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Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning

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Abstract

Objective

This study aimed to evaluate the usability of morphometric features obtained from mandibular panoramic radiographs in gender determination using machine learning algorithms.

Materials and methods

High-resolution radiographs of 200 patients aged 20–77 (41.0 ± 12.7) were included in the study. Twelve different morphometric measurements were extracted from each digital panoramic radiography included in the study. These measurements were used as features in the machine learning phase in which six different machine learning algorithms were used (k-nearest neighbor, decision trees, support vector machines, naive Bayes, linear discrimination analysis, and neural networks). To evaluate the reliability, we have performed tenfold cross-validation and we repeated this 10 times for every classification process. This process enhances the reliability of the results for other datasets.

Results

When all 12 features are used together, the accuracy rate is found to be 82.6 ± 0.5%. The classification accuracies are also compared using each feature alone. Three features that give the highest accuracy are coronoid height (80.9 ± 0.9%), condyle height (78.2 ± 0.5%), and ramus height (77.2 ± 0.4%), respectively. When compared to the classification algorithms, the highest accuracy was obtained with the naive Bayes algorithm with a rate of 84.0 ± 0.4%.

Conclusion

Machine learning techniques can accurately determine gender by analyzing mandibular morphometric structures from digital panoramic radiographs. The most precise results are achieved by evaluating the structures in combination, using attributes obtained from applying the MRMR algorithm to all features.

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Data availability

The datasets generated and/or analyzed during the current study are not publicly available considering that we have not required consents to publish this data, but are available from the corresponding author on reasonable request.

References

  1. Scheuer L. Application of osteology to forensic medicine. Clin Anat. 2002;15(4):297–312.

    Article  PubMed  Google Scholar 

  2. Iscan MY, Steyn M. The human skeleton in forensic medicine, 3rd edn. Springfield: Charles C Thomas Publisher; 2013.

  3. Milošević D, Vodanović M, Galić I, Subašić M. Estimating biological gender from panoramic dental x-ray images. Paper presented at: 2019 11th international symposium on image and signal processing and analysis (ISPA). 2019.

  4. Güleç E, Sağır M, Özer İ. Sex determinatination from foramen magnum in human skeleton. Ankara Univ Fac Lang Hist Geogr J. 2003;43(1):1–9.

    Google Scholar 

  5. Saini V, Srivastava R, Rai RK, Shamal SN, Singh TB, Tripathi SK. Mandibular ramus: an indicator for sex in fragmentary mandible. J Forensic Sci. 2011;56:S13–6.

    Article  PubMed  Google Scholar 

  6. Bhagwatkar T, Thakur M, Palve D, Bhondey A, Dhengar Y, Chaturvedi S. Sex determination by using mandibular ramus-a forensic study. J Adv Med Dent Sci Res. 2016;4(2):1.

    Google Scholar 

  7. More CB, Vijayvargiya R, Saha N. Morphometric analysis of mandibular ramus for sex determination on digital orthopantomogram. J Forensic Dent Sci. 2017;9(1):1.

    PubMed  PubMed Central  Google Scholar 

  8. Patil V, Vineetha R, Vatsa S, et al. Artificial neural network for gender determination using mandibular morphometric parameters: a comparative retrospective study. Cogent Eng. 2020;7(1):1723783.

    Article  Google Scholar 

  9. Krishan K, Chatterjee PM, Kanchan T, Kaur S, Baryah N, Singh R. A review of sex estimation techniques during examination of skeletal remains in forensic anthropology casework. Forensic Sci Int. 2016;261:165.e161–8.

  10. Franklin D, O’Higgins P, Oxnard CE, Dadour I. Determination of sex in South African Blacks by discriminant function analysis of mandibular linear dimensions: a preliminary investigation using the Zulu local population. Forensic Sci Med Pathol. 2006;2:263–8.

    Article  PubMed  Google Scholar 

  11. Poongodi V, Kanmani R, Anandi M, Krithika C, Kannan A, Raghuram P. Prediction of age and gender using digital radiographic method: a retrospective study. J Pharm Bioallied Sci. 2015;7(Suppl 2):S504.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Bhuyan R, Mohanty S, Bhuyan SK, Pati A, Priyadarshini S, Das P. Panoramic radiograph as a forensic aid in age and gender estimation: preliminary retrospective study. J Oral Maxillofac Pathol. 2018;22(2):266.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Indira AP, Markande A, David MP. Mandibular ramus: an indicator for sex determination-a digital radiographic study. J Forensic Dent Sci. 2012;4(2):58.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Dosi T, Vahanwala S, Gupta D. Assessment of the effect of dimensions of the mandibular ramus and mental foramen on age and gender using digital panoramic radiographs: a retrospective study. Contemp Clin Dentist. 2018;9(3):343.

    Article  Google Scholar 

  15. Hatipoğlu FP, Arıcıoğlu B, Hatipoğlu Ö, Köse TE, Günaçar DN. Prediction of root canal lengths and pulp volume of the maxillary permanent first molar based on stature, crown diameters, and facial morphometry. Anat Sci Int. 2023;98:454–62.

    Article  PubMed  Google Scholar 

  16. Nayyar AS, Kartheeki B, Sindhu YU. Accuracy of mandibular rami measurements in prediction of sex. Ann Med Health Sci Res. 2017;7(1):25–9.

    Google Scholar 

  17. Chandra A, Singh A, Badni M, Jaiswal R, Agnihotri A. Determination of sex by radiographic analysis of mental foramen in North Indian population. J Forensic Dent Sci. 2013;5(1):52.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Mathew NS, Chatra L, Shenoy P, Veena K, Prabhu RV, Sujatha B. Gender determination in panoramic radiographs, utilizing mandibular ramus parameters: a cross-sectional study. J Dent Res Rev. 2017;4(2):32–5.

    Article  Google Scholar 

  19. Maloth KN, Kundoor VKR, Vishnumolakala SSLP, Kesidi S, Lakshmi MV, Thakur M. Mandibular ramus: a predictor for sex determination-a digital radiographic study. J Indian Acad Oral Med Radiol. 2017;29(3):242–6.

    Article  Google Scholar 

  20. Sambhana S, Sanghvi P, Mohammed RB, Shanta PP, Thetay AAR, Chaudhary VS. Assessment of sexual dimorphism using digital orthopantomographs in South Indians. J Forensic Dent Sci. 2016;8(3):180.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Abualhija D, Revie G, Manica S. Mandibular ramus as a sex predictor in adult Jordanian subjects. Forensic Imaging. 2020;21: 200366.

    Article  Google Scholar 

  22. Damera A, Mohanalakhsmi J, Yellarthi PK, Rezwana BM. Radiographic evaluation of mandibular ramus for gender estimation: retrospective study. J Forensic Dent Sci. 2016;8(2):74.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Chalkoo AH, Maqbool S, Wani BA. Radiographic evaluation of sexual dimorphism in mandibular ramus: a digital orthopantomography study. Int J Appl Dent Sci. 2019;5(1):163–6.

    Google Scholar 

  24. Vinay G, SR MG, Anbalagan J. Sex determination of human mandible using metrical parameters. J Clin Diagnostic Research: JCDR. 2013;7(12):2671.

  25. Vodanović M, Dumančić J, Demo Ž, Mihelić D. Determination of sex by discriminant function analysis of mandibles from two Croatian archaeological sites. Acta Stomatol Croat. 2006;40(3):263–77.

    Google Scholar 

  26. Sharma M, Gorea RK, Gorea A, Abuderman A. A morphometric study of the human mandible in the Indian population for sex determination. Egypt J Forensic Sci. 2016;6(2):165–9.

    Article  Google Scholar 

  27. Pokhrel R, Bhatnagar R. Sexing of mandible using ramus and condyle in Indian population: a discriminant function analysis. Eur J Anat. 2013;17(1):39–42.

    Google Scholar 

  28. Kumar MP, Lokanadham S. Sex determination & morphometric parameters of human mandible. Int J Res Med Sci. 2013;1(2):93–6.

    Article  Google Scholar 

  29. Bertsatos A, Athanasopoulou K, Chovalopoulou M-E. Estimating sex using discriminant analysis of mandibular measurements from a modern Greek sample. Egypt J Forensic Sci. 2019;9:1–12.

    Article  Google Scholar 

  30. Villanueva EÁ, Garmendia AM, Torres G, Sánchez-Mejorada G, Gómez-Valdés JA. Gender assessment using the mandible in the Mexican population. Spanish J Legal Med. 2017;43(4):146–54.

    Article  Google Scholar 

  31. Sapancı İ, Şahin HO, Doğan Ö. Mandibular parametreler ile yaş ve cinsiyet arasındaki ilişkinin araştırılması: Retrospektif çalışma. Selcuk Dental J. 2019;6(4):328–34.

    Google Scholar 

  32. Sairam V, Potturi GR, Praveen B, Vikas G. Assessment of effect of age, gender, and dentoalveolar changes on mandibular morphology: a digital panoramic study. Contemp Clin Dentist. 2018;9(1):49.

    Article  CAS  Google Scholar 

  33. Jambunath U, Govindraju P, Balaji P, Poornima C, Latha S. Sex determination by using mandibular ramus and gonial angle–a preliminary comparative study. Int J Contemp Med Res. 2016;3(11):3278–80.

    Google Scholar 

  34. Samatha K, Byahatti SM, Ammanagi RA, Tantradi P, Sarang CK, Shivpuje P. Sex determination by mandibular ramus: a digital orthopantomographic study. J Forensic Dent Sci. 2016;8(2):95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Sönmez EÖ. Dijital panoramik radyografilerde morfometrik ölçümlerin çocuklarda yaş ve cinsiyet tayininde kullanılabilirliğinin retrospektif olarak araştırılması. Master thesis. Samsun: Pediatric Dentistry, Ondokuz Mayıs University; 2019.

    Google Scholar 

  36. Ortiz AG, Costa C, Silva RHAd, Biazevic MGH, Michel-Crosato E. Sex estimation: anatomical references on panoramic radiographs using Machine Learning. Forensic Imaging. 2020;20:200356.

  37. Kharoshah MAA, Almadani O, Ghaleb SS, Zaki MK, Fattah YAA. Sexual dimorphism of the mandible in a modern Egyptian population. J Forensic Leg Med. 2010;17(4):213–5.

    Article  PubMed  Google Scholar 

  38. Tunis TS, Sarig R, Cohen H, Medlej B, Peled N, May H. Sex estimation using computed tomography of the mandible. Int J Legal Med. 2017;131:1691–700.

    Article  PubMed  Google Scholar 

  39. Kallalli BN, Rawson K, Ramaswamy VK, Zakarneh WH, Singh A, Zingade J. Sex determination of human mandible using metrical parameters by computed tomography: a prospective radiographic short study. J Indian Acad Oral Med Radiol. 2016;28(1):7–10.

    Article  Google Scholar 

  40. de Oliveira GT, Alves MC, Haiter-Neto F. Mandibular sexual dimorphism analysis in CBCT scans. J Forensic Leg Med. 2016;38:106–10.

    Article  Google Scholar 

  41. Dong H, Deng M, Wang W, Zhang J, Mu J, Zhu G. Sexual dimorphism of the mandible in a contemporary Chinese Han population. Forensic Sci Int. 2015;255:9–15.

    Article  PubMed  Google Scholar 

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Acknowledgements

The present article has been sourced from Hanife Pertek’s Master’s dissertation.

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Authors and Affiliations

  1. Center for Nanotechnology & Biomaterials Application and Research (NBUAM), Marmara University, Istanbul, Turkey

    Hanife Pertek

  2. Department of Metallurgical and Materials Engineering, Faculty of Technology, Marmara University, Istanbul, Turkey

    Hanife Pertek

  3. Computer and Informatics, Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey

    Mustafa Kamaşak

  4. Department of Computer Education and Instructional Technologies, Atatürk Faculty of Education, Marmara University, Istanbul, Turkey

    Soner Kotan

  5. Department of Endodontics, Faculty of Dentistry, Niğde Ömer Halisdemir University, Niğde, Turkey

    Fatma Pertek Hatipoğlu

  6. Department of Restorative Dentistry, Faculty of Dentistry, Niğde Ömer Halisdemir University, Niğde, Turkey

    Ömer Hatipoğlu

  7. Department of Oral, Dental and Maxillofacial Surgery, Faculty of Dentistry, Recep Tayyip Erdogan University, Rize, Turkey

    Taha Emre Köse

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  1. Hanife Pertek
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  2. Mustafa Kamaşak
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  3. Soner Kotan
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  4. Fatma Pertek Hatipoğlu
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  5. Ömer Hatipoğlu
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Correspondence to Ömer Hatipoğlu.

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As per the statement made by the authors, it can be confirmed that there are no conflicting interests that could potentially influence their work or findings. This declaration serves as an assurance of the integrity and objectivity of their research.

Ethical Statement

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent was obtained from all patients for being included in the study.

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Pertek, H., Kamaşak, M., Kotan, S. et al. Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning. Oral Radiol (2024). https://doi.org/10.1007/s11282-024-00751-9

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