The morphology of the human mandible: A computational modelling study

  • Ravin Vallabh
  • Ju Zhang
  • Justin Fernandez
  • George Dimitroulis
  • David C. AcklandEmail author
Original Paper


Cephalometric methods have been used to evaluate morphometric measurements of the mandible and quantify sex-related anatomical features; however, most studies to date employ a limited set of location-specific measurements without considering the entire three-dimensional anatomy of the mandible. The aims of this study were to develop statistical shape models (SSMs) of partially edentulous male and female mandibles to evaluate inter-subject morphological variability and secondly to assess the effectiveness of discrete clinical morphometric measurements in prediction of complete three-dimensional mandible geometry. Computed tomography images of forty partially edentulous female and twenty-five male subjects were obtained, and SSM developed using mesh fitting, rigid body registration and principal component analysis. Analysis of female and male SSMs showed that the variation along their first principal components was size-related. Sex-differentiating pure shape variations were found along the first principal component of size-normalised SSM and were observed to be most prominent in the symphysis and posterior ramus regions of the mandible. Seven morphometric measurements were found to characterise female and male shape prediction optimally. The capability to rapidly generate accurate patient-specific shape-predictive models of the mandible may be useful for implant development and pre-operative planning, particularly in the absence of bony structures following trauma or tumour resection.


Statistical shape model Jaw anatomy Shape analysis Predictive model Morphometry Biomechanics 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10237_2019_1133_MOESM1_ESM.doc (316 kb)
Supplementary material 1 (DOC 316 kb)


  1. Ackland DC, Robinson D, Redhead M, Lee PV, Moskaljuk A, Dimitroulis G (2017) A personalized 3D-printed prosthetic joint replacement for the human temporomandibular joint: from implant design to implantation. J Mech Behav Biomed Mater 69:404–411. CrossRefGoogle Scholar
  2. Aragao JA, Souto ML, Mateus CR, Menezes Ldos S, Reis FP (2014) Edentulousness in relation to remodeling of the gonial angles and incisures in dentate and edentate mandibles: morphometric study using the Image J software. Surg Radiol Anat 36:889–894. CrossRefGoogle Scholar
  3. Bah MT et al (2015) Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model. Med Eng Phys 37:995–1007. CrossRefGoogle Scholar
  4. Balci Y, Yavuz MF, Cagdir S (2005) Predictive accuracy of sexing the mandible by ramus flexure. Homo 55:229–237CrossRefGoogle Scholar
  5. Bayome M, Park JH, Kook YA (2013) New three-dimensional cephalometric analyses among adults with a skeletal Class I pattern and normal occlusion. Korean J Orthod 43:62–73. CrossRefGoogle Scholar
  6. Bousleiman H, Iizuka T, Nolte LP, Reyes M (2013) Population-based design of mandibular fixation plates with bone quality and morphology considerations. Ann Biomed Eng 41:377–384. CrossRefGoogle Scholar
  7. Bräuer G (1988) Osteometrie. In: Knussmann R (ed) Anthropologie Handbuch der Vergleichenden Biologie des Menschen Band 1 Wesen und Methoden der Anthropologie. Gustav Fischer, StuttgartGoogle Scholar
  8. Brennan RM, Genco RJ, Hovey KM, Trevisan M, Wactawski-Wende J (2007) Clinical attachment loss, systemic bone density, and subgingival calculus in postmenopausal women. J Periodontol 78:2104–2111. CrossRefGoogle Scholar
  9. Chan EF, Farnsworth CL, Koziol JA, Hosalkar HS, Sah RL (2013) Statistical shape modeling of proximal femoral shape deformities in Legg–Calvé–Perthes disease and slipped capital femoral epiphysis. Osteoarthr Cartil 21:443–449. CrossRefGoogle Scholar
  10. Chrcanovic BR, Abreu MHNG, Custódio ALN (2011) Morphological variation in dentate and edentulous human mandibles. Surg Radiol Anat 33:203–213. CrossRefGoogle Scholar
  11. Cocos A, Halazonetis DJ (2017) Craniofacial shape differs in patients with tooth agenesis: geometric morphometric analysis. Eur J Orthod 39:345–351. Google Scholar
  12. Dye B, Thornton-Evans G, Li X, Iafolla T (2015) Dental caries and tooth loss in adults in the United States, 2011–2012. NCHS data brief: 197Google Scholar
  13. Eke PI et al (2015) Update on prevalence of periodontitis in adults in the United States: NHANES 2009 to 2012. J Periodontol 86:611–622. CrossRefGoogle Scholar
  14. Franklin D, O’Higgins P, Oxnard CE, Dadour I (2007) Sexual dimorphism and population variation in the adult mandible: forensic applications of geometric morphometrics. Forensic Sci Med Pathol 3:15–22. Google Scholar
  15. Ghosh S, Vengal M, Pai KM (2009) Remodeling of the human mandible in the gonial angle region: a panoramic, radiographic, cross-sectional study. Oral Radiol 25:2–5. CrossRefGoogle Scholar
  16. Guler AU, Sumer M, Sumer P, Bicer I (2005) The evaluation of vertical heights of maxillary and mandibular bones and the location of anatomic landmarks in panoramic radiographs of edentulous patients for implant dentistry. J Oral Rehabil 32:741–746. CrossRefGoogle Scholar
  17. Huumonen S et al (2010) Influence of edentulousness on gonial angle, ramus and condylar height. J Oral Rehabil 37:34–38. CrossRefGoogle Scholar
  18. Hwang E, Lin C, Jiao B, Chung N-E, Han S-H, Kim J, Lee UY (2015) Discriminant function analysis for sex determination using landmark coordinate data from three-dimensional mandible models. Aust J Forensic Sci 47:332–344. CrossRefGoogle Scholar
  19. Jolliffe IT (2002) Principal component analysis. Springer, BerlinzbMATHGoogle Scholar
  20. Kailembo A, Preet R, Stewart Williams J (2017) Common risk factors and edentulism in adults, aged 50 years and over, in China, Ghana, India and South Africa: results from the WHO Study on global AGEing and adult health (SAGE). BMC Oral Health 17:29. CrossRefGoogle Scholar
  21. Kemkes-Grottenthaler A, Lobig F, Stock F (2002) Mandibular ramus flexure and gonial eversion as morphologic indicators of sex. Homo 53:97–111CrossRefGoogle Scholar
  22. Kim S-G et al (2012) Development of 3D statistical mandible models for cephalometric measurements. Imaging Sci Dent 42:175–182CrossRefGoogle Scholar
  23. Koc D, Dogan A, Bek B (2010) Bite force and influential factors on bite force measurements: a literature review. Eur J Dent 4:223–232Google Scholar
  24. Lima FJC, Oliveira Neto OB, Barbosa FT, Sousa-Rodrigues CF (2016) Location, shape and anatomic relations of the mandibular foramen and the mandibular lingula: a contribution to surgical procedures in the ramus of the mandible. Oral Maxillofac Surg 20:177–182. CrossRefGoogle Scholar
  25. Lin H, Zhu P, Lin Y, Wan S, Shu X, Xu Y, Zheng Y (2013) Mandibular asymmetry: a three-dimensional quantification of bilateral condyles. Head Face Med 9:42. CrossRefGoogle Scholar
  26. Lin C, Jiao B, Liu S, Guan F, Chung NE, Han SH, Lee UY (2014) Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models. Forensic Sci Int 236:191.e191–191.e196. CrossRefGoogle Scholar
  27. Loth SR, Henneberg M (1996) Mandibular ramus flexure: a new morphologic indicator of sexual dimorphism in the human skeleton. Am J Phys Anthropol 99:473–485.<473:aid-ajpa>;2-x CrossRefGoogle Scholar
  28. McGarry TJ, Nimmo A, Skiba JF, Ahlstrom RH, Smith CR, Koumjian JH, Arbree NS (2002) Classification system for partial edentulism. J Prosthodont 11:181–193CrossRefGoogle Scholar
  29. Metzger MC, Vogel M, Hohlweg-Majert B, Mast H, Fan X, Rüdell A, Schlager S (2011) Anatomical shape analysis of the mandible in Caucasian and Chinese for the production of preformed mandible reconstruction plates. J Craniomax Surg 39:393–400. CrossRefGoogle Scholar
  30. Mohammad AR, Hooper DA, Vermilyea SG, Mariotti A, Preshaw PM (2003) An investigation of the relationship between systemic bone density and clinical periodontal status in post-menopausal Asian-American women. Int Dent J 53:121–125. CrossRefGoogle Scholar
  31. Nicholson E, Harvati K (2006) Quantitative analysis of human mandibular shape using three-dimensional geometric morphometrics. Am J Phys Anthropol 131:368–383. CrossRefGoogle Scholar
  32. Oettle AC, Becker PJ, de Villiers E, Steyn M (2009a) The influence of age, sex, population group, and dentition on the mandibular angle as measured on a South African sample. Am J Phys Anthropol 139:505–511. CrossRefGoogle Scholar
  33. Oettle AC, Pretorius E, Steyn M (2009b) Geometric morphometric analysis of the use of mandibular gonial eversion in sex determination. Homo 60:29–43. CrossRefGoogle Scholar
  34. Ozturk CN, Ozturk C, Bozkurt M, Uygur HS, Papay FA, Zins JE (2013) Dentition, bone loss, and the aging of the mandible. Aesthetic Surg J 33:967–974. CrossRefGoogle Scholar
  35. Parr NM, Passalacqua NV, Skorpinski K (2017) Investigations into age-related changes in the human mandible. J Forensic Sci. Google Scholar
  36. Peltzer K et al (2014) Prevalence of loss of all teeth (edentulism) and associated factors in older adults in China, Ghana, India, Mexico, Russia and South Africa. Int J Environ Res Public Health 11:11308–11324. CrossRefGoogle Scholar
  37. Polychronis G, Christou P, Mavragani M, Halazonetis DJ (2013) Geometric morphometric 3D shape analysis and covariation of human mandibular and maxillary first molars. Am J Phys Anthropol 152:186–196. Google Scholar
  38. Raith S, Varga V, Steiner T, Hölzle F, Fischer H (2016) Computational geometry assessment for morphometric analysis of the mandible. Comput Methods Biomech Biomed Eng 20:27–34. CrossRefGoogle Scholar
  39. Raith S, Wolff S, Steiner T, Modabber A, Weber M, Hölzle F, Fischer H (2017) Planning of mandibular reconstructions based on statistical shape models. Int J Comput Assist Radiol Surg 12:99–112. CrossRefGoogle Scholar
  40. Russell S, Gordon S, Lukacs J, Kaste L (2013) Sex/gender differences in tooth loss and edentulism: historical perspectives, biological factors, and sociologic reasons. Dent Clin. Google Scholar
  41. Schneider MT, Zhang J, Crisco JJ, Weiss AP, Ladd AL, Nielsen P, Besier T (2015) Men and women have similarly shaped carpometacarpal joint bones. J Biomech 48:3420–3426. CrossRefGoogle Scholar
  42. Sella-Tunis T, Pokhojaev A, Sarig R, O’Higgins P, May H (2018) Human mandibular shape is associated with masticatory muscle force. Sci Rep 8:6042. CrossRefGoogle Scholar
  43. Smoger LM, Shelburne KB, Cyr AJ, Rullkoetter PJ, Laz PJ (2017) Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking. J Biomech 58:187–194. CrossRefGoogle Scholar
  44. Tibshirani R (1996) Regression shrinkage and selection via the lasso. J R Stat Soc Ser B (Methodol) 58:267–288MathSciNetzbMATHGoogle Scholar
  45. Watanabe H, Mohammad Abdul M, Kurabayashi T, Aoki H (2010) Mandible size and morphology determined with CT on a premise of dental implant operation. Surg Radiol Anat 32:343–349. CrossRefGoogle Scholar
  46. Woods C, Fernee C, Browne M, Zakrzewski S, Dickinson A (2017) The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research. PLoS ONE 12:e0186754. CrossRefGoogle Scholar
  47. Wu B, Liang J, Plassman BL, Remle RC, Luo X (2012) Edentulism trends among middle-aged and older adults in the united states: comparison of five racial/ethnic groups. Commun Dent Oral Epidemiol 40:145–153. CrossRefGoogle Scholar
  48. Zachow S, Lamecker H, Elsholtz B, Stiller M (2005) Reconstruction of mandibular dysplasia using a statistical 3D shape model. Int Congr Ser 1281:1238–1243. CrossRefGoogle Scholar
  49. Zhang J, Malcolm D, Hislop-Jambrich J, Thomas CDL, Nielsen PMF (2014) An anatomical region-based statistical shape model of the human femur. Comput Methods Biomech Biomed Eng Imaging Vis 2:176–185. CrossRefGoogle Scholar
  50. Zhang J, Hislop-Jambrich J, Besier TF (2016) Predictive statistical models of baseline variations in 3-D femoral cortex morphology. Med Eng Phys 38:450–457. CrossRefGoogle Scholar
  51. Zhang J, Ackland DC, Fernandez J (2018) Point-cloud registration using adaptive radial basis functions. Comput Methods Biomech Biomed Eng 21:498–502CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringUniversity of MelbourneParkvilleAustralia
  2. 2.Auckland Bioengineering InstituteUniversity of AucklandAucklandNew Zealand
  3. 3.Department of Engineering ScienceUniversity of AucklandAucklandNew Zealand
  4. 4.Department of SurgerySt Vincent’s HospitalFitzroyAustralia

Personalised recommendations