Determination of Gender By Machine Learning Algorithms, Through Using Craniocervical Junction Parameters and Dimensions of the Cervical Spinal Canal

Gamze Taşkın Senol; İbrahim Kürtül; Abdullah Ray; Gülçin Ahmetoğlu; Yusuf Seçgin; Zülal Öner

doi:10.20515/otd.1291030

Research Article

Determination of Gender By Machine Learning Algorithms, Through Using Craniocervical Junction Parameters and Dimensions of the Cervical Spinal Canal

Year 2023, Volume: 45 Issue: 5, 672 - 677, 27.09.2023

Gamze Taşkın Senol İbrahim Kürtül Abdullah Ray Gülçin Ahmetoğlu Yusuf Seçgin Zülal Öner

https://doi.org/10.20515/otd.1291030

Abstract

Gender determination is the first step for biological identification. With the widespread use of machine learning algorithms (MLA) for diagnosis, the significance of applying them also in gender determination studies has become apparent. This study has therefore aimed at determining gender from the parameters obtained out of magnetic resonance images (MRI) of the cranio-cervical junction and cervical-spinal canal by using MLA. MRI of the craniocervical junction and cervical-spinal canal of 110 men and 110 women were included in this study. The 15 parameters were tested with Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) algorithms. Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), F1 score (F1), Matthews-correlation coefficient (Mcc) values were used as performance criteria. The Acc, Spe, Sen, F1, and Mcc were found to be 1.00 in the LR, LDA, QDA and RF algorithms. The ratios of the Acc, Spe, Sen, and F1 were 0.98, and of the Mcc was 0.96 in the DT algorithm. It was found that the ratio between the SHAP analyzer of the RF algorithm and the belt of the ratio between the arch of the atlas and the anterior-posterior distance of the dens (R3) parameter had a higher contribution to the estimation of gender compared to other parameters. It was concluded that the LDA, QDA, LR, DT and RF algorithms applied to the parameters acquired from the MRI of the craniocervical junction and cervical-spinal canal, could determine the gender with very high accuracy.

Keywords

Craniocervical Junction, Cervical Spinal Canal, Magnetic Resonance Imaging, Sex Determination, Machine Learning Algorithms

References

1. Zeyfeoğlu Y, Hancı İH. İnsanlarda Kimlik Tespiti. Sted. 2001;10(10):375–7.
2. Durić M, Rakočević Z, Donić D. The reliability of sex determination of skeletons from forensic context in the Balkans. Forensic Sci Int. 2005;147(2-3 SPEC.ISS.):159–64.
3. Kranioti EF, Apostol MA. Sexual dimorphism of the tibia in contemporary Greeks, Italians, and Spanish: forensic implications. Int J Legal Med. 2015;129(2):357–63.
4. Tellioglu AM, Karakas S. Humerus’tan morfometrik yöntemlerle cinsiyet tayini. FÜSağBilTıp Derg. 2013;27(2):75–9.
5. Tellioglu AM, Durum Y, Gök M, Karakas S, Polat AG, Karaman CZ. Suitability of foramen magnum measurements in sex determination and their clinical significance. Folia Morphol. 2018;77(1):99–104.
6. Toy S, Secgin Y, Oner Z, Turan MK, Oner S, Senol D. A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium. Sci Rep [Internet]. 2022;12(1):1–11.
7. Güleç E, Sağır M, Özer İ. İnsan İskeletlerinde Foramen Magnum’dan Cinsiyet Tayini. Ankara Üniversitesi Dil ve Tarih-Coğrafya Fakültesi Derg. 2003;43(1):1–9.
8. Seçme Özkaya Z, Aslan A. Kranioservikal Bileşke Travmalarında Tanı Yöntemleri. Arşiv Kaynak Tarama Derg. 2016;25(3):335–50.
9. Offiah CE, Day E. The craniocervical junction: embryology, anatomy, biomechanics and imaging in blunt trauma. Insights Imaging [Internet]. 2017;8(1):29–47.
10. Korkmaz M, Kilincer C. Derleme Türk Nöroşir Servikal Dar Kanalda Doğal Seyir ve İzlem Araçlarının Yeri Natural Course of Cervical Spinal Stenosis and Follow-up Tools. Derg. 2018;28(2):159–64.
11. Malas MA, Salbacak A, Aler A, Yardımcı C. Lumbal canalis vertebralis orta sagittal çaplarının magnetic resonance görüntüleme ile belirlenmesi. Sdü Tip Fakültesi Dergisi. 1997;4(3):7–11.
12. Sunar M, Kapakin S. Morphometric evaluation of craniocervical junction by magnetic resonance imaging method. Asian J Neurosurg. 2019;14(3):702–9.
13. Ulbrich EJ, Schraner C, Boesch C, Hodler J, Busato A, Anderson SE, et al. Normative MR cervical spinal canal dimensions. Radiology. 2014;271(1):172–82.
14. Kranioti EF, Vorniotakis N, Galiatsou C, Işcan MY, Michalodimitrakis M. Sex identification and software development using digital femoral head radiographs. Forensic Sci Int. 2009;189(1–3):113.e1-113.e7.
15. Secgin Y, Oner Z, Turan M, Oner S. Gender prediction with parameters obtained from pelvis computed tomography images and decision tree algorithm. Med Sci | Int Med J. 2021;10(2):356.
16. Curate F, Umbelino C, Perinha A, Nogueira C, Silva AM, Cunha E. Sex determination from the femur in Portuguese populations with classical and machine-learning classifiers. J Forensic Leg Med [Internet]. 2017;52:75–81.
17. Marlow EJ, Pastor RF. Sex Determination Using the Second Cervical Vertebra—A Test. J Forensic Sci. 2011;56(1):165–9.
18. Ünlütürk Ö, İşcan MY. Tanınabilir Vertebralardan Cinsiyet Tayini. Bull Leg Med. 2014;18(1):4–13.
19. Rohmani A, Shafie MS, Nor FM. Sex estimation using the human vertebra: A systematic review. Egypt J Forensic Sci. 2021;11(1).
20. Gülhan Ö. Pelvis’ten radyolojik yöntemler ile cinsiyet tayini: Türkiye örneklemi. Antropoloji. 2018;36:53–69.
21. Gill GW. Racial Variation in the Proximal and Distal Femur: Heritability and Forensic Utility. J Forensic Sci. 2001;46(4):15049J.
22. Inskip S, Scheib CL, Wohns AW, Ge X, Kivisild T, Robb J. Evaluating macroscopic sex estimation methods using genetically sexed archaeological material: The medieval skeletal collection from St John’s Divinity School, Cambridge. Am J Phys Anthropol. 2019;168(2):340–51.
23. Scheuer L. Application of osteology to forensic medicine. Clin Anat. 2002;15(4):297–312.
24. Ahmed AA. Estimation of sex from the upper limb measurements of Sudanese adults. J Forensic Leg Med [Internet]. 2013;20(8):1041–7.
25. Ali Z, Cox C, Stock MK, Zandee vanRilland EE, Rubio A, Fowler DR. Estimating Sex Using Metric Analysis of the Scapula by Postmortem Computed Tomography. J Forensic Sci. 2018;63(5):1346–9.
26. Colman KL, de Boer HH, Dobbe JGG, Liberton NPTJ, Stull KE, van Eijnatten M, et al. Virtual forensic anthropology: The accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans. Forensic Sci Int [Internet]. 2019;304:109963.
27. Colman KL, van der Merwe AE, Stull KE, Dobbe JGG, Streekstra GJ, van Rijn RR, et al. The accuracy of 3D virtual bone models of the pelvis for morphological sex estimation. Int J Legal Med. 2019;133(6):1853–60.
28. Torimitsu S, Makino Y, Saitoh H, Sakuma A, Ishii N, Yajima D, et al. Sexual determination based on multidetector computed tomographic measurements of the second cervical vertebra in a contemporary Japanese population. Forensic Sci Int [Internet]. 2016;266:588.e1-588.e6.
29. 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):365–72.
30. Mostafavi RS, Memarian A, Amiri A, Motamedi O. Estimating Sex from second and seventh cervical vertebras in Iranian adult population using Computed Tomography scan images. Nucl Med Med Imaging [Internet]. 2020;1–13.

Kraniyoservikal Bileşke Parametreleri ve Servikal Spinal Kanal Boyutları Kullanılarak Makine Öğrenimi Algoritmaları ile Cinsiyetin Belirlenmesi

Year 2023, Volume: 45 Issue: 5, 672 - 677, 27.09.2023

Gamze Taşkın Senol İbrahim Kürtül Abdullah Ray Gülçin Ahmetoğlu Yusuf Seçgin Zülal Öner

https://doi.org/10.20515/otd.1291030

Abstract

Cinsiyet belirleme, biyolojik tanımlama için ilk adımdır. Makine öğrenmesi algoritmalarının (MLA) teşhis için yaygın olarak kullanılmasıyla birlikte, cinsiyet belirleme çalışmalarında da uygulanmasının önemi ortaya çıkmıştır. Bu nedenle bu çalışmada, MLA kullanılarak kranio-servikal bileşke ve servikal-spinal kanalın manyetik rezonans görüntülerinden (MRG) elde edilen parametrelerden cinsiyetin belirlenmesi amaçlanmıştır. Bu çalışmaya 110 erkek ve 110 kadının kraniyoservikal bileşke ve servikal-spinal kanal MR görüntüleri dahil edildi. 15 parametre Karar Ağacı (DT), Rastgele Orman (RF), Lojistik Regresyon (LR), Doğrusal Diskriminant Analizi (LDA), Kuadratik Diskriminant Analizi (QDA) algoritmaları ile test edilmiştir. Performans kriterleri olarak Doğruluk (Acc), Özgüllük (Spe), Duyarlılık (Sen), F1 skoru (F1), Matthews-korelasyon katsayısı (Mcc) değerleri kullanılmıştır.
Sonuçlar: Acc, Spe, Sen, F1 ve Mcc değerleri LR, LDA, QDA ve RF algoritmalarında 1.00 olarak bulunmuştur. DT algoritmasında Acc, Spe, Sen ve F1 oranları 0.98, Mcc oranı ise 0.96 olarak bulunmuştur. RF algoritmasının SHAP analizörü ile atlasın kavisi ile densin ön-arka mesafesi arasındaki oranın kemeri (R3) parametresinin cinsiyet tahminine katkısının diğer parametrelere kıyasla daha yüksek olduğu bulunmuştur. Kraniyoservikal bileşke ve servikal-spinal kanal MRG'sinden elde edilen parametrelere uygulanan LDA, QDA, LR, DT ve RF algoritmalarının cinsiyeti çok yüksek doğrulukla belirleyebildiği sonucuna varılmıştır.

Keywords

kraniyoservikal bileşke, servikal spinal kanal, manyetik rezonanans görüntüleme, cinsiyet tayini, makine öğrenim algoritması

References

1. Zeyfeoğlu Y, Hancı İH. İnsanlarda Kimlik Tespiti. Sted. 2001;10(10):375–7.
2. Durić M, Rakočević Z, Donić D. The reliability of sex determination of skeletons from forensic context in the Balkans. Forensic Sci Int. 2005;147(2-3 SPEC.ISS.):159–64.
3. Kranioti EF, Apostol MA. Sexual dimorphism of the tibia in contemporary Greeks, Italians, and Spanish: forensic implications. Int J Legal Med. 2015;129(2):357–63.
4. Tellioglu AM, Karakas S. Humerus’tan morfometrik yöntemlerle cinsiyet tayini. FÜSağBilTıp Derg. 2013;27(2):75–9.
5. Tellioglu AM, Durum Y, Gök M, Karakas S, Polat AG, Karaman CZ. Suitability of foramen magnum measurements in sex determination and their clinical significance. Folia Morphol. 2018;77(1):99–104.
6. Toy S, Secgin Y, Oner Z, Turan MK, Oner S, Senol D. A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium. Sci Rep [Internet]. 2022;12(1):1–11.
7. Güleç E, Sağır M, Özer İ. İnsan İskeletlerinde Foramen Magnum’dan Cinsiyet Tayini. Ankara Üniversitesi Dil ve Tarih-Coğrafya Fakültesi Derg. 2003;43(1):1–9.
8. Seçme Özkaya Z, Aslan A. Kranioservikal Bileşke Travmalarında Tanı Yöntemleri. Arşiv Kaynak Tarama Derg. 2016;25(3):335–50.
9. Offiah CE, Day E. The craniocervical junction: embryology, anatomy, biomechanics and imaging in blunt trauma. Insights Imaging [Internet]. 2017;8(1):29–47.
10. Korkmaz M, Kilincer C. Derleme Türk Nöroşir Servikal Dar Kanalda Doğal Seyir ve İzlem Araçlarının Yeri Natural Course of Cervical Spinal Stenosis and Follow-up Tools. Derg. 2018;28(2):159–64.
11. Malas MA, Salbacak A, Aler A, Yardımcı C. Lumbal canalis vertebralis orta sagittal çaplarının magnetic resonance görüntüleme ile belirlenmesi. Sdü Tip Fakültesi Dergisi. 1997;4(3):7–11.
12. Sunar M, Kapakin S. Morphometric evaluation of craniocervical junction by magnetic resonance imaging method. Asian J Neurosurg. 2019;14(3):702–9.
13. Ulbrich EJ, Schraner C, Boesch C, Hodler J, Busato A, Anderson SE, et al. Normative MR cervical spinal canal dimensions. Radiology. 2014;271(1):172–82.
14. Kranioti EF, Vorniotakis N, Galiatsou C, Işcan MY, Michalodimitrakis M. Sex identification and software development using digital femoral head radiographs. Forensic Sci Int. 2009;189(1–3):113.e1-113.e7.
15. Secgin Y, Oner Z, Turan M, Oner S. Gender prediction with parameters obtained from pelvis computed tomography images and decision tree algorithm. Med Sci | Int Med J. 2021;10(2):356.
16. Curate F, Umbelino C, Perinha A, Nogueira C, Silva AM, Cunha E. Sex determination from the femur in Portuguese populations with classical and machine-learning classifiers. J Forensic Leg Med [Internet]. 2017;52:75–81.
17. Marlow EJ, Pastor RF. Sex Determination Using the Second Cervical Vertebra—A Test. J Forensic Sci. 2011;56(1):165–9.
18. Ünlütürk Ö, İşcan MY. Tanınabilir Vertebralardan Cinsiyet Tayini. Bull Leg Med. 2014;18(1):4–13.
19. Rohmani A, Shafie MS, Nor FM. Sex estimation using the human vertebra: A systematic review. Egypt J Forensic Sci. 2021;11(1).
20. Gülhan Ö. Pelvis’ten radyolojik yöntemler ile cinsiyet tayini: Türkiye örneklemi. Antropoloji. 2018;36:53–69.
21. Gill GW. Racial Variation in the Proximal and Distal Femur: Heritability and Forensic Utility. J Forensic Sci. 2001;46(4):15049J.
22. Inskip S, Scheib CL, Wohns AW, Ge X, Kivisild T, Robb J. Evaluating macroscopic sex estimation methods using genetically sexed archaeological material: The medieval skeletal collection from St John’s Divinity School, Cambridge. Am J Phys Anthropol. 2019;168(2):340–51.
23. Scheuer L. Application of osteology to forensic medicine. Clin Anat. 2002;15(4):297–312.
24. Ahmed AA. Estimation of sex from the upper limb measurements of Sudanese adults. J Forensic Leg Med [Internet]. 2013;20(8):1041–7.
25. Ali Z, Cox C, Stock MK, Zandee vanRilland EE, Rubio A, Fowler DR. Estimating Sex Using Metric Analysis of the Scapula by Postmortem Computed Tomography. J Forensic Sci. 2018;63(5):1346–9.
26. Colman KL, de Boer HH, Dobbe JGG, Liberton NPTJ, Stull KE, van Eijnatten M, et al. Virtual forensic anthropology: The accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans. Forensic Sci Int [Internet]. 2019;304:109963.
27. Colman KL, van der Merwe AE, Stull KE, Dobbe JGG, Streekstra GJ, van Rijn RR, et al. The accuracy of 3D virtual bone models of the pelvis for morphological sex estimation. Int J Legal Med. 2019;133(6):1853–60.
28. Torimitsu S, Makino Y, Saitoh H, Sakuma A, Ishii N, Yajima D, et al. Sexual determination based on multidetector computed tomographic measurements of the second cervical vertebra in a contemporary Japanese population. Forensic Sci Int [Internet]. 2016;266:588.e1-588.e6.
29. 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):365–72.
30. Mostafavi RS, Memarian A, Amiri A, Motamedi O. Estimating Sex from second and seventh cervical vertebras in Iranian adult population using Computed Tomography scan images. Nucl Med Med Imaging [Internet]. 2020;1–13.

There are 30 citations in total.

Details

Primary Language	English
Subjects	Health Care Administration
Journal Section	ORİJİNAL MAKALE
Authors	Gamze Taşkın Senol 0000-0001-5587-1055 İbrahim Kürtül 0000-0002-9218-6468 Abdullah Ray 0000-0002-8124-6402 Gülçin Ahmetoğlu 0000-0002-0417-1806 Yusuf Seçgin 0000-0002-0118-6711 Zülal Öner 0000-0003-0459-1015
Publication Date	September 27, 2023
Published in Issue	Year 2023 Volume: 45 Issue: 5

Cite

Vancouver	Senol GT, Kürtül İ, Ray A, Ahmetoğlu G, Seçgin Y, Öner Z. Determination of Gender By Machine Learning Algorithms, Through Using Craniocervical Junction Parameters and Dimensions of the Cervical Spinal Canal. Osmangazi Tıp Dergisi. 2023;45(5):672-7.

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