Estimation of ancestry from cranial measurements based on MDCT data acquired in a Japanese and Western Australian population.
Ancestry assessment
Forensic anthropology
Japanese
Multidetector computed tomography
Skull
Western Australian
Journal
International journal of legal medicine
ISSN: 1437-1596
Titre abrégé: Int J Legal Med
Pays: Germany
ID NLM: 9101456
Informations de publication
Date de publication:
22 Jan 2024
22 Jan 2024
Historique:
received:
19
10
2023
accepted:
08
01
2024
medline:
22
1
2024
pubmed:
22
1
2024
entrez:
22
1
2024
Statut:
aheadofprint
Résumé
The estimation of ancestry is important not only towards establishing identity but also as a required precursor to facilitating the accurate estimation of other attributes such as sex, age at death, and stature. The present study aims to analyze morphological variation in the crania of Japanese and Western Australian individuals and test predictive models based on machine learning for their potential forensic application. The Japanese and Western Australian samples comprise computed tomography (CT) scans of 230 (111 female; 119 male) and 225 adult individuals (112 female; 113 male), respectively. A total of 18 measurements were calculated, and machine learning methods (random forest modeling, RFM; support vector machine, SVM) were used to classify ancestry. The two-way unisex model achieved an overall accuracy of 93.2% for RFM and 97.1% for SVM, respectively. The four-way sex and ancestry model demonstrated an overall classification accuracy of 84.0% for RFM and 93.0% for SVM. The sex-specific models were most accurate in the female samples (♀ 95.1% for RFM and 100% for SVM; ♂91.4% for RFM and 97.4% for SVM). Our findings suggest that cranial measurements acquired in CT images can be used to accurately classify Japanese and Western Australian individuals into their respective population. This is the first study to assess the feasibility of ancestry estimation using three-dimensional CT images of the skull.
Identifiants
pubmed: 38252284
doi: 10.1007/s00414-024-03159-6
pii: 10.1007/s00414-024-03159-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Balseven-Odabasi A, Yalcinozan E, Keten A et al (2013) Age and sex estimation by metric measurements and fusion of hyoid bone in a Turkish population. J Forensic Leg Med 20:496–501. https://doi.org/10.1016/j.jflm.2013.03.022
doi: 10.1016/j.jflm.2013.03.022
pubmed: 23756521
Ousley S, Jantz R, Freid D (2009) Understanding race and human variation: why are forensic anthropologists are good at identifying race. Am J Phys Anthropol 139:68–76. https://doi.org/10.1002/ajpa.21006
doi: 10.1002/ajpa.21006
pubmed: 19226647
Cunha E, Ubelaker DH (2020) Evaluation of ancestry from human skeletal remains: a concise review. Forensic Sci Res 5:89–97. https://doi.org/10.1080/20961790.2019.1697060
doi: 10.1080/20961790.2019.1697060
pubmed: 32939424
Byers S (2011) Introduction to Forensic Anthropology, 4th edn. Routledge, Boston
Cunha E, Ortega PA (2016) Como los antrop ologos fore-nses evaluan la ancestr ıa? In: Sanabria MC (ed) Patologıa y Antropologıa Forense de la Muerte–La Investigacion Cientıfico Judicial de la Muerte Yla Tortura, desde las Fosas Clandestinas Hasta Laudiencia Publica. Forensic Publisher, Bogot a (Colombia), pp 221–235 Spanish
Ousley SD, Jantz RL (2005) FORDISC 3.1: Personal computer forensic discriminant functions. Universty of Tennesse
Ousley SD, Jantz RL (2012) ForDisc 3 and statistical methods for sex and ancestry estimation. In: Dirkmaat DC (ed) A companion to forensic anthropology, 1st edn. Wiley-Blackwell, West Sussex, UK, pp 311–329
doi: 10.1002/9781118255377.ch15
Wright RVS (1992) Correlation between cranial form and geography in homo sapiens: CRANID—a computer program for forensic and other applications. Archaeol Ocean 27:128–134. https://doi.org/10.1002/j.1834-4453.1992.tb00296.x
doi: 10.1002/j.1834-4453.1992.tb00296.x
Wright R (2008) Detection of likely ancestry using CRANID. In: Oxenham M (ed) Forensic approaches death, disaster and abuse. Australian Academic Press, Sydney, pp 111–122
Navega D, Coelho C, Vicente R et al (2015) AncesTrees: ancestry estimation with randomized decision trees. Int J Legal Med 129:1145–1153. https://doi.org/10.1007/s00414-014-1050-9
doi: 10.1007/s00414-014-1050-9
pubmed: 25053239
Hefner JT, Spradley MK, Anderson B (2014) Ancestry assessment using random forest modeling. J Forensic Sci 59:583–589. https://doi.org/10.1111/1556-4029.12402
doi: 10.1111/1556-4029.12402
pubmed: 24502438
Dudzik B, Jantz RL (2016) Misclassifications of hispanics using fordisc 3.1: comparing cranial morphology in Asian and hispanic populations. J Forensic Sci 61:1311–1318
doi: 10.1111/1556-4029.13123
pubmed: 27427086
Thali MJ, Braun M, Buck U et al (2005) VIRTOPSY–scientific documentation, reconstruction and animation in forensic: individual and real 3D data based geo-metric approach including optical body/object surface and radiological CT/MRI scanning. J Forensic Sci 50:428–442. https://doi.org/10.1520/JFS2004290
doi: 10.1520/JFS2004290
pubmed: 15813556
Dedouit F, Telmon N, Costagliola R et al (2007) Virtual anthropology and forensic identification: report of one case. Forensic Sci Int 173:182–187. https://doi.org/10.1016/j.forsciint.2007.01.002
doi: 10.1016/j.forsciint.2007.01.002
pubmed: 17289318
Ramsthaler F, Kettner M, Gehl A et al (2010) Digital forensic osteology: morphological sexing of skeletal remains using volume-rendered cranial CT scans. Forensic Sci Int 195:148–152. https://doi.org/10.1016/j.forsciint.2009.12.010
doi: 10.1016/j.forsciint.2009.12.010
pubmed: 20074879
Robinson C, Eisma R, Morgan B et al (2008) Anthropological measurement of lower limb and foot bones using multi-detector computed tomography. J Forensic Sci 53:1289–1295. https://doi.org/10.1111/j.1556-4029.2008.00875.x
doi: 10.1111/j.1556-4029.2008.00875.x
pubmed: 18798776
Torimitsu S, Makino Y, Saitoh H et al (2015) Estimation of sex in Japanese cadavers based on sternal measurements using multidetector computed tomography. Leg Med (Tokyo) 17:226–231. https://doi.org/10.1016/j.legalmed.2015.01.003
doi: 10.1016/j.legalmed.2015.01.003
pubmed: 25684712
Franklin D, Cardini A, Flavel A et al (2012) The application of traditional and geometric morphometric analyses for forensic quantification of sexual dimorphism: preliminary investigations in a Western Australian population. Int J Legal Med 126:549–558. https://doi.org/10.1007/s00414-012-0684-8
doi: 10.1007/s00414-012-0684-8
pubmed: 22399102
Franklin D, Cardini A, Flavel A et al (2013) Estimation of sex from cranial measurements in a western Australian population. Forensic Sci Int 229:158.e1–158.e8. https://doi.org/10.1016/j.forsciint.2013.03.005
doi: 10.1016/j.forsciint.2013.03.005
pubmed: 23537716
Franklin D, Freedman L, Milne N et al (2006) A geometric morphometric study of sexual dimorphism in the crania of indigenous southern Africans. S Afr J Sci 102:229–238
Bass WM (2005) Human osteology: a laboratory and field manual, 5th edn. University of Columbia, Missouri
Howells W (1989) Skull shapes and the map: craniometric analyses in the dispersion of modern homo. Peabody Museum of Archaeology and Ethnology, Cambridge, Harvard University Press, Cambridge
de Villiers H (1968) The skull of South African Negro: a biometrical and morphological study. Witswatersrand University Press, Witswatersrand
Howells W (1973) Cranial variation in man. A study by muiltivariate analysis of patterns of difference, among recent human populations. Pap Peabody Museum Archaeol Ethnol 67:1–259
Langley NR, Jantz LM, Ousley SD et al (2016) Data collection procedures for forensic skeletal material 2.0.2. Tennesse Forensic Anthropology Center Department of Anthropology the University of Tennessee, Knoxville
Goto R, Mascie-Taylor CG (2007) Precision of measurement as a component of human variation. J Physiol Anthropol 26:253–256. https://doi.org/10.2114/jpa2.26.253
doi: 10.2114/jpa2.26.253
pubmed: 17435374
Franklin D, Cardini A, Flavel A et al (2013) Concordance of traditional osteometric and volume-rendered MSCT interlandmark cranial measurements. Int J Legal Med 127:505–520. https://doi.org/10.1007/s00414-012-0772-9
doi: 10.1007/s00414-012-0772-9
pubmed: 23052442
Ulijaszek SJ, Kerr DA (1999) Anthropometric measurement error and the assessment of nutritional status. Br J Nutr 82:165–177. https://doi.org/10.1017/S0007114599001348
doi: 10.1017/S0007114599001348
pubmed: 10655963
Weinberg SM, Scott NM, Neiswanger K, Marazita ML (2005) Intraobserver error associated with measurements of the hand. Am J Hum Biol 17:368–371. https://doi.org/10.1002/ajhb.20129
doi: 10.1002/ajhb.20129
pubmed: 15849702
Breiman L (2001) Random forests. Mach Learn 45:5–32. https://doi.org/10.1023/A:1010933404324
doi: 10.1023/A:1010933404324
Dietterich TG (2000) An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Mach Learn 40:139–157. https://doi.org/10.1023/A:1007607513941
doi: 10.1023/A:1007607513941
Dietterich TG (2000) Ensemble methods in machine learning. International workshop on multiple classifier systems. Springer, Berlin Heidelberg, Berlin, pp 1–15
Breiman L (1994) Bagging predictors: technical report 42. University of California, Berkley
Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference, and prediction, 2nd edn. Springer, Berlin
doi: 10.1007/978-0-387-84858-7
Spiros MC, Hefner JT (2020) Ancestry estimation using cranial and postcranial macromorphoscopic traits. J Forensic Sci 65:921–929
doi: 10.1111/1556-4029.14231
pubmed: 31725188
Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20:273–297. https://doi.org/10.1007/BF00994018
doi: 10.1007/BF00994018
Liaw A, Wiener M (2002) Classification and regression by random forest. R News 2(3):18–22
Meyer D, Dimitriadou E, Hornik K et al (2015) Package “e1071”: Misc functions of the department of statistics, probability theory group (formerly: E1071), TU Wien. R package version 1.6–7. https://CRAN.R-project.org/package=e1071 . https://cran.r-project.org/web/packages/e1071/e1071.pdf . Accessed 14 October 2019.
Swift L, Flavel A, Franklin D (2019) A preliminary investigation of cranial sexual dimorphism in a Northern Territory population. Aust J Forensic Sci 51:S184–S187. https://doi.org/10.1080/00450618.2019.1569721
doi: 10.1080/00450618.2019.1569721
Ubelaker DH, DeGaglia CM (2017) Population variation in skeletal sexual dimorphism. Forensic Sci Int 278:407.e1–407.e7. https://doi.org/10.1016/j.forsciint.2017.06.012
doi: 10.1016/j.forsciint.2017.06.012
pubmed: 28698063
Liebenberg L, Krüger GC, L’Abbé EN et al (2019) Postcraniometric sex and ancestry estimation in South Africa: a validation study. Int J Legal Med 133:289–296
doi: 10.1007/s00414-018-1865-x
pubmed: 29797281
Ogawa Y, Imaizumi K, Miyasaka S et al (2013) Discriminant functions for sex estimation of modern Japanese skulls. J Forensic Leg Med 20:234–238. https://doi.org/10.1016/j.jflm.2012.09.023
doi: 10.1016/j.jflm.2012.09.023
pubmed: 23622466
İşcan MY, Yoshino M, Kato S (1995) Sexual dimorphism in modern Japanese crania. Am J Hum Biol 7:459–464. https://doi.org/10.1002/ajhb.1310070407
doi: 10.1002/ajhb.1310070407
pubmed: 28557089
Franklin D, Flavel A (2019) Population specificity in the estimation of skeletal age and sex: case studies using a Western Australian population. Aust J Forensic Sci 51:S188–S192. https://doi.org/10.1080/00450618.2019.1569722
doi: 10.1080/00450618.2019.1569722
Vance VL, Steyn M, L’Abbé EN et al (2010) A cross-sectional analysis of age related changes in the osteometric dimensions of long bones in modern South Africans of European and African descent. Forensic Sci Int 199:110.e1–110.e9. https://doi.org/10.1016/j.forsciint.2010.02.036
doi: 10.1016/j.forsciint.2010.02.036
pubmed: 20338703
Albert AM, Ricanek K Jr, Patterson E (2007) A review of the literature on the aging adult skull and face: implications for forensic science research and applications. Forensic Sci Int 172:1–9. https://doi.org/10.1016/j.forsciint.2007.03.015
doi: 10.1016/j.forsciint.2007.03.015
pubmed: 17434276
Hefner JT, Ousley SD (2014) Statistical classification methods for estimating ancestry using morphoscopic traits. J Forensic Sci 59:883–890
doi: 10.1111/1556-4029.12421
pubmed: 24646108
Du Jardin P, Ponsaillé J, Alunni-Perret V et al (2009) A comparison between neural network and other metric methods to determine sex from the upper femur in a modern French population. Forensic Sci Int 192:127.e1–127.e6. https://doi.org/10.1016/j.forsciint.2009.07.014
doi: 10.1016/j.forsciint.2009.07.014
pubmed: 19733989
Mahfouz M, Badawi A, Merkl B et al (2007) Patella sex determination by 3D statistical shape models and nonlinear classifiers. Forensic Sci Int 173:161–170. https://doi.org/10.1016/j.forsciint.2007.02.024
doi: 10.1016/j.forsciint.2007.02.024
pubmed: 17482786
Moss GP, Shah AJ, Adams RG et al (2012) The application of discriminant analysis and machine learning methods as tools to identify and classify compounds with potential as transdermal enhancers. Eur J Pharm Sci 45:116–127. https://doi.org/10.1016/j.ejps.2011.10.027
doi: 10.1016/j.ejps.2011.10.027
pubmed: 22101136
Nikita E, Nikitas P (2020) On the use of machine learning algorithms in forensic anthropology. Leg Med (Tokyo) 47:101771. https://doi.org/10.1016/j.legalmed.2020.101771
doi: 10.1016/j.legalmed.2020.101771
pubmed: 32795933
Liebenberg L, Stull KE, L'Abbé EN, Botha D (2015) Evaluating the accuracy of cranial indices in ancestry estimation among South African groups. J Forensic Sci 60:1277–1282. https://doi.org/10.1111/1556-4029.12770
doi: 10.1111/1556-4029.12770
pubmed: 25772025
Torimitsu S, Makino Y, Saitoh H et al (2018) Determination of sex on the basis of hyoid bone measurements in a Japanese population using multidetector computed tomography. Int J Legal Med 132:907–914. https://doi.org/10.1007/s00414-017-1728-x
doi: 10.1007/s00414-017-1728-x
pubmed: 29098386
Torimitsu S, Makino Y, Saitoh H et al (2017) Stature estimation in a contemporary Japanese population based on clavicular measurements using multidetector computed tomography. Forensic Sci Int 275:316.e1–316.e6. https://doi.org/10.1016/j.forsciint.2017.02.037
doi: 10.1016/j.forsciint.2017.02.037
pubmed: 28343812
Torimitsu S, Makino Y, Saitoh H et al (2015) Stature estimation in Japanese cadavers based on scapular measurements using multidetector computed tomography. Int J Legal Med 129:211–218. https://doi.org/10.1007/s00414-014-1054-5
doi: 10.1007/s00414-014-1054-5
pubmed: 25064735
Chiba F, Inokuchi G, Hoshioka Y et al (2022) Age estimation by evaluation of osteophytes in thoracic and lumbar vertebrae using postmortem CT images in a modern Japanese population. Int J Legal Med 136:261–267. https://doi.org/10.1007/s00414-021-02714-9
doi: 10.1007/s00414-021-02714-9
pubmed: 34642821
Kobayashi S, Makino Y, Torimitsu S et al (2023) Age estimation by evaluating median palatine suture closure using postmortem CT. Int J Legal Med 137:1097–1107. https://doi.org/10.1007/s00414-023-02994-3
doi: 10.1007/s00414-023-02994-3
pubmed: 37074412
Williams FL, Belcher RL, Armelagos GJ (2005) Forensic misclassification of ancient Nubian crania: implications for assumptions about human variation. Curr Anthropol 46:340–346. https://doi.org/10.1086/428792
doi: 10.1086/428792
Stull KE, Kenyhercz MW, L’Abbé EN (2014) Ancestry estimation in South Africa using craniometrics and geometric morphometrics. Forensic Sci Int 245:206.e1–206.e7
doi: 10.1016/j.forsciint.2014.10.021
pubmed: 25459274
Spradley MK, Jantz RL (2016) Ancestry estimation in forensic anthropology: geometric morphometric versus standard and nonstandard interlandmark distances. J Forensic Sci 61(4):892–897. https://doi.org/10.1111/1556-4029.13081
doi: 10.1111/1556-4029.13081