Top

Published in:

01-07-2014 | Population Data

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

Authors: Pauline Saint-Martin, Camille Rérolle, Fabrice Dedouit, Hervé Rousseau, Daniel Rougé, Norbert Telmon

Published in: International Journal of Legal Medicine | Issue 4/2014

Abstract

The contribution of magnetic resonance imaging to forensic age estimation of living individuals is a subject of ongoing research. Several studies have focused on the wrist, clavicle, knee, and foot, and shown interesting results regarding the 18-year threshold. Authors have developed various staging systems for epiphyseal growth plate maturation. However, the procedure is observer-dependent and requires experience and a certain time-learning process. To reduce these pitfalls, we have developed an automatic method based on the analysis of variations of gray levels within the epiphyseal–metaphyseal junction. This method was tested on 160 MRI scans of the distal tibial epiphysis in a sample of individuals aged from 8 to 25 years old, after intensity non-uniformity correction of all images. Results showed that in our sample, 97.4 % of males and 93.9 % of females aged 18 years or more would be correctly classified using this method. To our knowledge, automatic methods for MRI analysis have not been used in the field of age estimation yet. Further studies should be performed to assess the validity of this procedure.

Cunha E, Baccino E, Martrille L, Ramsthaler F, Prieto J, Schuliar Y, Lynnerup N, Cattaneo C (2009) The problem of aging human remains and living individuals: a review. Forensic Sci Int 193:1–13PubMedCrossRef

Ritz-Timme S, Cattaneo C, Collins MJ, Waite ER, Schütz HW, Kaatsch HJ, Borrman HIM (2000) Age estimation: the state of the art in relation to the specific demands of forensic practice. Int J Legal Med 113:129–136PubMedCrossRef

Schmeling A, Olze A, Reisinger W, Geserick G (2001) Age estimation of living people undergoing criminal proceedings. Lancet 358:89–90PubMedCrossRef

Schmeling A, Olze A, Reisinger W, Geserick G (2004) Forensic age diagnostics of living people undergoing criminal proceedings. Forensic Sci Int 144:243–245PubMedCrossRef

Schmeling A, Geserick G, Reisinger W, Olze A (2007) Age estimation. Forensic Sci Int 165:178–181PubMedCrossRef

Schmeling A, Grundmann C, Fuhrmann A, Kaatsch HJ, Knell B, Ramsthaler F, Reisinger W, Riepert T, Ritz-Timme S, Rösing FW, Rötzsher K, Geserick G (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–460PubMedCrossRef

Quirmbach F, Ramsthaler F, Verhoff MA (2009) Evaluation of the ossification of the medial clavicular epiphysis with a digittal ultrasonic system to determine the age threshold of 21years. Int J Legal Med 123:241–245PubMedCrossRef

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 125:271–276PubMedCrossRef

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 127:831–838PubMedCrossRef

10.

Schmidt S, Mühler M, Schmeling A, Reisinger W, Schulz R (2007) Magnetic resonance imaging of the clavicular ossification. Int J Legal Med 121:321–324PubMedCrossRef

11.

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 21:757–767PubMedCrossRef

12.

Hillewig E, Degroote J, Van der Paelt T, Visscher A, Vandemaele P, Lutin B, D’Hooghe L, Vandriessche V, Piette M, Verstraete K (2013) Magnetic resonance imaging of the sternal extremity of the clavicle in forensic age estimation : towards more sound age estimates. Int J Legal Med 127:677–689PubMedCrossRef

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 41:45–52PubMedCentralPubMedCrossRef

14.

Dvorak J, George J, Junge A, Hodler J (2007) Application of MRI of the wrist for age determination in international U-17 soccer competition. Br J Sports Med 41:497–500PubMedCentralPubMedCrossRef

15.

Dvorak J (2009) Detecting over-age players using wrist MRI: science partnering with sport to ensure fair play. Br J Sports Med 43:884–885PubMedCrossRef

16.

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 46:273–278PubMedCrossRef

17.

Dedouit F, Auriol J, Rousseau H, Rougé D, Crubézy E, Telmon N (2012) Age assessment by magnetic resonance imaging of the knee: a preliminary study. Forensic Sci Int 217:232.e1–232.e7CrossRef

18.

Jopp E, Schröder I, Maas R, Adam G, Püschel K (2010) Proximale tibiaepiphyse im magnetresonanztomogramm. Neue Möglichkeit zur Altersbestimmung bei Lebenden? Rechtsmedizin 20:464–468CrossRef

19.

Saint-Martin P, Rérolle C, Dedouit F, Bouilleau L, Rousseau H, Rougé D, Telmon N (2013) Age estimation by magnetic resonance imaging of the distal tibial epiphysis and the calcaneum. Int J Legal Med 127:1023–1030PubMedCrossRef

20.

Lynnerup N, Belard E, Buch-Olsen K, Sejrsen B, Damgaard-Pedersen K (2008) Intra- and interobserver error of the Greulich–Pyle method as used on a Danish forensic sample. Forensic Sci Int 179:242.e1–242.e6CrossRef

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 118:5–8PubMedCrossRef

22.

Cameriere R, De Luca S, De Angelis D, Merelli V, Giuliodori A, Cingolani M, Cattaneo C, Ferrante L (2012) Reliability of Schmeling’s stages of ossification of medial clavicular epiphyses and its validity to assess 18years of age in living subjects. Int J Legal Med 126:923–932PubMedCrossRef

23.

Bellon EM, Haacke EM, Coleman PE, Sacco DC, Steiger DA, Gangarosa RE (1986) MR Artifacts: a review. Am J Roentgenol 147:1271–1281CrossRef

24.

McKern TW, Stewart TD (1957) Skeletal age changes in young American males analyzed from the standpoint of age determination. Technical Report EP-45. Environmental Protection Research Division, HQ=Quatermaster Research and Development Command, United States Army, Natick, MA

25.

Scheuer L, Black SM (2000) Developmental juvenile osteology. Elsevier/Academic, Amsterdam

26.

Bass W (2005) Human osteology—a laboratory and field manual of the human skeleton. Archaeological Society, Columbia

27.

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 135:161–170PubMedCrossRef

28.

Davies DA, Parsons FG (1927) The age order of the appearance and union of the normal epiphyses as seen by X-rays. J Anat 62:58–71PubMedCentralPubMed

29.

Flecker H (1932) Roentgenographic observations of the times of appearance of epiphyses and their fusions with the diaphyses. J Anat 67:118–164PubMedCentralPubMed

30.

Hoerr NL, Pyle SI, Francis CC (1962) Radiographic atlas of skeletal development of the foot and ankle—a standard of reference. Thomas, Springfield

31.

Ogden JA, McCarthy SM (1983) Radiology of postnatal skeletal development. VIII. Distal tibia and fibula. Skelet Radiol 10:209–220CrossRef

32.

Banerjee KK, Agrawal BB (1998) Estimation of age from epiphyseal union at wrist and ankle joints in the capital city of India. Forensic Sci Int 98:31–39PubMedCrossRef

33.

Crowder C, Austin D (2005) Age ranges of epiphyseal fusion in the distal tibia and fibula of contemporary males and females. J Forensic Sci 50:1001–1007PubMedCrossRef

34.

Belaroussi B, Milles J, Carme S, Zhu YM, Benoit-Cattin H (2006) Intensity non-uniformity correction in MRI: existing methods and their validation. Med Imaging Anal 10:234–246CrossRef

35.

Sled JG, Zijdenbos AP, Evans AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17:87–97PubMedCrossRef

36.

Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC (2010) N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29:1310–1320PubMedCentralPubMedCrossRef

37.

Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward S, Miller JV, Pieper S, Kikinis R (2012) 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 30:1323–1341PubMedCentralPubMedCrossRef

38.

Boyes RG, Gunter JL, Frost C, Janke AL, Yeatman T, Hill DLG, Bernstein MA, Thompson PM, Weiner MW, Schuff N, Alexander GE, Killiany RJ, DeCarli C, Jack CR, Fox NC for the ADNI Study (2008) Intensity non-uniformity correction using N3 on 3-T scanners with multischannel phased array coils. Neuroimage 39:1752–1762PubMedCentralPubMedCrossRef

39.

R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN: 3-9000051-07-0 http://www.R-project.org

40.

Iscan MY (1989) Age markers in the human skeleton. Thomas, Springfield

41.

Brewer JB, Magda S, Airriess C, Smith ME (2009) Fully-automated quantification of regional brain volumes for improved detection of focal atrophy in Alzheimer disease. AJNR Am J Neuroradiol 30:578–580PubMedCrossRef

42.

Chupin M, Gérardin E, Cuingnet R, Boutet C, Lemieux L, Lehéricy S, Benali H, Garnero L, Colliot O, the Alzheimer’s Disease Neuroimaging Initiative (2009) Fully automatic hippocampus segmentation and classification in Alzheimer’s disease and mild cognitive impairment applied on data from ADNI. Hippocampus 19:579–587PubMedCentralPubMedCrossRef

43.

Cuingnet R, Gerardin E, Tessieras J, Auzias G, Lehéricy S, Habert MO, Chupin M, Benali H, Colliot O, The Alzheimer’s Disease Neuroimaging Initiative (2011) Automatic classification of patients with Alzheimer’s disease from structural MRI: a comparison of ten methods using the ADNI database. Neuroimage 56:766–781PubMedCrossRef

44.

Constantinides C, Roullot E, Lefort M, Frouin F (2012) Fully automated segmentation of the left ventricle applied to cine MR images: description and results on a database of 45 subjects. Conf Proc IEEE Eng Med Biol Soc 2012:3207–3210PubMed

Title: 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
Authors: Pauline Saint-Martin
Camille Rérolle
Fabrice Dedouit
Hervé Rousseau
Daniel Rougé
Norbert Telmon
Publication date: 01-07-2014
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Legal Medicine / Issue 4/2014
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-014-0987-z

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 4/2014

Age estimation based on pictures and videos presumably showing child or youth pornography

Developmental variation among Cochliomyia macellaria Fabricius (Diptera: Calliphoridae) populations from three ecoregions of Texas, USA

New reference tables and user-friendly Internet application for predicted heart weights

Erratum to: Modeling one complete versus triplicate analyses in low template DNA typing

Age estimation by quantitative features of pubic symphysis using multidetector computed tomography

Erratum to: Determination of impact parameters and efficiency of 6.8/15 caliber captive bolt guns