Journal of Oral Medicine and Pain

  • 제46권2호
  • /
  • Pages.21-32
  • /
  • 2021
  • /
  • 2288-9272(pISSN)
  • /
  • 2383-8493(eISSN)
대한안면통증구강내과학회 (Korean Academy of Orofacial Pain and Oral Medicine)
권호 표지
DOI QR코드

DOI QR Code

Age Estimation with Panoramic Radiomorphometric Parameters Using Generalized Linear Models

  • Lee, Yeon-Hee (Department of Orofacial Pain and Oral Medicine, Kyung Hee University Dental Hospital) ;
  • An, Jung-Sub (Department of Orthodontics, Seoul National University Dental Hospital)
  • 투고 : 2021.02.18
  • 심사 : 2021.03.24
  • 발행 : 2021.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Purpose: The purpose of the present study was to investigate the correlation between age and 34 radiomorphometric parameters on panoramic radiographs, and to provide generalized linear models (GLMs) as a non-invasive, inexpensive, and accurate method to the forensic judgement of living individual's age. Methods: The study included 417 digital panoramic radiographs of Korean individuals (178 males and 239 females, mean age: 32.57±17.81 years). Considering the skeletal differences between the sexes, GLMs were obtained separately according to sex, as well as across the total sample. For statistical analysis and to predict the accuracy of the new GLMs, root mean squared error (RMSE) and adjusted R-squared (R2) were calculated. Results: The adjusted R2-values of the developed GLMs in the total sample, and male and female groups were 0.623, 0.637, and 0.660, respectively (p<0.001), while the allowable RMSE values were 8.80, 8.42, and 8.53 years, respectively. In the GLM of the total sample, the most influential predictor of greater age was decreased pulp area in the #36 first molar (beta=-26.52; p<0.01), followed by the presence of periodontitis (beta=10.24; p<0.01). In males, the most influential factor was the presence of periodontitis (beta=9.20; p<0.05), followed by the number of full veneer crowns (beta=2.19; p<0.001). In females, the most influential predictor was the presence of periodontitis (beta=18.10; p<0.001), followed by the tooth area of the #16 first molar (beta=-11.57; p<0.001). Conclusions: We established acceptable GLM for each sex and found out the predictors necessary to age estimation which can be easily found in panoramic radiographs. Our study provides reference that parameters such as the area of tooth and pulp, the number of teeth treated, and the presence of periodontitis should be considered in estimating age.

키워드

참고문헌

  1. Juneja M, Devi YB, Rakesh N, Juneja S. Age estimation using pulp/tooth area ratio in maxillary canines-A digital image analysis. J Forensic Dent Sci 2014;6:160-165.
  2. Mathew DG, Rajesh S, Koshi E, Priya LE, Nair AS, Mohan A. Adult forensic age estimation using mandibular first molar radiographs: a novel technique. J Forensic Dent Sci 2013;5:56-59. https://doi.org/10.4103/0975-1475.114552
  3. Ilayaraja V, Ganapathy N, Jisha G, Keerthipriyadharshini T, Maheswaran T, Yoithapprabhunath TR. Digitized morphometric analysis using maxillary canine and mandibular first molar for age estimation in South Indian population. Open Dent J 2018;12:762-769. https://doi.org/10.2174/1745017901814010762
  4. Manjunatha BS, Soni NK. Estimation of age from development and eruption of teeth. J Forensic Dent Sci 2014;6:73-76. https://doi.org/10.4103/0975-1475.132526
  5. Fieuws S, Willems G, Larsen-Tangmose S, Lynnerup N, Boldsen J, Thevissen P. Obtaining appropriate interval estimates for age when multiple indicators are used: evaluation of an ad-hoc procedure. Int J Legal Med 2016;130:489-499. https://doi.org/10.1007/s00414-015-1200-8
  6. Farhadian M, Salemi F, Saati S, Nafisi N. Dental age estimation using the pulp-to-tooth ratio in canines by neural networks. Imaging Sci Dent 2019;49:19-26. https://doi.org/10.5624/isd.2019.49.1.19
  7. Panchbhai AS. Dental radiographic indicators, a key to age estimation. Dentomaxillofac Radiol 2011;40:199-212. https://doi.org/10.1259/dmfr/19478385
  8. Lambrechts P, Braem M, Vuylsteke-Wauters M, Vanherle G. Quantitative in vivo wear of human enamel. J Dent Res 1989;68:1752-1754. https://doi.org/10.1177/00220345890680120601
  9. Donachie MA, Walls AW. The tooth wear index: a flawed epidemiological tool in an ageing population group. Community Dent Oral Epidemiol 1996;24:152-158. https://doi.org/10.1111/j.1600-0528.1996.tb00833.x
  10. Eklund SA. Trends in dental treatment, 1992 to 2007. J Am Dent Assoc 2010;141:391-399. https://doi.org/10.14219/jada.archive.2010.0191
  11. Kanchan T, Krishan K. Mental foramen in prediction of age. J Clin Diagn Res 2015;9:GJ01.
  12. Ozturk CN, Ozturk C, Bozkurt M, Uygur HS, Papay FA, Zins JE. Dentition, bone loss, and the aging of the mandible. Aesthet Surg J 2013;33:967-974. https://doi.org/10.1177/1090820X13503473
  13. Lavelle CL. Preliminary study of mandibular shape after tooth loss. J Prosthet Dent 1985;53:726-730. https://doi.org/10.1016/0022-3913(85)90033-2
  14. Oksayan R, Asarkaya B, Palta N, Simsek I, Sokucu O, Isman E. Effects of edentulism on mandibular morphology: evaluation of panoramic radiographs. ScientificWorldJournal 2014;2014: 254932.
  15. Dye BA. Global periodontal disease epidemiology. Periodontol 2000 2012;58:10-25. https://doi.org/10.1111/j.1600-0757.2011.00413.x
  16. Hienz SA, Paliwal S, Ivanovski S. Mechanisms of bone resorption in periodontitis. J Immunol Res 2015;2015:615486.
  17. Tugnait A, Carmichael F. Use of radiographs in the diagnosis of periodontal disease. Dent Update 2005;32:536-538, 541-542. https://doi.org/10.12968/denu.2005.32.9.536
  18. Saxena S, Sharma P, Gupta N. Experimental studies of forensic odontology to aid in the identification process. J Forensic Dent Sci 2010;2:69-76. https://doi.org/10.4103/0975-1475.81285
  19. Dosi T, Vahanwala S, Gupta D. Assessment of the effect of dimensions of the mandibular ramus and mental foramen on age and gender using digital panoramic radiographs: a retrospective study. Contemp Clin Dent 2018;9:343-348.
  20. Limdiwala PG, Shah JS. Age estimation by using dental radiographs. J Forensic Dent Sci 2013;5:118-122. https://doi.org/10.4103/0975-1475.119778
  21. Shah PH, Venkatesh R. Pulp/tooth ratio of mandibular first and second molars on panoramic radiographs: an aid for forensic age estimation. J Forensic Dent Sci 2016;8:112. https://doi.org/10.4103/0975-1475.186374
  22. Pianosi F, Beven K, Freer J, Hall JW, Rougier J, Stephenson DB. Sensitivity analysis of environmental models: a systematic review with practical workflow. Environ Model Softw 2016;79:214-232. https://doi.org/10.1016/j.envsoft.2016.02.008
  23. Lu R, Wang D, Wang M, Rempala GA. Estimation of Sobol's sensitivity indices under generalized linear models. Commun Stat Theory Methods 2018;47:5163-5195. https://doi.org/10.1080/03610926.2017.1388397
  24. Renvert S, Persson RE, Persson GR. Tooth loss and periodontitis in older individuals: results from the Swedish National Study on Aging and Care. J Periodontol 2013;84:1134-1144. https://doi.org/10.1902/jop.2012.120378
  25. Van Horn ML, Jaki T, Masyn K, et al. Evaluating differential effects using regression interactions and regression mixture models. Educ Psychol Meas 2015;75:677-714. https://doi.org/10.1177/0013164414554931
  26. Babshet M, Acharya AB, Naikmasur VG. Age estimation in Indians from pulp/tooth area ratio of mandibular canines. Forensic Sci Int 2010;197:125.e1-4. https://doi.org/10.1016/j.forsciint.2009.12.065
  27. Hwang SY, Choi ES, Kim YS, Gim BE, Ha M, Kim HY. Health effects from exposure to dental diagnostic X-ray. Environ Health Toxicol 2018;33:e2018017. https://doi.org/10.5620/eht.e2018017
  28. Dehghani M, Shadkam E, Ahrari F, Dehghani M. Age estimation by canines' pulp/tooth ratio in an Iranian population using digital panoramic radiography. Forensic Sci Int 2018;285:44-49. https://doi.org/10.1016/j.forsciint.2018.01.016
  29. Roh BY, Lee WJ, Ryu JW, Ahn JM, Yoon CL, Lee SS. The application of the Kvaal method to estimate the age of live Korean subjects using digital panoramic radiographs. Int J Legal Med 2018;132:1161-1166. https://doi.org/10.1007/s00414-017-1762-8
  30. Lee JH, Lee C, Battulga B, et al. Morphological analysis of the lower second premolar for age estimation of Korean adults. Forensic Sci Int 2017;281:186.e1-186.e6. https://doi.org/10.1016/j.forsciint.2017.10.005
  31. Scheinost D, Noble S, Horien C, et al. Ten simple rules for predictive modeling of individual differences in neuroimaging. Neuroimage 2019;193:35-45. https://doi.org/10.1016/j.neuroimage.2019.02.057
  32. Gustafson G. Age determination on teeth. J Am Dent Assoc 1950; 41:45-54. https://doi.org/10.14219/jada.archive.1950.0132
  33. Paewinsky E, Pfeiffer H, Brinkmann B. Quantification of secondary dentine formation from orthopantomograms--a contribution to forensic age estimation methods in adults. Int J Legal Med 2005;119:27-30. https://doi.org/10.1007/s00414-004-0492-x
  34. Cameriere R, Brogi G, Ferrante L, et al. Reliability in age determination by pulp/tooth ratio in upper canines in skeletal remains. J Forensic Sci 2006;51:861-864. https://doi.org/10.1111/j.1556-4029.2006.00159.x
  35. Cameriere R, Ferrante L, Cingolani M. Precision and reliability of pulp/tooth area ratio (RA) of second molar as indicator of adult age. J Forensic Sci 2004;49:1319-1323.
  36. Kim S, Lee YH, Noh YK, Park FC, Auh QS. Age-group determination of living individuals using first molar images based on artificial intelligence. Sci Rep 2021. doi: 10.1038/s41598-020-80182-8. [Epub ahead of print]
  37. Demmer RT, Papapanou PN. Epidemiologic patterns of chronic and aggressive periodontitis. Periodontol 2000 2010;53:28-44. https://doi.org/10.1111/j.1600-0757.2009.00326.x
  38. Wu Y, Dong G, Xiao W, et al. Effect of aging on periodontal inflammation, microbial colonization, and disease susceptibility. J Dent Res 2016;95:460-466. https://doi.org/10.1177/0022034515625962
  39. Costa FO, Guimaraes AN, Cota LO, et al. Impact of different periodontitis case definitions on periodontal research. J Oral Sci 2009;51:199-206. https://doi.org/10.2334/josnusd.51.199
  40. Borrell LN, Beck JD, Heiss G. Socioeconomic disadvantage and periodontal disease: the Dental Atherosclerosis Risk in Communities study. Am J Public Health 2006;96:332-339. https://doi.org/10.2105/AJPH.2004.055277
  41. Copeland LB, Krall EA, Brown LJ, Garcia RI, Streckfus CF. Predictors of tooth loss in two US adult populations. J Public Health Dent 2004;64:31-37.
  42. Jayawardena CK, Abesundara AP, Nanayakkara DC, Chandrasekara MS. Age-related changes in crown and root length in Sri Lankan Sinhalese. J Oral Sci 2009;51:587-592. https://doi.org/10.2334/josnusd.51.587
  43. Van't Spijker A, Rodriguez JM, Kreulen CM, Bronkhorst EM, Bartlett DW, Creugers NH. Prevalence of tooth wear in adults. Int J Prosthodont 2009;22:35-42.

피인용 문헌

  1. Age Estimation Based on Mandibular Premolar and Molar Development: A Pilot Study vol.46, pp.4, 2021, https://doi.org/10.14476/jomp.2021.46.4.125