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International Journal of Legal Medicine

, Volume 130, Issue 4, pp 1129–1142 | Cite as

Accuracy of scoring of the epiphyses at the knee joint (SKJ) for assessing legal adult age of 18 years

  • Ivan Galić
  • Frane Mihanović
  • Alice Giuliodori
  • Federica Conforti
  • Mariano Cingolani
  • Roberto Cameriere
Original Article

Abstract

Important aspects of forensic practice are age estimation and discrimination of individuals of unknown age as adults and minors. The developing knee joint was recognized as a potential site for age examination in late adolescence. We analyzed a sample of anteroposterior x-rays of the knee joints from 446 living individuals from Umbria, Italy (234 males and 212 females), aged between 12 and 26 years. We evaluated the ossification of the distal femoral (DF), proximal tibial (PT), and proximal fibular (PF) epiphyses. We took into account possible persistence of the epiphyseal scars in the ossified epiphyses by the adopted stages of those previously introduced by Cameriere et al. (2012). We also used measurements from all three epiphyses to calculate the total score of maturation for the knee joint (SKJ). Cohen Kappa coefficients of intrarater agreement for staging the DF, PT, and PF epiphyses were 0.839, 0.894, and 0.907, while interrater agreement was 0.919, 0.791, and 0.907, respectively. The resulting receiver operating characteristic (ROC) curves of SKJ show better discriminatory power than those for DF, PT, and PF epiphyses in predicting that the participant, either male or female, was an adult or a minor. The areas under the curves for SKJ were 0.991 and 0.968 vs. 0.944, 0.962, 0.974 and 0.891, 0.910, 0.918 for males and females, respectively. The results of the 2 by 2 contingency tables showed that SKJ score of 4 in males and SKJ score of 5 in females were the most suitable cut-off value in discriminating between adults and minors. Principally, the sensitivity test for males was 0.94, with 95 % confidence interval (95 % CI) 0.90 to 0.97 and specificity was 0.96 (95 % CI 0.91 to 0.98). The proportion of correctly classified individuals was 0.95 (95 % CI 0.91 to 0.97). For females, the sensitivity test was 0.89 (95 % CI 0.84 to 0.92) and specificity was 0.92 (95 % CI 0.87 to 0.96), the proportion of correctly classified individuals was 0.90 (95 % CI 0.85 to 0.94). These results indicate that the SKJ method may give valuable supporting information in forensic procedures for discriminating individuals of legal adult age of 18 years. Further studies should address the usefulness of the SKJ method in different populations.

Keywords

Forensic science Knee joint Ossifying epiphyses Unaccompanied minor Age estimation Adult age 

Notes

Acknowledgments

We acknowledge Prof. Ana Marusic and Prof. Ana Jeroncic for assistance with editing and revising the manuscript. We are also grateful to anonymous reviewers for their comments and suggestions, which greatly improved the manuscript.

Compliance with ethical standards

The protocol to collect X-rays and perform the study was conducted in accordance with the ethical standards laid down by the Declaration of Helsinki. The Ethics Committee for Research Involving Human Subjects of the Foligno Hospital approved the study [96].

References

  1. 1.
    Adams BJ (2007) Forensic anthropology. Chelsea House, New YorkGoogle Scholar
  2. 2.
    Cunha E, Baccino E, Martrille L et al (2009) The problem of aging human remains and living individuals: a review. Forensic Sci Int 193:1–13. doi: 10.1016/j.forsciint.2009.09.008 CrossRefPubMedGoogle Scholar
  3. 3.
    Schmeling A, Reisinger W, Geserick G, Olze A (2006) Age estimation of unaccompanied minors. Part I. General considerations. Forensic Sci Int 159(Suppl 1):S61–S64. doi: 10.1016/j.forsciint.2006.02.017 CrossRefPubMedGoogle Scholar
  4. 4.
    Olze A, Reisinger W, Geserick G, Schmeling A (2006) Age estimation of unaccompanied minors. Part II. Dental aspects. Forensic Sci Int 159(Suppl 1):S65–S67. doi: 10.1016/j.forsciint.2006.02.018 CrossRefPubMedGoogle Scholar
  5. 5.
    Aynsley-Green A (2009) Unethical age assessment. Br Dent J 206:337. doi: 10.1038/sj.bdj.2009.260 CrossRefPubMedGoogle Scholar
  6. 6.
    Verley Kvittingen A (2010) Negotiating childhood: age assessment in the UK asylum system, Working paper series No 67. Refugee Studies Centre, Oxford Department of International Development, University of Oxford, OxfordGoogle Scholar
  7. 7.
    Lewis ME, Flavel A (2006) Age assessment of child skeletal remains in forensic contexts. In: Schmitt A, Cunha E, Pinheiro J (eds) Forensic anthropology and medicine. Humana Press, Totowa, pp 243–257CrossRefGoogle Scholar
  8. 8.
    Schmeling A, Olze A, Reisinger W, Geserick G (2001) Age estimation of living people undergoing criminal proceedings. Lancet 358:89–90. doi: 10.1016/S0140-6736(01)05379-X CrossRefPubMedGoogle Scholar
  9. 9.
    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 124:183–186. doi: 10.1007/s00414-009-0415-y CrossRefPubMedGoogle Scholar
  10. 10.
    Cameriere R, Ferrante L (2011) Canine pulp ratios in estimating pensionable age in subjects with questionable documents of identification. Forensic Sci Int 206:132–135. doi: 10.1016/j.forsciint.2010.07.025 CrossRefPubMedGoogle Scholar
  11. 11.
    Focardi M, Pinchi V, De Luca F, Norelli GA (2014) Age estimation for forensic purposes in Italy: ethical issues. Int J Legal Med 128:515–522. doi: 10.1007/s00414-014-0986-0 PubMedGoogle Scholar
  12. 12.
    (1975) Law No. 39 of March 8, 1975, on the recognition of the legal age of majority for citizens having reached 18 years old and amendment of other provisions relating to the capacity to act and the right to vote. Rome, ItalyGoogle Scholar
  13. 13.
    Liversidge HM (2008) Timing of human mandibular third molar formation. Ann Hum Biol 35:294–321. doi: 10.1080/03014460801971445 CrossRefPubMedGoogle Scholar
  14. 14.
    Knottnerus JA, Muris JW (2009) Assessment of the accuracy of diagnostic tests: the cross-sectional study. The evidence base of clinical diagnosis. Wiley-Blackwell, New York, pp 42–62Google Scholar
  15. 15.
    Habbema JDF, Eijkemans R, Krijnen P, Knottnerus JA (2009) Analysis of data on the accuracy of diagnostic tests. The evidence base of clinical diagnosis. Wiley-Blackwell, London, pp 118–145Google Scholar
  16. 16.
    Konigsberg LW, Herrmann NP, Wescott DJ, Kimmerle EH (2008) Estimation and evidence in forensic anthropology: age-at-death. J Forensic Sci 53:541–557. doi: 10.1111/j.1556-4029.2008.00710.x CrossRefPubMedGoogle Scholar
  17. 17.
    Bhat VJ, Kamath GP (2007) Age estimation from root development of mandibular third molars in comparison with skeletal age of wrist joint. Am J Forensic Med Pathol 28:238–241. doi: 10.1097/PAF.0b013e31805f67c0 CrossRefPubMedGoogle Scholar
  18. 18.
    Schmidt S, Baumann U, Schulz R, Reisinger W, Schmeling A (2008) Study of age dependence of epiphyseal ossification of the hand skeleton. Int J Legal Med 122:51–54. doi: 10.1007/s00414-007-0209-z CrossRefPubMedGoogle Scholar
  19. 19.
    Schmidt S, Nitz I, Schulz R, Schmeling A (2008) Applicability of the skeletal age determination method of tanner and Whitehouse for forensic age diagnostics. Int J Legal Med 122:309–314. doi: 10.1007/s00414-008-0237-3 CrossRefPubMedGoogle Scholar
  20. 20.
    Cardoso HF (2008) Epiphyseal union at the innominate and lower limb in a modern Portuguese skeletal sample, and age estimation in adolescent and young adult male and female skeletons. Am J Phys Anthropol 135:161–170. doi: 10.1002/ajpa.20717 CrossRefPubMedGoogle Scholar
  21. 21.
    De Luca S, De Giorgio S, Butti AC, Biagi R, Cingolani M, Cameriere R (2012) Age estimation in children by measurement of open apices in tooth roots: study of a Mexican sample. Forensic Sci Int 221(155):e1–e7. doi: 10.1016/j.forsciint.2012.04.026 PubMedGoogle Scholar
  22. 22.
    Cameriere R, De Luca S, De Angelis D et al (2012) Reliability of Schmeling’s stages of ossification of medial clavicular epiphyses and its validity to assess 18 years of age in living subjects. Int J Legal Med 126:923–932. doi: 10.1007/s00414-012-0769-4 CrossRefPubMedGoogle Scholar
  23. 23.
    Cameriere R, Ferrante L (2008) Age estimation in children by measurement of carpals and epiphyses of radius and ulna and open apices in teeth: a pilot study. Forensic Sci Int 174:60–63. doi: 10.1016/j.forsciint.2007.03.013 CrossRefPubMedGoogle Scholar
  24. 24.
    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 154:3–12. doi: 10.1016/j.forsciint.2004.08.018 CrossRefPubMedGoogle Scholar
  25. 25.
    Schmeling A, Geserick G, Reisinger W, Olze A (2007) Age estimation. Forensic Sci Int 165:178–181. doi: 10.1016/j.forsciint.2006.05.016 CrossRefPubMedGoogle Scholar
  26. 26.
    Schmeling A, Grundmann C, Fuhrmann A et al (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–460. doi: 10.1007/s00414-008-0254-2 CrossRefPubMedGoogle Scholar
  27. 27.
    Focardi M, Pinchi V, De Luca F, Norelli GA (2014) Reply to the letter to the editor. Int J Legal Med. doi: 10.1007/s00414-014-1044-7 Google Scholar
  28. 28.
    Rudolf E (2014) Comments to Focardi et al., Age estimation for forensic purposes in Italy: ethical issues. Int J Legal Med. doi: 10.1007/s00414-014-1043-8 Google Scholar
  29. 29.
    Schmidt S, Muhler M, Schmeling A, Reisinger W, Schulz R (2007) Magnetic resonance imaging of the clavicular ossification. Int J Legal Med 121:321–324. doi: 10.1007/s00414-007-0160-z CrossRefPubMedGoogle Scholar
  30. 30.
    Hillewig E, De Tobel J, Cuche O, Vandemaele P, Piette M, Verstraete K (2011) Magnetic resonance imaging of the medial extremity of the clavicle in forensic bone age determination: a new four-minute approach. Eur Radiol 21:757–767. doi: 10.1007/s00330-010-1978-1 CrossRefPubMedGoogle Scholar
  31. 31.
    Hillewig E, Degroote J, Van der Paelt T et al (2013) Magnetic resonance imaging of the sternal extremity of the clavicle in forensic age estimation: towards more sound age estimates. Int J Legal Med 127:677–689. doi: 10.1007/s00414-012-0798-z CrossRefPubMedGoogle Scholar
  32. 32.
    Dedouit F, Auriol J, Rousseau H, Rouge D, Crubezy E, Telmon N (2012) Age assessment by magnetic resonance imaging of the knee: a preliminary study. Forensic Sci Int 217(232):e1–e7. doi: 10.1016/j.forsciint.2011.11.013 PubMedGoogle Scholar
  33. 33.
    Jopp E, Schröder I, Maas R, Adam G, Püschel K (2010) Proximale Tibiaepiphyse im Magnetresonanztomogramm. Rechtsmedizin 20:464–468. doi: 10.1007/s00194-010-0705-1 CrossRefGoogle Scholar
  34. 34.
    Saint-Martin P, Rerolle C, Dedouit F et al (2013) Age estimation by magnetic resonance imaging of the distal tibial epiphysis and the calcaneum. Int J Legal Med 127:1023–1030. doi: 10.1007/s00414-013-0844-5 CrossRefPubMedGoogle Scholar
  35. 35.
    Saint-Martin P, Rerolle C, Dedouit F, Rousseau H, Rouge D, Telmon N (2014) Evaluation of an automatic method for forensic age estimation by magnetic resonance imaging of the distal tibial epiphysis—a preliminary study focusing on the 18-year threshold. Int J Legal Med 128:675–683. doi: 10.1007/s00414-014-0987-z CrossRefPubMedGoogle Scholar
  36. 36.
    Saint-Martin P, Rerolle C, Pucheux J, Dedouit F, Telmon N (2014) Contribution of distal femur MRI to the determination of the 18-year limit in forensic age estimation. Int J Legal Med. doi: 10.1007/s00414-014-1020-2 Google Scholar
  37. 37.
    Krämer JA, Schmidt S, Jurgens KU, Lentschig M, Schmeling A, Vieth V (2014) The use of magnetic resonance imaging to examine ossification of the proximal tibial epiphysis for forensic age estimation in living individuals. Forensic Sci Med Pathol 10:306–313. doi: 10.1007/s12024-014-9559-2 CrossRefPubMedGoogle Scholar
  38. 38.
    Krämer JA, Schmidt S, Jurgens KU, Lentschig M, Schmeling A, Vieth V (2014) Forensic age estimation in living individuals using 3.0 T MRI of the distal femur. Int J Legal Med 128:509–514. doi: 10.1007/s00414-014-0967-3 CrossRefPubMedGoogle Scholar
  39. 39.
    Schmidt S, Schiborr M, Pfeiffer H, Schmeling A, Schulz R (2013) Age dependence of epiphyseal ossification of the distal radius in ultrasound diagnostics. Int J Legal Med 127:831–838. doi: 10.1007/s00414-013-0871-2 CrossRefPubMedGoogle Scholar
  40. 40.
    Schmidt S, Schmeling A, Zwiesigk P, Pfeiffer H, Schulz R (2011) Sonographic evaluation of apophyseal ossification of the iliac crest in forensic age diagnostics in living individuals. Int J Legal Med 125:271–276. doi: 10.1007/s00414-011-0554-9 CrossRefPubMedGoogle Scholar
  41. 41.
    Mettler FA, Huda W, Yoshizumi TT, Mahesh M (2008) Effective doses in radiology and diagnostic nuclear medicine: a catalog. Radiology 248:254–263. doi: 10.1148/radiol.2481071451 CrossRefPubMedGoogle Scholar
  42. 42.
    Pyle SI, Hoerr NL (1955) Radiographic atlas of skeletal development of the knee. Charles C Thomas, SpringfieldGoogle Scholar
  43. 43.
    O’Connor JE, Bogue C, Spence LD, Last J (2008) A method to establish the relationship between chronological age and stage of union from radiographic assessment of epiphyseal fusion at the knee: an Irish population study. J Anat 212:198–209. doi: 10.1111/j.1469-7580.2007.00847.x CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    O’Connor JE, Coyle J, Bogue C, Spence LD, Last J (2014) Age prediction formulae from radiographic assessment of skeletal maturation at the knee in an Irish population. Forensic Sci Int 234(188):e1–e8. doi: 10.1016/j.forsciint.2013.10.032 PubMedGoogle Scholar
  45. 45.
    O’Connor JE, Coyle J, Spence LD, Last J (2013) Epiphyseal maturity indicators at the knee and their relationship to chronological age: results of an Irish population study. Clin Anat 26:755–767. doi: 10.1002/ca.22122 CrossRefPubMedGoogle Scholar
  46. 46.
    Hackman L, Black S (2013) Age estimation from radiographic images of the knee. J Forensic Sci 58:732–737. doi: 10.1111/1556-4029.12077 CrossRefPubMedGoogle Scholar
  47. 47.
    Schaefer MC, Black SM (2005) Comparison of ages of epiphyseal union in North American and Bosnian skeletal material. J Forensic Sci 50:777–784CrossRefPubMedGoogle Scholar
  48. 48.
    Roche AF, Chumlea W, Thissen D (1988) Assessing the skeletal maturity of the hand-wrist: Fels method. Thomas, SpringfieldGoogle Scholar
  49. 49.
    Roche AF, Wainer H, Thissen D (1975) Skeletal maturity: the knee joint as a biological indicator. Plenum Medical Book Co, New YorkGoogle Scholar
  50. 50.
    McKern TW, Stewart TD (1957) In: United States Army Quartermaster Research Development C (ed) Skeletal age changes in young American males analysed from the standpoint of age identification. Headquarters, Quartermaster Research & Development Command, Natick, p 170Google Scholar
  51. 51.
    Cameriere R, Cingolani M, Giuliodori A, De Luca S, Ferrante L (2012) Radiographic analysis of epiphyseal fusion at knee joint to assess likelihood of having attained 18 years of age. Int J Legal Med 126:889–899. doi: 10.1007/s00414-012-0754-y CrossRefPubMedGoogle Scholar
  52. 52.
    Weiss E, Desilva J, Zipfel B (2012) Brief communication: radiographic study of metatarsal one basal epiphyseal fusion: a note of caution on age determination. Am J Phys Anthropol 147:489–492. doi: 10.1002/ajpa.22022 CrossRefPubMedGoogle Scholar
  53. 53.
    Davies C, Hackman L, Black S (2016) The persistence of epiphyseal scars in the distal radius in adult individuals. Int J Legal Med 130:199–206. doi: 10.1007/s00414-015-1192-4 CrossRefPubMedGoogle Scholar
  54. 54.
    Faisant M, Rerolle C, Faber C, Dedouit F, Telmon N, Saint-Martin P (2015) Is the persistence of an epiphyseal scar of the knee a reliable marker of biological age? Int J Legal Med 129:603–608. doi: 10.1007/s00414-014-1130-x CrossRefPubMedGoogle Scholar
  55. 55.
    Prieto JL, Barberia E, Ortega R, Magana C (2005) Evaluation of chronological age based on third molar development in the Spanish population. Int J Legal Med 119:349–354. doi: 10.1007/s00414-005-0530-3 CrossRefPubMedGoogle Scholar
  56. 56.
    Martin-de las Heras S, Garcia-Fortea P, Ortega A, Zodocovich S, Valenzuela A (2008) Third molar development according to chronological age in populations from Spanish and Magrebian origin. Forensic Sci Int 174:47–53. doi: 10.1016/j.forsciint.2007.03.009 CrossRefPubMedGoogle Scholar
  57. 57.
    Fletcher R, Fletcher S (2005) Diagnosis. In: Fletcher R, Fletcher S (eds) Clinical epidemiology the essentials. Wolters, Kluwer, Lippincott, Williams & Wilkins, Baltimore, pp 35–58Google Scholar
  58. 58.
    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:E13. doi: 10.1038/sj.bdj.2010.976 CrossRefPubMedGoogle Scholar
  59. 59.
    The Italian National Institute of Statistics (2014) Resident population on the January, 1st 2014. IStatGoogle Scholar
  60. 60.
    Davies C, Hackman L, Black S (2014) The persistence of epiphyseal scars in the adult tibia. Int J Legal Med 128:335–343. doi: 10.1007/s00414-013-0838-3 CrossRefPubMedGoogle Scholar
  61. 61.
    Rai B, Kaur J (2013) Dental age estimation. Evidence-based forensic dentistry. Springer, Berlin Heidelberg, pp 35–63CrossRefGoogle Scholar
  62. 62.
    Schmeling A, Reisinger W, Loreck D, Vendura K, Markus W, Geserick G (2000) Effects of ethnicity on skeletal maturation: consequences for forensic age estimations. Int J Legal Med 113:253–258CrossRefPubMedGoogle Scholar
  63. 63.
    Schmeling A, Schulz R, Danner B, Rosing FW (2006) The impact of economic progress and modernization in medicine on the ossification of hand and wrist. Int J Legal Med 120:121–126. doi: 10.1007/s00414-005-0007-4 CrossRefPubMedGoogle Scholar
  64. 64.
    De Luca S, Biagi R, Begnoni G et al (2014) Accuracy of Cameriere’s cut-off value for third molar in assessing 18 years of age. Forensic Sci Int 235(102):e1–e6. doi: 10.1016/j.forsciint.2013.10.036 PubMedGoogle Scholar
  65. 65.
    Schmeling A, Garamendi PM, Prieto JL, Landa MI (2011) Forensic age estimation in unaccompanied minors and young living adults. In: Vieira DN (ed) Forensic medicine - from old problems to new challenges. InTech Europe Rijeka, Croatia, pp 77–120Google Scholar
  66. 66.
    Cameriere R, De Angelis D, Ferrante L, Scarpino F, Cingolani M (2007) Age estimation in children by measurement of open apices in teeth: a European formula. Int J Legal Med 121:449–453. doi: 10.1007/s00414-007-0179-1 CrossRefPubMedGoogle Scholar
  67. 67.
    Thevissen P, Altalie S, Brkić H et al (2013) Comparing 14 country-specific populations on third molars development: consequences for age predictions of individuals with different geographic and biological origin. J Forensic Odontostomatol 31:87–88Google Scholar
  68. 68.
    Cameriere R, Ferrante L, De Angelis D, Scarpino F, Galli F (2008) The comparison between measurement of open apices of third molars and Demirjian stages to test chronological age of over 18 year olds in living subjects. Int J Legal Med 122:493–497. doi: 10.1007/s00414-008-0279-6 CrossRefPubMedGoogle Scholar
  69. 69.
    Cameriere R, Santoro V, Roca R et al (2014) Assessment of legal adult age of 18 by measurement of open apices of the third molars: study on the Albanian sample. Forensic Sci Int 245C:205.e1–205.e5. doi: 10.1016/j.forsciint.2014.10.013 CrossRefGoogle Scholar
  70. 70.
    Galic I, Lauc T, Brkic H et al (2015) Cameriere’s third molar maturity index in assessing age of majority. Forensic Sci Int 252:191.e1–191.e5. doi: 10.1016/j.forsciint.2015.04.030 CrossRefGoogle Scholar
  71. 71.
    Deitos AR, Costa C, Michel-Crosato E, Galic I, Cameriere R, Biazevic MG (2015) Age estimation among Brazilians: younger or older than 18? J Forensic Leg Med 33:111–115. doi: 10.1016/j.jflm.2015.04.016 CrossRefPubMedGoogle Scholar
  72. 72.
    Olze A, van Niekerk P, Schulz R, Ribbecke S, Schmeling A (2012) The influence of impaction on the rate of third molar mineralisation in male black Africans. Int J Legal Med 126:869–874. doi: 10.1007/s00414-012-0753-z CrossRefPubMedGoogle Scholar
  73. 73.
    Cameriere R, Brkic H, Ermenc B, Ferrante L, Ovsenik M, Cingolani M (2008) The measurement of open apices of teeth to test chronological age of over 14-year olds in living subjects. Forensic Sci Int 174:217–221. doi: 10.1016/j.forsciint.2007.04.220 CrossRefPubMedGoogle Scholar
  74. 74.
    Ambarkova V, Galic I, Vodanovic M, Biocina-Lukenda D, Brkic H (2014) Dental age estimation using Demirjian and Willems methods: cross sectional study on children from the former Yugoslav Republic of Macedonia. Forensic Sci Int 234(187):e1–e7. doi: 10.1016/j.forsciint.2013.10.024 PubMedGoogle Scholar
  75. 75.
    Galic I, Vodanovic M, Jankovic S et al (2013) Dental age estimation on Bosnian-Herzegovinian children aged 6–14 years: evaluation of Chaillet’s international maturity standards. J Forensic Leg Med 20:40–45. doi: 10.1016/j.jflm.2012.04.037 CrossRefPubMedGoogle Scholar
  76. 76.
    Cameriere R, De Luca S, Biagi R, Cingolani M, Farronato G, Ferrante L (2012) Accuracy of three age estimation methods in children by measurements of developing teeth and carpals and epiphyses of the ulna and radius. J Forensic Sci 57:1263–1270. doi: 10.1111/j.1556-4029.2012.02120.x CrossRefPubMedGoogle Scholar
  77. 77.
    Tise M, Mazzarini L, Fabrizzi G, Ferrante L, Giorgetti R, Tagliabracci A (2011) Applicability of Greulich and Pyle method for age assessment in forensic practice on an Italian sample. Int J Legal Med 125:411–416. doi: 10.1007/s00414-010-0541-6 CrossRefPubMedGoogle Scholar
  78. 78.
    Greulich WW, Pyle SI (1959) Radiographic atlas of skeletal development of the hand and wrist, 2nd edn. Stanford University Press, Stanford, p xvi, 256Google Scholar
  79. 79.
    Baccetti T, Franchi L, McNamara JA (2005) The cervical vertebral maturation (CVM) method for the assessment of optimal treatment timing in dentofacial orthopedics. Semin Orthod 11:119–129CrossRefGoogle Scholar
  80. 80.
    Cameriere R, Giuliodori A, Zampi M et al (2015) Age estimation in children and young adolescents for forensic purposes using fourth cervical vertebra (C4). Int J Legal Med 129:347–355. doi: 10.1007/s00414-014-1112-z CrossRefPubMedGoogle Scholar
  81. 81.
    Thevissen PW, Kaur J, Willems G (2012) Human age estimation combining third molar and skeletal development. Int J Legal Med 126:285–292. doi: 10.1007/s00414-011-0639-5 CrossRefPubMedGoogle Scholar
  82. 82.
    Wittschieber D, Ottow C, Vieth V et al (2015) Projection radiography of the clavicle: still recommendable for forensic age diagnostics in living individuals? Int J Legal Med 129:187–193. doi: 10.1007/s00414-014-1067-0 CrossRefPubMedGoogle Scholar
  83. 83.
    Kellinghaus M, Schulz R, Vieth V, Schmidt S, Schmeling A (2010) Forensic age estimation in living subjects based on the ossification status of the medial clavicular epiphysis as revealed by thin-slice multidetector computed tomography. Int J Legal Med 124:149–154. doi: 10.1007/s00414-009-0398-8 CrossRefPubMedGoogle Scholar
  84. 84.
    Kellinghaus M, Schulz R, Vieth V, Schmidt S, Pfeiffer H, Schmeling A (2010) Enhanced possibilities to make statements on the ossification status of the medial clavicular epiphysis using an amplified staging scheme in evaluating thin-slice CT scans. Int J Legal Med 124:321–325. doi: 10.1007/s00414-010-0448-2 CrossRefPubMedGoogle Scholar
  85. 85.
    Wittschieber D, Schulz R, Vieth V et al (2014) The value of sub-stages and thin slices for the assessment of the medial clavicular epiphysis: a prospective multi-center CT study. Forensic Sci Med Pathol 10:163–169. doi: 10.1007/s12024-013-9511-x CrossRefPubMedGoogle Scholar
  86. 86.
    Nuzzolese E, Solarino B, Liuzzi C, Di Vella G (2011) Assessing chronological age of unaccompanied minors in southern Italy. Am J Forensic Med Pathol 32:202–207. doi: 10.1097/PAF.0b013e318221bc73 CrossRefPubMedGoogle Scholar
  87. 87.
    The Organisation for Economic Co-operation and Development (2014) International migration outlook 2014. OECD Publishing, Paris, p 266Google Scholar
  88. 88.
    Zelic K, Galic I, Nedeljkovic N et al (2015) Accuracy of Cameriere’s third molar maturity index in assessing legal adulthood on Serbian population. Forensic Sci Int 259:127–132. doi: 10.1016/j.forsciint.2015.12.032 CrossRefPubMedGoogle Scholar
  89. 89.
    The Organisation for Economic Co-operation and Development (2013) International migration outlook 2013. OECD Publishing, Paris, p 264Google Scholar
  90. 90.
    The Organisation for Economic Co-operation and Development (2012) International migration outlook 2012. OECD Publishing, Paris, p 242Google Scholar
  91. 91.
    Thevissen PW, Kvaal SI, Willems G (2012) Ethics in age estimation of unaccompanied minors. J Forensic Odontostomatol 30(Suppl 1):84–102PubMedGoogle Scholar
  92. 92.
    Corradi F, Pinchi V, Barsanti I, Manca R, Garatti S (2013) Optimal age classification of young individuals based on dental evidence in civil and criminal proceedings. Int J Legal Med 127:1157–1164. doi: 10.1007/s00414-013-0919-3 CrossRefPubMedGoogle Scholar
  93. 93.
    Lajolo C, Giuliani M, Cordaro M et al (2013) Two new oro-cervical radiographic indexes for chronological age estimation: a pilot study on an Italian population. J Forensic Leg Med 20:861–866. doi: 10.1016/j.jflm.2013.06.021 CrossRefPubMedGoogle Scholar
  94. 94.
    Aynsley-Green A, Cole TJ, Crawley H, Lessof N, Boag LR, Wallace RM (2012) Medical, statistical, ethical and human rights considerations in the assessment of age in children and young people subject to immigration control. Br Med Bull 102:17–42. doi: 10.1093/bmb/lds014 CrossRefPubMedGoogle Scholar
  95. 95.
    Schmeling A, Schulz R, Reisinger W, Muhler M, Wernecke KD, Geserick G (2004) Studies on the time frame for ossification of the medial clavicular epiphyseal cartilage in conventional radiography. Int J Legal Med 118:5–8. doi: 10.1007/s00414-003-0404-5 CrossRefPubMedGoogle Scholar
  96. 96.
    World Medical Association (2013) World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310:2191–2194. doi: 10.1001/jama.2013.281053 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.AgEstimation ProjectInstitute of Legal Medicine, University of MacerataMacerataItaly
  2. 2.Department of Radiologic TechnologyDepartment of Health Studies, University of SplitSplitCroatia
  3. 3.Departments of Research in Biomedicine and Health and Dental MedicineUniversity of Split School of MedicineSplitCroatia
  4. 4.Macerata HospitalMacerataItaly
  5. 5.Institute of Legal MedicineUniversity of PerugiaPerugiaItaly
  6. 6.Institute of Legal MedicineUniversity of MacerataMacerataItaly

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