent in the observer subjectivity, to improve reliability and statistical

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analysis of the data.

The minimum age of the individual in the present study is 14 years and maximum age of 60 years. As the root completion of permanent mandibular 2nd molar will take place around 14 to

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15 years, so the individuals with the chronological age of > 14 years were included in the present study. Total study subjects were divided into five groups in the present study with 10 years class

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interval. The 10 years difference was taken because in a study conducted by Morse DR (1991) found statistically significant shrinkage in root canal due to dentin deposition was noted with advancing age between 10 years of age.26 The mean PTR of the study subjects was 0.10 ± 0.02, ranging from 0.08 ± 0.02 to 0.11 ± 0.02. These results are comparable with the results arrived by Cameriere et.al., in which case the mean PTR of individuals ranging from 0.088 to 0.097 and mandibular 2nd molar was taken as an

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index teeth.3 From the results of group wise PTR (Table 2), it can be inferred that secondary dentin formation was less in younger subjects when compared to the older subjects as secondary dentin formation might takes place at a faster rate. Much of this variability also may be

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associated with different environmental factors such as diet and even due to the error in morphometry of pulp. Abrasive diet can cause wearing away of the tooth surface which can increase the deposition of secondary dentin and this in turn causes reduction in the size of the

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pulp. The study population consisted of local Kannadiga population who do not have severe abrasive diet habits. Further, in young age upto 30 years soft to moderately abrasive diet are

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consumed which gives support to less reduction of pulp chamber in the younger individuals. The mean PTR of males and females in the present study is 0.101 ± 0.02 and 0.095 ± 0.022 respectively. The p value of 0.011 signifies PTR was significantly lower in females than in males. This reveals that there is a necessity to derive a gender specific equation to predict the age

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of an individual accurately when considering the mandibular 2nd molar as an index tooth. Size of the teeth may be smaller in females which could result in a smaller size of pulp chamber. This could be a reason for the significant difference. Mean PTR of males and females was not

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significant in the study conducted by Cameriere R et.al (2009).27 This was in contrast to the

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results of our study because this study was carried on extracted teeth from the skeletons. It is also found that there is no significant difference in the mean PTR of males and females in the study conducted by Jeevan MB et.al (2011)4 which was in contrast to our study. In the present study, Pearson’s correlation coefficient between age and PTR showed

highly statistically significant value (p < 0.001) for r = -0.441, -0.406 & -0.419 among males, females and total subjects which was negatively correlated and was in accordance with the literature.9,12,17, 23,25,28

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When the three – dimensional pulp was reproduced in two dimensional radiograph, the edges of the pulp may be blurred due to the cylindrical shape of the pulp of multirooted teeth. This cannot be clearly delineated on the radiographs which resulted in a low pulpal volume.

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Hence, low correlation value (-0.419) in the present study. These results can be compared with the studies conducted on Indian subjects by Babshet M et.al (2010, 11).17,20 Studies conducted by Jeevan MB et.al (2011) and Afify MM et.al (2014) showed highest r value (-0.995 & -0.914 to -

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0.947) respectively.4,25 The size of pulp area in canines revealed that the secondary dentin deposition was better than any other teeth, which could be the one of the reason for increased

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correlation. The rate of secondary deposition in Indians is slower when compared to the Egyptian population. This could be the reason for low value in our study. The amount of masticatory stresses beared by posterior teeth is more when compared to the canines and premolars. This leads to the increased secondary dentin deposition rather than anterior teeth which could finally

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result in the low PTR value and hence the lowest correlation observed in our study. Simple linear regression analysis is the most commonly used one in the Forensic research to estimate the age. This method was used by Cameriere et.al (2004), Zaher JF et.al (2011),

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Affify MM et.al (2014) landed up finally with fruitful results.3,10,12,25 Even in our study PTR was

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the only dependent variable against chronological age. Hence, simple linear regression analysis is used in our study to predict the age of the individuals. In the present study, we derived a separate equation to predict the age of individual inorder to avoid the variations in sample size, technique used and also geographical location of the individuals. The predicted age of an individual is relatively higher from the chronological age with the SEE of around 12 years. This was relatively higher when compared to the previous studies. 3,10,12,17,22,23,25

This wide variation in our study may be due to the variation in the sample size,

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geographical variation and also the teeth (multirooted) selected for the study. Another reason might be that the secondary dentin deposition occurs throughout the life and leads to a reduction in the size of the pulp cavity and presently there is no evidence that this process occurs in a linear

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manner or that every age group needs the same time span to present itself with a defined amount of secondary dentin. Although linear regression is widely used in forensics to provide the estimate of a measurement, (for instance the age at death or the living stature) it should be kept

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in mind that human growth is non- linear process. So the timing of secondary dentin formation is more closely fit by a curved line rather than a straight line. Therefore, it could be possible that

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the formation rate of secondary dentin does underlie the chronological differences, which, in turn, would imply the need for further research to provide sufficient data for age estimation.29 Poor precision in measurement of an anthropometric variable will lead to underestimation of correlations with other variables. The main sources of imprecision errors are random

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imperfections in the measuring instruments or in the measuring and recording techniques.30 Even the Inter and Intra observer differences were noticed in a non destructive dental age calculation methods in adults (i.e. in both morphological methods and radiographic methods).31 So we

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assessed both the intra and inter examiner variability. This is 0.85 & 0.83 respectively which

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reflects a high degree of conformity in observational judgements within or between the examiner/s.

Nevertheless, the derived formula had very modest numbers of ‘‘acceptable’’ age

estimates. It appears that the low correlation between secondary dentine deposition and age in Davangere population (r = -0.419) is responsible for sub-optimal age estimation. Our findings here point to the same inference drawn by Babshet M,20 Dental parameters in isolation (e.g. secondary dentine deposition) may lead to higher errors. Nonetheless, radiographic evaluation of

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fully developed teeth probably allows for the assessment of secondary dentine only, and there may be no other suitable dental parameter available for non-invasive adult age estimation. An approach to enhance age prediction may be to use multiple teeth and future studies could include

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additional teeth like canines in which secondary deposition will be better than any teeth and multiple regression models.

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Further research should aim at involving larger sample, including not only age and gender but also race and culture parameters. In future, studies have to be done on multi-radicular

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teeth to rely on these teeth; which can serve as an index for age estimation and also the application of recent statistical methods rather than going for conventional ones. Conclusion:

Till now reported in the literature this was the first study which used the permanent

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mandibular 2nd molar as an index teeth for estimating the age for wide range of age group i.e., from 14- 60 years where the PTR was used as a dependent variable. Even our study results showed a wide variation in the estimated age which is not in the acceptable range. It provides a

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new window of opportunity in the field of forensic research where the further studies can be carried out to check the reliability of multirooted teeth in age estimation rather than going for

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invasive analysis.

Competing interests: None Funding: None

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Acknowledgments: We would like to thank the DR. D.K.Sangam for his timely help for

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Statistical analysis and also Mr. Santosh for his guidance in AUTOCAD software.

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Figure 1: Tracing of Tooth and Pulpal Outline and Calculation of Tooth & Pulpal Area using AUTOCAD. Figure 2a: Scattered plot showing Relationship between Age and PTR in Females.

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Figure 2b: Scattered plot showing Relationship between Age and PTR in Males.

Figure 2c: Scattered plot showing Relationship between Age and PTR in combined sample.

AC C

EP

TE D

M AN U

SC

Figure 3: Scattered plot showing Predicted versus Actual age in the whole sample.

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Table 1: Descriptive Statistics of PTR in each age group. Females

Combined

Group- I

0.111±0.017 0.105±0.030 0.108±0.025

Group - II

0.111±0.021 0.104±0.023 0.108±0.022

Group - III

0.103±0.023 0.097±0.017 0.100±0.021

Group - IV

0.092±0.018 0.091±0.019 0.091±0.018

Group- V

0.089±0.019 0.078±0.012 0.084±0.017

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Males

AC C

EP

TE D

M AN U

SC

Group

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Sex

Mean ±SD

Male

0.101±0.022

Female

t value

p value

2.65

0.008*

0.095±0.023

AC C

EP

TE D

M AN U

SC

PTR- Pulp to Tooth area Ratio, *- significant difference

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Table 2: Sex wise comparison of PTR

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Table 3: Pearson’s Correlation between age and predictive morphological variable (PTR) p value

Males

-0.441