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.
Similar content being viewed by others
Abbreviations
- CI:
-
Confidence interval
- END:
-
End stage
- MAE:
-
Mean absolute error
- SAR:
-
Specific absorption rate
- SE:
-
T1-weighted spin echo MR-sequence
- TFS:
-
Threefold stratification sign
- VIBE:
-
T1-weighted gradient echo volumetric interpolated breath-hold examination MR-sequence
References
Schmeling A, Geserick G, Reisinger W, Olze A (2007) Age estimation. Forensic Sci Int 165:178–181
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 35:117–140
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
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 27:5041–5048
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 61–69
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 131:579–584
Schmeling A, Dettmeyer R, Rudolf E, Vieth V, Geserick G (2016) Forensic age estimation. Dtsch Arztebl Int 113:44–50
Thevissen PW (2013) Dental age estimation in sub-adults: striving for an optimal approach. Leuven University Press, Leuven
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
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 42:358–367
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 130:1121–1128
Dvorak J (2009) Detecting over-age players using wrist MRI: science partnering with sport to ensure fair play. Br J Sports Med 43:884–885
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 41:45–52
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 41:497–500
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 46:273–278
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 55:139–144
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 26:324–328
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 266:281–288
Hojreh A, Gamper J, Schmook MT et al (2018) Hand MRI and the Greulich-Pyle atlas in skeletal age estimation in adolescents. Skelet Radiol 47:963–971. https://doi.org/10.1007/s00256-017-2867-3
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
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 118:5–8
Wittschieber D, Schmidt S, Vieth V et al (2014) Subclassification of clavicular substage 3a is useful for diagnosing the age of 17 years. Rechtsmedizin 24:485–488
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 129:1259–1264
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
Thevissen PW, Fieuws S, Willems G (2013) Third molar development: evaluation of nine tooth development registration techniques for age estimations. J Forensic Sci 58:393–397
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 44:130–139
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 44:121–129
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
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 73–106
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 130:489–499
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 124:35–42
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 50:129–137
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 12:21–24
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 128:183–191
McGibbon CA, Bencardino J, Palmer WE (2003) Subchondral bone and cartilage thickness from MRI: effects of chemical-shift artifact. MAGMA 16:1–9
De Tobel J, Parmentier GIL, Phlypo I et al (2018) Magnetic resonance imaging of third molars in forensic age estimation: comparison of the Ghent and Graz protocols focusing on apical closure. Int J Legal Med. https://doi.org/10.1007/s00414-018-1905-6
Vieth V, Schulz R, Heindel W et al (2018) Forensic age assessment by 3.0T MRI of the knee: proposal of a new MRI classification of ossification stages. Eur Radiol 28:3255–3262. https://doi.org/10.1007/s00330-017-5281-2
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 49:146–151
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 129:609–617
Terada Y, Kono S, Tamada D et al (2013) Skeletal age assessment in children using an open compact MRI system. Magn Reson Med 69:1697–1702
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 13:215–219
Terada Y, Tamada D, Kose K et al (2016) Acceleration of skeletal age MR examination using compressed sensing. J Magn Reson Imaging 44:204–211
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 39:1198–1205
Jaramillo D, Connolly SA, Mulkern RV, Shapiro F (1998) Developing epiphysis: MR imaging characteristics and histologic correlation in the newborn lamb. Radiology 207:637–645
Bleka Ø, Wisloff T, Dahlberg PS, Rolseth V, Egeland T (2018) Advancing estimation of chronological age by utilizing available evidence based on two radiographical methods. Int J Legal Med. https://doi.org/10.1007/s00414-018-1848-y
International Organization for Forensic Odonto-Stomatology (IOFOS) (2018) Recommendations for quality assurance. Dental Age Estimation, Leuven
Greulich W, Pyle SI (1959) Radiographic atlas of skeletal development of the hand and wrist, 2nd edn. Stanford University Press, Stanford
Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227
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 102:17–42
Thevissen PW, Kvaal SI, Dierickx K, Willems G (2012) Ethics in age estimation of unaccompanied minors. J Forensic Odontostomatol 30(Suppl 1):84–102
Acknowledgements
The authors wish to express their gratitude to all participants and everyone who helped with the recruitment. We thank Maarten Peleman and Dries Ovaere for installing the viewing software on the department’s computers. Finally, we wish to acknowledge Inès Phlypo for her indispensable critical appraisal of the manuscript.
Results described in this manuscript were presented at the 20th Meeting of the Study Group on Forensic Age Diagnostics (Arbeitsgemeinschaft für Forensische Altersdiagnostik, AGFAD) in Berlin, Germany, on March 17, 2017.
Funding
Funding for this research was entirely provided by the Department of Radiology and Nuclear Medicine at Ghent University and the Department of Imaging and Pathology - Forensic Odontology at KU Leuven.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Guarantor
The scientific guarantor of this publication is Koenraad Verstraete, Ghent University.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
One of the authors has significant statistical expertise.
Informed consent
Written informed consent was obtained from all participants in this study. In case of minors, written informed consent was also obtained from the parents.
Ethical approval
The study was approved by the Ghent University Hospital Ethics Committee.
Study subjects or cohorts overlap
Parts of the study population have been previously reported in [2, 3, 26,27,28, 36]. In those studies, the development of their clavicles and third molars was studied for age estimation.
Methodology
• prospective
• cross sectional study/observational
• performed at one institution
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 392 kb)
Rights and permissions
About this article
Cite this article
De Tobel, J., Hillewig, E., de Haas, M.B. et al. Forensic age estimation based on T1 SE and VIBE wrist MRI: do a one-fits-all staging technique and age estimation model apply?. Eur Radiol 29, 2924–2935 (2019). https://doi.org/10.1007/s00330-018-5944-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00330-018-5944-7