Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
International Journal of Legal Medicine
Published in: International Journal of Legal Medicine 6/2013

01-11-2013 | Original Article

Optimal age classification of young individuals based on dental evidence in civil and criminal proceedings

Authors: Fabio Corradi, Vilma Pinchi, Iljà Barsanti, Roberto Manca, Stefano Garatti

Published in: International Journal of Legal Medicine | Issue 6/2013

Login to get access

Abstract

Background

Criminal cases involving young people, irregular immigration and the many issues related to asylum seekers has increased the judicial demand of age estimation. Calcification of teeth and specifically of third molar has demonstrated to be reliable evidence to estimate age respect to 18 years threshold of age.

Aims

As prosecution of research of Pinchi et al. (2010) and Corradi et al. (J Forensic Sci 58:51–59, 2013), the study aims to evaluate if tuning the size of the zone of indifference posed around the age threshold improves the performances of the age classification model.

Materials and methods

The sample was composed of 1,560 OPGs of Italian subjects aged between 15 and 22 years. Third molar calcification stage was assessed according to Demirjian’s scale by three different experts. Intra- and inter-operator variability has been calculated. The statistical analysis was provided by a Modified Naïve Bayesian allowing the use of soft evidence. Rate of in/correct classification was provided for individuals classified at a very high level of probability (90 %), as needed for criminal cases, and for a lower probability level (51 %) as it suffices for civil cases.

Results

The intra-observer reproducibility varies between 79.2 and 89.2 % with soft evidence, whilst it decreases from values between 0.589 and 0.763, when only hard evidence is allowed to experts showing the usefulness of the MBN approach. In civil cases, imposing the constraint of classifying at least 95 % of the individuals, the method achieved a rate of correct classification in the range 80–83 % depending on the expert. In criminal cases, we tuned the ZOI size to achieve 85 % of individuals correctly classified and the model succeeded in classifying 66–81 % of the sample, the variability still being dependent on the expert’s ability.

Conclusions

After a review of several studies concerning the age classification of young individuals by using dental evidence, we must conclude that it is almost impossible to make a comparison among them. To rank the effectiveness of different methods is to challenge them with the same problem and data, looking at the results measured by the same accepted scoring rule. It could also be interesting to repeat the experiment in different conditions varying the reference population and considering if some important covariates, like sex and health status, influence the model performances.
Appendix
Available only for authorised users
Literature
1.
Schmeling A, Grundmann C, Fuhrmann A, Kaatsch HJ, Knell B, Ramsthaler F, Reisinger W, Riepert T, Ritz-Timme S, Rösing FW, Rötzscher K, Geserick G (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–460PubMed
2.
3.
Olze A, Solheim T, Schulz R, Kupfer M, Pfeiffer H, Schmeling A (2010) Assessment of the radiographic visibility of the periodontal ligament in the lower third molars for the purpose of forensic age estimation in living individuals. Int J Legal Med 124:445–448PubMed
4.
Olze A, Solheim T, Schulz R, Kupfer M, Schmeling A (2010) Evaluation of the radiographic visibility of the root pulp in the lower third molars for the purpose of forensic age estimation in living individuals. Int J Legal Med 124:183–186PubMed
5.
Olze A, Hertel J, Schulz R, Wierer T, Schmeling A (2012) Radiographic evaluation of Gustafson’s criteria for the purpose of forensic age diagnostics. Int J Legal Med 126:615–621PubMed
6.
Knell B, Ruhstaller P, Prieels F, Schmeling A (2009) Dental age diagnostics by means of radiographical evaluation of the growth stages of lower wisdom teeth. Int J Legal Med 123:465–469PubMed
7.
Pinchi V, Norelli GA, Pradella F, Vitale G, Rugo D, Nieri M (2012) Comparison of the applicability of four odontological methods for age estimation of the 14 years legal threshold in a sample of Italian adolescents. J Forensic Odontostomatol 30:17–25PubMed
8.
9.
Thevissen PW, Fieuws S, Willems G (2010) Human third molars development: comparison of nine country specific populations. Forensic Sci Int 201:102–105PubMed
10.
Liversidge HM, Marsden PH (2010) Estimating age and the likelihood of having attained 18 years of age using mandibular third molars. Br Dent J 209:E13PubMed
11.
Lee SS, Byun YS, Park MJ, Choi JH, Yoon CL, Shin KJ (2010) The chronology of second and third molar development in Koreans and its application to forensic age estimation. Int J Legal Med 124:659–665PubMed
12.
Acharya AB (2011) Accuracy of predicting 18 years of age from mandibular third molar development in a Indian sample using Demirjian’s ten-stage criteria. Int J Legal Med 125:227–233PubMed
13.
Bacci M, Pezzulli S, Benucci G, Giusti GV (1996) La radiografia dentaria per la previsione d’età: assimilazione Bayesiana dei dati sulla mineralizzazione e diagnosi ottimale. Riv It Med Leg 18:1005–1048
14.
Lucy D, Aykroyd RG, Pollard AM, Solheim T (1996) A Bayesian approach to adult human age estimation from dental observations by Johanson’s ages changes. J Forensic Sci 41:189–194PubMed
15.
Corradi F, Pinchi V, Barsanti I, Garatti S (2013) Probabilistic classification of age by third molar development: the use of soft evidence. J Forensic Sci 58:51–59PubMed
16.
Braga J, Hueze Y, Chabadel O, Sonan NK, Gueramy A (2005) Non-adult dental age assessment: correspondence analysis and linear regression versus Bayesian predictions. Int J Legal Med 119:260–274PubMed
17.
Demirijan A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227
18.
Demirjian A, Goldstein H (1976) New systems for dental maturity based on seven and four teeth. Ann Hum Biol 3:411–421PubMed
19.
Sisman Y, Uysal T, Yagmur F, Ramoglu SI (2007) Third-molar development in relation to chronologic age in Turkish children and young adults. Angle Orthod 77:1040–1045PubMed
20.
de Oliveira FT, Capelozza AL, Lauris JR, de Bullen IR (2012) Mineralization of mandibular third molars can estimate chronological age—Brazilian indices. Forensic Sci Int 219:147–150PubMed
21.
Garamendi PM, Landa MI, Ballesteros J, Solano MA (2005) Reliability of the methods applied to assess age minority in living subjects around 18 years old: a survey on a Moroccan origin population. Forensic Sci Int 154:3–12PubMed
22.
Pearl J (1988) Probabilistic reasoning in intelligent system: networks of plausible inference. Morgan Kaufmann, San Francisco
23.
Hand DJ, Yu K (2001) Idiot’s Bayes—not so stupid after all? Int Stat Rev 69:385–399, ISSN 0306–7734
24.
Cowell RG, Dawid AP, Lauritzen SL, Spiegelhalter DJ (1999) Probabilistic networks and expert systems. Springer, Berlin, Heidelberg
25.
Pruvost MO, Boraud C, Chariot P (2010) Skeletal age determination in adolescents involved in judicial procedures: from evidence-based principles to medical practice. J Med Ethics 36(2):71–74
26.
Pinchi V, Norelli GA, Caputi F, Fassina G, Pradella F, Vincenti C (2012) Dental identification by comparison of antemortem and postmortem dental radiographs: influence of operator qualifications and cognitive bias. Forensic Sci Int 222:252–255PubMed
27.
Liversidge HM (2012) The assessment and interpretation of Demirjian, Goldstein and Tanner’s dental maturity. Ann Hum Biol 39:412–431PubMed
28.
Lewis JM, Senn DR (2010) Dental age estimation utilizing third molar development: a review of principles, methods, and population studies used in the United States. Forensic Sci Int 201:79–83PubMed
29.
30.
Thevissen PW, Fieuws S, Willems G (2010) Human dental age estimation using third molar developmental stages: does a Bayesian approach outperform regression models to discriminate between juveniles and adults? Int J Legal Med 124:35–42PubMed
31.
Portigliatti Barbos M, Robetti I, Iorio M, Festa T (1982) L’accertamento dell’età dentaria nel secondo decennio di vita quale contributo alla definizione della competenza dei tribunali minorili. Riv It Med Leg 4:863–873
32.
Metadata
Title
Optimal age classification of young individuals based on dental evidence in civil and criminal proceedings
Authors
Fabio Corradi
Vilma Pinchi
Iljà Barsanti
Roberto Manca
Stefano Garatti
Publication date
01-11-2013
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Legal Medicine / Issue 6/2013
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI
https://doi.org/10.1007/s00414-013-0919-3

Other articles of this Issue 6/2013

International Journal of Legal Medicine 6/2013 Go to the issue

Original Article

Image analysis of pubic bone for sex determination in a computed tomography sample

Original Article

Single nucleotide polymorphism typing with massively parallel sequencing for human identification

Original Article

Ballistic parameters of .177 (4.5 mm) caliber plastic-sleeved composite projectiles compared to conventional lead pellets

Technical Note

The application of cone-beam CT in the aging of bone calluses: a new perspective?

Short Communication

Influence of an individual's age on the amount and interpretability of DNA left on touched items

Original Article

Body fluid identification by mass spectrometry