Literature DB >> 7879773

Age estimation using dental periapical radiographic parameters. A review and comparative study of clinically based and regression models with the Operation Desert Storm victims.

D R Morse1, J V Esposito, H P Kessler, R Gorin.   

Abstract

A brief discussion of teeth and aging is followed by a review of the first four studies by our group at Temple University. In the present study, periapical, postmortem radiographs taken with the bisecting-angle technique from U.S. armed forces personnel killed during Operation Desert Storm were analyzed for age estimation. A total of 74 sets of dental radiographs (52 complete and 22 incomplete) with documented age of the individual at the time of death recorded were examined by investigators (D.R.M. and J.V.E.), who were blind to age range and specific ages of the victims. Comparisons were made between the same clinically based and multiple regression models used in a previous study of age estimation from private dental practice patients in which the long-cone radiographic technique had been used. Age estimation for both models was based on the same radiographic parameters used in that previous study (13 for the clinical model and eight for the regression model). Results showed that, in contrast to that previous study, the clinical model was superior to the regression model. Mean difference between estimated and actual age was +/- 4.4 years (clinical) and +/- 6.3 years (regression). Median difference between estimated and actual age was +/- 2.0 years (clinical) and +/- 6.0 years (regression). Mode difference between estimated and actual age was +/- 2.0 years (clinical) and +/- 6 and 7 years (regression). The results from the present study show that the clinical and regression models developed from full-mouth series of periapical radiographs taken of living patients by the long-cone radiographic technique can be used with decedents' radiographs taken with the bisecting-angle technique.

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Year:  1994        PMID: 7879773

Source DB:  PubMed          Journal:  Am J Forensic Med Pathol        ISSN: 0195-7910            Impact factor:   0.921


  2 in total

1.  A fully automated method of human identification based on dental panoramic radiographs using a convolutional neural network.

Authors:  Young Hyun Kim; Eun-Gyu Ha; Kug Jin Jeon; Chena Lee; Sang-Sun Han
Journal:  Dentomaxillofac Radiol       Date:  2021-12-02       Impact factor: 3.525

Review 2.  Forensic radiology in dentistry.

Authors:  T Manigandan; C Sumathy; M Elumalai; S Sathasivasubramanian; A Kannan
Journal:  J Pharm Bioallied Sci       Date:  2015-04
  2 in total

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