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European Radiology
Published in: European Radiology 6/2019

01-06-2019 | Magnetic Resonance Imaging | Forensic Medicine

Forensic age estimation based on T1 SE and VIBE wrist MRI: do a one-fits-all staging technique and age estimation model apply?

Authors: Jannick De Tobel, Elke Hillewig, Michiel Bart de Haas, Bram Van Eeckhout, Steffen Fieuws, Patrick Werner Thevissen, Koenraad Luc Verstraete

Published in: European Radiology | Issue 6/2019

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Abstract

Objectives

Providing recommendations for wrist MRI in age estimation by determining (1) which anatomical structures to include in the statistical model, (2) which MRI sequence to conduct, and (3) which staging technique to apply.

Methods

Radius and ulna were prospectively studied on 3 T MRI in 363 healthy Caucasian participants (185 females, 178 males) between 14 and 26 years old, using T1 spin echo (SE) and T1 gradient echo VIBE. Bone development was assessed applying a 5-stage staging technique with several amelioration attempts to optimise staging. A Bayesian model rendered point predictions of age and diagnostic indices to discern minors from adults.

Results

All approaches rendered similar results, with none of them outperforming the others. A single bone assessment of radius or ulna sufficed. SE and VIBE sequences were both suitable, but needed sequence-specific age estimation. A one-fits-all 5-stage staging technique—with substages in stage 3—was suitable and did not benefit from profound substaging. Age estimation based on SE radius resulted in a mean absolute error of 1.79 years, a specificity (correctly identified minors) of 93%, and a discrimination slope of 0.640.

Conclusion

Radius and ulna perform similarly to estimate age, and so do SE and VIBE. A one-fits-all staging technique can be applied.

Key Points

• Radius and ulna perform similarly to estimate age.
• SE and VIBE perform similarly, but age estimation should be based on the corresponding sequence-specific reference data.
• A one-fits-all 5-stage staging technique with substages 3a, 3b, and 3c can be applied to both bones and both sequences.
Appendix
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Literature
1.
2.
De Tobel J, Phlypo I, Fieuws S, Politis C, Verstraete KL, Thevissen PW (2017) Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging. J Forensic Odontostomatol 35:117–140PubMedCentral
3.
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 127:677–689CrossRefPubMed
4.
Ottow C, Schulz R, Pfeiffer H, Heindel W, Schmeling A, Vieth V (2017) Forensic age estimation by magnetic resonance imaging of the knee: the definite relevance in bony fusion of the distal femoral- and the proximal tibial epiphyses using closest-to-bone T1 TSE sequence. Eur Radiol 27:5041–5048CrossRefPubMed
5.
Štern D, Kainz P, Payer C, Urschler M (2017) Multi-factorial age estimation from skeletal and dental MRI Volumes. In: International workshop on machine learning in medical imaging. Springer, Quebec City, pp 61–69CrossRef
6.
Timme M, Ottow C, Schulz R et al (2017) Magnetic resonance imaging of the distal radial epiphysis: a new criterion of maturity for determining whether the age of 18 has been completed? Int J Legal Med 131:579–584CrossRefPubMed
7.
8.
Thevissen PW (2013) Dental age estimation in sub-adults: striving for an optimal approach. Leuven University Press, Leuven
9.
Cunha E, Baccino E, Martrille L et al (2009) The problem of aging human remains and living individuals: a review. Forensic Sci Int 193:1–13CrossRefPubMed
10.
Urschler M, Grassegger S, Štern D (2015) What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents. Ann Hum Biol 42:358–367CrossRefPubMed
11.
Serin J, Rérolle C, Pucheux J et al (2016) Contribution of magnetic resonance imaging of the wrist and hand to forensic age assessment. Int J Legal Med 130:1121–1128CrossRefPubMed
12.
Dvorak J (2009) Detecting over-age players using wrist MRI: science partnering with sport to ensure fair play. Br J Sports Med 43:884–885CrossRefPubMed
13.
Dvorak J, George J, Junge A, Hodler J (2007) Age determination by magnetic resonance imaging of the wrist in adolescent male football players. Br J Sports Med 41:45–52CrossRefPubMed
14.
Dvorak J, George J, Junge A, Hodler J (2007) Application of MRI of the wrist for age determination in international U-17 soccer competitions. Br J Sports Med 41:497–500CrossRefPubMedPubMedCentral
15.
George J, Nagendran J, Azmi K (2012) Comparison study of growth plate fusion using MRI versus plain radiographs as used in age determination for exclusion of overaged football players. Br J Sports Med 46:273–278CrossRefPubMed
16.
Schmidt S, Vieth V, Timme M, Dvorak J, Schmeling A (2015) Examination of ossification of the distal radial epiphysis using magnetic resonance imaging. New insights for age estimation in young footballers in FIFA tournaments. Sci Justice 55:139–144CrossRefPubMed
17.
Tscholl PM, Junge A, Dvorak J, Zubler V (2016) MRI of the wrist is not recommended for age determination in female football players of U-16/U-17 competitions. Scand J Med Sci Sports 26:324–328CrossRefPubMed
18.
Urschler M, Krauskopf A, Widek T et al (2016) Applicability of Greulich-Pyle and Tanner-Whitehouse grading methods to MRI when assessing hand bone age in forensic age estimation: a pilot study. Forensic Sci Int 266:281–288CrossRefPubMed
19.
20.
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 124:321–325CrossRefPubMed
21.
Schmeling A, Schulz R, Reisinger W, Mühler 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 118:5–8CrossRefPubMed
22.
Wittschieber D, Schmidt S, Vieth V et al (2014) Subclassification of clavicular substage 3a is useful for diagnosing the age of 17 years. Rechtsmedizin 24:485–488CrossRef
23.
Ekizoglu O, Hocaoglu E, Inci E, Can IO, Aksoy S, Sayin I (2015) Estimation of forensic age using substages of ossification of the medial clavicle in living individuals. Int J Legal Med 129:1259–1264CrossRefPubMed
24.
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 10:163–169CrossRefPubMed
25.
Thevissen PW, Fieuws S, Willems G (2013) Third molar development: evaluation of nine tooth development registration techniques for age estimations. J Forensic Sci 58:393–397CrossRefPubMed
26.
De Tobel J, Hillewig E, Bogaert S, Deblaere K, Verstraete K (2017) Magnetic resonance imaging of third molars: developing a protocol suitable for forensic age estimation. Ann Hum Biol 44:130–139CrossRefPubMed
27.
De Tobel J, Hillewig E, Verstraete K (2017) Forensic age estimation based on magnetic resonance imaging of third molars: converting 2D staging into 3D staging. Ann Hum Biol 44:121–129CrossRefPubMed
28.
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 21:757–767CrossRefPubMed
29.
Boldsen JL, Milner GR, Konigsberg LW, Wood JW (2002) Transition analysis: a new method for estimating age from skeletons. In: Hoppa RD, Vaupel JW (eds) Paleodemography: Age distributions from skeletal samples. (Cambridge Studies in Biological and Evolutionary Anthropology). Cambridge University Press, Cambridge, pp 73–106CrossRef
30.
Fieuws S, Willems G, Larsen-Tangmose S, Lynnerup N, Boldsen J, Thevissen P (2016) Obtaining appropriate interval estimates for age when multiple indicators are used: evaluation of an ad-hoc procedure. Int J Legal Med 130:489–499CrossRefPubMed
31.
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 124:35–42CrossRefPubMed
32.
Bolívar J, Sandoval Ó, Osorio J, Dib G, Gallo J (2015) Relationship of chronological age and sexual maturity with skeletal maturity by magnetic resonance imaging of the distal radial epiphysis in adolescent football players. Apunts Medicina de l'Esport 50:129–137CrossRef
33.
Sarkodie BD, Botwe BO, Pambo P, Brakohiapa EK, Mayeden RN (2018) MRI age verification of U-17 footballers: the Ghana study. J Forensic Radiol Imaging 12:21–24CrossRef
34.
Wittschieber D, Schulz R, Vieth V et al (2014) Influence of the examiner's qualification and sources of error during stage determination of the medial clavicular epiphysis by means of computed tomography. Int J Legal Med 128:183–191CrossRefPubMed
35.
McGibbon CA, Bencardino J, Palmer WE (2003) Subchondral bone and cartilage thickness from MRI: effects of chemical-shift artifact. MAGMA 16:1–9CrossRefPubMed
36.
37.
38.
Abdelbary MH, Abdelkawi MM, Nasr MA (2018) Age determination by MR imaging of the wrist in Egyptian male football players. How far is it reliable? The Egyptian Journal of Radiology and Nuclear Medicine 49:146–151CrossRef
39.
Serinelli S, Panebianco V, Martino M et al (2015) Accuracy of MRI skeletal age estimation for subjects 12-19. Potential use for subjects of unknown age. Int J Legal Med 129:609–617CrossRefPubMed
40.
Terada Y, Kono S, Tamada D et al (2013) Skeletal age assessment in children using an open compact MRI system. Magn Reson Med 69:1697–1702CrossRefPubMed
41.
Terada Y, Kono S, Uchiumi T et al (2014) Improved reliability in skeletal age assessment using a pediatric hand MR scanner with a 0.3T permanent magnet. Magn Reson Med Sci 13:215–219CrossRefPubMed
42.
Terada Y, Tamada D, Kose K et al (2016) Acceleration of skeletal age MR examination using compressed sensing. J Magn Reson Imaging 44:204–211CrossRefPubMed
43.
Tomei E, Sartori A, Nissman D et al (2014) Value of MRI of the hand and the wrist in evaluation of bone age: preliminary results. J Magn Reson Imaging 39:1198–1205CrossRefPubMed
44.
Jaramillo D, Connolly SA, Mulkern RV, Shapiro F (1998) Developing epiphysis: MR imaging characteristics and histologic correlation in the newborn lamb. Radiology 207:637–645CrossRefPubMed
45.
46.
International Organization for Forensic Odonto-Stomatology (IOFOS) (2018) Recommendations for quality assurance. Dental Age Estimation, Leuven
47.
Greulich W, Pyle SI (1959) Radiographic atlas of skeletal development of the hand and wrist, 2nd edn. Stanford University Press, Stanford
48.
Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227
49.
Aynsley-Green A, Cole T, Crawley H, Lessof N, Boag L, Wallace R (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 102:17–42CrossRefPubMed
50.
Thevissen PW, Kvaal SI, Dierickx K, Willems G (2012) Ethics in age estimation of unaccompanied minors. J Forensic Odontostomatol 30(Suppl 1):84–102PubMed
Metadata
Title
Forensic age estimation based on T1 SE and VIBE wrist MRI: do a one-fits-all staging technique and age estimation model apply?
Authors
Jannick De Tobel
Elke Hillewig
Michiel Bart de Haas
Bram Van Eeckhout
Steffen Fieuws
Patrick Werner Thevissen
Koenraad Luc Verstraete
Publication date
01-06-2019
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 6/2019
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-018-5944-7

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