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Yedinci Servikal Vertebra'ya Ait Bilgisayarlı Tomografi Görüntülerinden Elde Edilen Parametrelerle Geometrik Morfometri Kullanılarak Cinsiyet Tahmini

Yıl 2025, Cilt: 22 Sayı: 4

Öz

Amaç: Vertebraların dayanıklılığı, adli durumlarda veya doğal afetlerde bulunma olasılıklarını artırır. Bu yapılar üzerinden de kimlik tayini işlemleri kolaylaştırılabilir. Kurulan bu hipotez ile yola çıkılan bu çalışmada amaç, 7. servikal vertebra üzerinde belirlenen noktalara geometrik morfometri yöntemi kullanılarak yüksek doğrulukta ve güvenilirlikte cinsiyet tayininin mümkün olup olmadığını ortaya koymaktır.
Materyal ve metod: Çalışma 18-65 yaş aralığındaki 300 bireye ait bilgisayarlı tomografi görüntüleri kullanılarak gerçekleştirildi. Görüntüler üç boyutlu hale getirilerek üst üste çakıştırma işlemi uygulandı. Daha sonra gerçek büyütmedeki görüntüler TPS formatına çevrilerek 30 landmark eklendi. Oluşan bu ham koordinatlara Generalized Procrusters Analysis (GPA) analizi uygulanıp ağırlık merkezi etrafında koordinatlar yeniden konumlandırıldı. Yeniden konumlandırılan bu verilere de Principal Component Analysis uygulanıp boyutsallık azaltıldı. Boyutsallığı azaltılan görüntülere de Lineer diskriminant analizi (LDA) uygulanıp cinsiyet tahmini doğruluk oranı elde edildi.
Bulgular: Çalışma sonucunda ağırlık merkezi etrafında toplanan koordinatların %63,674’ünün ilk 6 principal component tarafından açıklanabileceği bulundu. Yeni koordinatlara uygulanan LDA analizi ile de %83,33 cinsiyet tahmin oranı elde edildi.
Sonuç: Çalışma sonucunda 7. servikal vertebra üzerinde belirlenen noktalara geometrik morfometri yöntemi uygulanarak cinsiyet tahmini açısından yüksek bir doğruluk oranı elde edildi.

Kaynakça

  • 1. Zelditch M, Swiderski D, Sheets HD. Geometric morphometrics for biologists: a primer. Academic Press; 2012.
  • 2. Kimmerle E, Ross A, Slice D. Sexual dimorphism in America: geometric morphometric analysis of the craniofacial region. J Forensic Sci. 2008;53(1):54-57.
  • 3. Szara T, Duro S, Gündemir O, Demircioğlu İ. Sex determination in Japanese Quails (Coturnix japonica) using geometric morphometrics of the skull. Animals (Basel). 2022;12(3):302.
  • 4. Mitteroecker P, Gunz P. Advances in geometric morphometrics. Evol Biol. 2009;36(2):235-247.
  • 5. Bigoni L, Velemínská J, Brůžek J. Three-dimensional geometric morphometric analysis of cranio-facial sexual dimorphism in a Central European sample of known sex. Homo. 2010;61(1):16-32.
  • 6. Demircioğlu İ, Demiraslan Y, Gürbüz İ, Dayan M. Geometric morphometric analysis of skull and mandible in Awassi ewe and ram. Kafkas Univ Vet Fak Derg. 2021;27(1):15-22.
  • 7. Slice D. Geometric morphometrics. Annu Rev Anthropol. 2007;36:261-281.
  • 8. Adams D, Rohlf F, Slice D. Geometric morphometrics: ten years of progress following the ‘revolution’. Ital J Zool. 2004;71(1):5-16.
  • 9. Okumura M, Araujo A. Archaeology, biology, and borrowing: A critical examination of Geometric Morphometrics in Archaeology. J Archaeol Sci. 2019;101:149-158.
  • 10. Erkartal H, Tatlı M, Secgin Y, Toy S, Duman B, Hekim B. Gender estimation with parameters obtained from the upper dental arcade by using machine learning algorithms and artificial neural networks. Eur J Ther. 2023;29(3):352-358.
  • 11. Oner Z, Turan M, Oner S, Secgin Y, Sahin B. Sex estimation using sternum part lenghts by means of artificial neural networks. Forensic Sci Int. 2019;301:6-11.
  • 12. Turan M, Oner Z, Secgin Y, Oner S. A trial on artificial neural networks in predicting sex through bone length measurements on the first and fifth phalanges and metatarsals. Comput Biol Med. 2019;115:103490.
  • 13. Gillet C, Costa-Mendes L, Rérolle C, Telmon N, Maret D, Savall F, et al. Sex estimation in the cranium and mandible: a multislice computed tomography (MSCT) study using anthropometric and geometric morphometry methods. Int J Legal Med. 2020;134(3):823-832.
  • 14. Alcina M, Rissech C, Clavero A, Turbón D. Sexual dimorphism of the clavicle in a modern Spanish sample. Eur J Anat. 2015;19(1):73-83.
  • 15. Kantarcı M, Aydın S, Oğul H, Kızılgöz V. New imaging techniques and trends in radiology. Diagn Interv Radiol. 2025;31(4):341-342.
  • 16. Christensen A, Smith M, Gleiber D, Cunningham D, Wescott D. The use of X-ray computed tomography technologies in forensic anthropology. Forensic Anthropol.
  • 17. Scherf H. Computed tomography in paleoanthropology—an overview. Archaeol Anthropol Sci. 2013;5(3):205-214.
  • 18. Djorojevic M, Roldán C, García-Parra P, Alemán I, Botella M. Morphometric sex estimation from 3D computed tomography os coxae model and its validation in skeletal remains. Int J Legal Med. 2014;128(5):879-888.
  • 19. Corner B, Lele S, Richtsmeier J. Measuring precision of three-dimensional landmark data. J Quant Anthropol. 1992;3(4):347-359.
  • 20. Forsberg A, Kullberg J, Agartz I, Ahlström H, Johansson L, Henriksson K. Landmark‐based software for anatomical measurements: A precision study. Clin Anat. 2009;22(4):456-462.
  • 21. Vannier M, Brunsden B, Hildebolt C, Falk D, Cheverud J, Figiel G, et al. Brain surface cortical sulcal lengths: quantification with three-dimensional MR imaging. Radiology. 1991;180(2):479-484.
  • 22. Ross A, Slice D, Williams S. Geometric morphometric tools for the classification of human skulls. Department of Justice; 2010. Document 231195.
  • 23. Secgin Y, Erkartal H, Tatlı M, Toy S, Oner Z, Oner S. Determination of Sex Differences Using Machine Learning Algorithms and Artificial Neural Networks with Parameters Obtained from Basilar Artery. Int J Morphol. 2024;42(5):1295-1300.
  • 24. Secgin Y, Toy S, Cakmak M, Oner Z, Ciftci R, Oner S. Gender Prediction from Direct Pelvic Radiographs Using Efficientnet Deep Learning Model. 2024. Available at SSRN 4995313.
  • 25. Seçgin Y, Öner Z, Öner S, Toy Ş. Gender prediction using geometric morphometry with parameters of the cranium obtained from computed tomography images. Cukurova Med J. 2024;49(3):769-778.
  • 26. Secgin Y, Oner Z, Turan M, Oner S. Gender prediction with the parameters obtained from pelvis computed tomography images and machine learning algorithms. J Anat Soc India. 2022;71(3):204-209.
  • 27. Gama I, Navega D, Cunha E. Sex estimation using the second cervical vertebra: a morphometric analysis in a documented Portuguese skeletal sample. Int J Legal Med. 2015;129(2):365-372.
  • 28. Franklin D, O’Higgins P, Oxnard C, Dadour I. Sexual dimorphism and population variation in the adult mandible: forensic applications of geometric morphometrics. Forensic Sci Med Pathol. 2007;3(1):15-22.
  • 29. Fauad M, Alias A, Noor K, Choy K, Ng W, Chung E, et al. Sexual dimorphism from third cervical vertebra (C3) on lateral cervical radiograph: A 2-dimensional geometric morphometric approach. Forensic Imaging. 2021;24:200441.
  • 30. Rozendaal A, Scott S, Peckmann T, Meek S. Estimating sex from the seven cervical vertebrae: an analysis of two European skeletal populations. Forensic Sci Int. 2020;306:110072.
  • 31. Kaeswaren Y, Hackman L. Sexual dimorphism in the cervical vertebrae and its potential for sex estimation of human skeletal remains in a white scottish population. Forensic Sci Int Rep. 2019;1:100023.
  • 32. Ekizoglu O, Hocaoglu E, Inci E, Karaman G, Garcia-Donas J, Kranioti E, et al. Virtual morphometric method using seven cervical vertebrae for sex estimation on the Turkish population. Int J Legal Med. 2021;135(5):1953-1964.

Sex Prediction Using Geometric Morphometry with Parameters Obtained From Computed Tomography Images of the Seventh Cervical Vertebra

Yıl 2025, Cilt: 22 Sayı: 4

Öz

Background: The durability of vertebrae increases their likelihood of being discovered in forensic contexts or natural disasters. Identification procedures can also be facilitated through these structures. The aim of this study, based on this hypothesis, is to determine whether it is possible to identify gender with high accuracy and reliability using geometric morphometry on specific points identified on the 7th cervical vertebra.
Materials and Methods: The study was conducted using computed tomography images from 300 individuals aged 18-65. The images were converted into three dimensions and superimposed. The images at actual magnification were then converted to TPS format and 30 landmarks were added. Generalized Procrustes Analysis was applied to these raw coordinates, and the coordinates were repositioned around the center of gravity. Principal Component Analysis was then applied to these repositioned data to reduce dimensionality. Linear discriminant analysis (LDA) was applied to the reduced-dimensionality images to obtain the gender prediction accuracy rate.
Results: The study found that 63.674% of the coordinates clustered around the center of gravity could be explained by the first 6 principal components. LDA analysis applied to the new coordinates yielded an 83.33% gender prediction rate.
Conclusions: The study achieved a high accuracy rate for gender prediction by applying geometric morphometry to points identified on the 7th cervical vertebra.

Etik Beyan

This study was approved by the Karabük University Non-Interventional Local Ethics Committee (approval no: 2025/2235, date: April 16, 2025).

Kaynakça

  • 1. Zelditch M, Swiderski D, Sheets HD. Geometric morphometrics for biologists: a primer. Academic Press; 2012.
  • 2. Kimmerle E, Ross A, Slice D. Sexual dimorphism in America: geometric morphometric analysis of the craniofacial region. J Forensic Sci. 2008;53(1):54-57.
  • 3. Szara T, Duro S, Gündemir O, Demircioğlu İ. Sex determination in Japanese Quails (Coturnix japonica) using geometric morphometrics of the skull. Animals (Basel). 2022;12(3):302.
  • 4. Mitteroecker P, Gunz P. Advances in geometric morphometrics. Evol Biol. 2009;36(2):235-247.
  • 5. Bigoni L, Velemínská J, Brůžek J. Three-dimensional geometric morphometric analysis of cranio-facial sexual dimorphism in a Central European sample of known sex. Homo. 2010;61(1):16-32.
  • 6. Demircioğlu İ, Demiraslan Y, Gürbüz İ, Dayan M. Geometric morphometric analysis of skull and mandible in Awassi ewe and ram. Kafkas Univ Vet Fak Derg. 2021;27(1):15-22.
  • 7. Slice D. Geometric morphometrics. Annu Rev Anthropol. 2007;36:261-281.
  • 8. Adams D, Rohlf F, Slice D. Geometric morphometrics: ten years of progress following the ‘revolution’. Ital J Zool. 2004;71(1):5-16.
  • 9. Okumura M, Araujo A. Archaeology, biology, and borrowing: A critical examination of Geometric Morphometrics in Archaeology. J Archaeol Sci. 2019;101:149-158.
  • 10. Erkartal H, Tatlı M, Secgin Y, Toy S, Duman B, Hekim B. Gender estimation with parameters obtained from the upper dental arcade by using machine learning algorithms and artificial neural networks. Eur J Ther. 2023;29(3):352-358.
  • 11. Oner Z, Turan M, Oner S, Secgin Y, Sahin B. Sex estimation using sternum part lenghts by means of artificial neural networks. Forensic Sci Int. 2019;301:6-11.
  • 12. Turan M, Oner Z, Secgin Y, Oner S. A trial on artificial neural networks in predicting sex through bone length measurements on the first and fifth phalanges and metatarsals. Comput Biol Med. 2019;115:103490.
  • 13. Gillet C, Costa-Mendes L, Rérolle C, Telmon N, Maret D, Savall F, et al. Sex estimation in the cranium and mandible: a multislice computed tomography (MSCT) study using anthropometric and geometric morphometry methods. Int J Legal Med. 2020;134(3):823-832.
  • 14. Alcina M, Rissech C, Clavero A, Turbón D. Sexual dimorphism of the clavicle in a modern Spanish sample. Eur J Anat. 2015;19(1):73-83.
  • 15. Kantarcı M, Aydın S, Oğul H, Kızılgöz V. New imaging techniques and trends in radiology. Diagn Interv Radiol. 2025;31(4):341-342.
  • 16. Christensen A, Smith M, Gleiber D, Cunningham D, Wescott D. The use of X-ray computed tomography technologies in forensic anthropology. Forensic Anthropol.
  • 17. Scherf H. Computed tomography in paleoanthropology—an overview. Archaeol Anthropol Sci. 2013;5(3):205-214.
  • 18. Djorojevic M, Roldán C, García-Parra P, Alemán I, Botella M. Morphometric sex estimation from 3D computed tomography os coxae model and its validation in skeletal remains. Int J Legal Med. 2014;128(5):879-888.
  • 19. Corner B, Lele S, Richtsmeier J. Measuring precision of three-dimensional landmark data. J Quant Anthropol. 1992;3(4):347-359.
  • 20. Forsberg A, Kullberg J, Agartz I, Ahlström H, Johansson L, Henriksson K. Landmark‐based software for anatomical measurements: A precision study. Clin Anat. 2009;22(4):456-462.
  • 21. Vannier M, Brunsden B, Hildebolt C, Falk D, Cheverud J, Figiel G, et al. Brain surface cortical sulcal lengths: quantification with three-dimensional MR imaging. Radiology. 1991;180(2):479-484.
  • 22. Ross A, Slice D, Williams S. Geometric morphometric tools for the classification of human skulls. Department of Justice; 2010. Document 231195.
  • 23. Secgin Y, Erkartal H, Tatlı M, Toy S, Oner Z, Oner S. Determination of Sex Differences Using Machine Learning Algorithms and Artificial Neural Networks with Parameters Obtained from Basilar Artery. Int J Morphol. 2024;42(5):1295-1300.
  • 24. Secgin Y, Toy S, Cakmak M, Oner Z, Ciftci R, Oner S. Gender Prediction from Direct Pelvic Radiographs Using Efficientnet Deep Learning Model. 2024. Available at SSRN 4995313.
  • 25. Seçgin Y, Öner Z, Öner S, Toy Ş. Gender prediction using geometric morphometry with parameters of the cranium obtained from computed tomography images. Cukurova Med J. 2024;49(3):769-778.
  • 26. Secgin Y, Oner Z, Turan M, Oner S. Gender prediction with the parameters obtained from pelvis computed tomography images and machine learning algorithms. J Anat Soc India. 2022;71(3):204-209.
  • 27. Gama I, Navega D, Cunha E. Sex estimation using the second cervical vertebra: a morphometric analysis in a documented Portuguese skeletal sample. Int J Legal Med. 2015;129(2):365-372.
  • 28. Franklin D, O’Higgins P, Oxnard C, Dadour I. Sexual dimorphism and population variation in the adult mandible: forensic applications of geometric morphometrics. Forensic Sci Med Pathol. 2007;3(1):15-22.
  • 29. Fauad M, Alias A, Noor K, Choy K, Ng W, Chung E, et al. Sexual dimorphism from third cervical vertebra (C3) on lateral cervical radiograph: A 2-dimensional geometric morphometric approach. Forensic Imaging. 2021;24:200441.
  • 30. Rozendaal A, Scott S, Peckmann T, Meek S. Estimating sex from the seven cervical vertebrae: an analysis of two European skeletal populations. Forensic Sci Int. 2020;306:110072.
  • 31. Kaeswaren Y, Hackman L. Sexual dimorphism in the cervical vertebrae and its potential for sex estimation of human skeletal remains in a white scottish population. Forensic Sci Int Rep. 2019;1:100023.
  • 32. Ekizoglu O, Hocaoglu E, Inci E, Karaman G, Garcia-Donas J, Kranioti E, et al. Virtual morphometric method using seven cervical vertebrae for sex estimation on the Turkish population. Int J Legal Med. 2021;135(5):1953-1964.
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Adli Tıp, Klinik Tıp Bilimleri (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Yusuf Seçgin 0000-0002-0118-6711

Halil Şaban Erkartal 0000-0002-6558-3265

Zaid Ali Naji Zanqah 0009-0006-2619-3180

Nesibe Yılmaz 0000-0002-5527-8507

Nevin Köremezli Keskin 0000-0002-3169-9083

Şeyma Toy 0000-0002-6067-0087

Erken Görünüm Tarihi 10 Aralık 2025
Yayımlanma Tarihi 14 Aralık 2025
Gönderilme Tarihi 8 Eylül 2025
Kabul Tarihi 12 Ekim 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 22 Sayı: 4

Kaynak Göster

Vancouver Seçgin Y, Erkartal HŞ, Zanqah ZAN, Yılmaz N, Köremezli Keskin N, Toy Ş. Sex Prediction Using Geometric Morphometry with Parameters Obtained From Computed Tomography Images of the Seventh Cervical Vertebra. Harran Üniversitesi Tıp Fakültesi Dergisi. 2025;22(4).

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