Research Article
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Year 2024, Volume: 27 Issue: 3, 194 - 200, 30.09.2024

Elif Meltem Aslan Öztürk , Aslıhan Artaş

https://doi.org/10.7126/cumudj.1473635

Abstract

References

  • 1. Safi A-F, Kauke M, Grandoch A, Nickenig H-J, Zöller JE, Kreppel M. Age-related volumetric changes in mandibular condyles. J Craniofac Surg. 2018;29:510-513.
  • 2. Krisjane Z, Urtane I, Krumina G, Bieza A, Zepa K, Rogovska I. Condylar and mandibular morphological criteria in the 2D and 3D MSCT imaging for patients with Class II division 1 subdivision malocclusion. Stomatologija. 2007;9:67-71.
  • 3. Papadaki ME, Tayebaty F, Kaban LB, Troulis MJ. Condylar resorption. Oral Maxillofac Surg Clin North Am. 2007;19:223-234.
  • 4. Mercuri LG. Osteoarthritis, osteoarthrosis, and idiopathic condylar resorption. Oral Maxillofac Surg Clin North Am. 2008;20:169-183.
  • 5. Enomoto A, Watahiki J, Yamaguchi T, Irie T, Tachikawa T, Maki K. Effects of mastication on mandibular growth evaluated by microcomputed tomography. Eur J Orthod. 2010;32:66-70.
  • 6. Saccucci M, Polimeni A, Festa F, Tecco S. Do skeletal cephalometric characteristics correlate with condylar volume, surface and shape? A 3D analysis. Head Face Med. 2012;8:1-8.
  • 7. Hatch J, Shinkai R, Sakai S, Rugh J, Paunovich E. Determinants of masticatory performance in dentate adults. Arch Oral Biol. 2001;46:641-648.
  • 8. Paknahad M, Khojastepour L, Tabatabaei S, Mahjoori-Ghasrodashti M. Association between condylar bone changes and eichner index in patients with temporomandibular dysfunction: A cone beam computed tomography study. J Dent. 2023;24:12.
  • 9. Ikebe K, Matsuda K-i, Kagawa R, Enoki K, Okada T, Yoshida M. Masticatory performance in older subjects with varying degrees of tooth loss. J Dent. 2012;40:71-76.
  • 10. Ikebe K, Nokubi T, Morii K, Kashiwagi J, Furuya M. Association of bite force with ageing and occlusal support in older adults. J Dent. 2005;33:131-137.
  • 11. Boom H, Van Spronsen P, Van Ginkel F, Van Schijndel R, Castelijns J, Tuinzing D. A comparison of human jaw muscle cross-sectional area and volume in long-and short-face subjects, using MRI. Arch Oral Biol. 2008;53:273-281.
  • 12. Eichner K. Uber eine Gruppeneinteilung des Luckengebisse fur die Prothetik. Deutsche Zahnarztliche Zeitschriff. 1955;10:1831-1834.
  • 13. Paknahad M, Shahidi S, Akhlaghian M, Abolvardi M. Is mandibular fossa morphology and articular eminence inclination associated with temporomandibular dysfunction? J Dent. 2016;17:134.
  • 14. Serindere G, Aktuna Belgin C, Serindere M. Volumetric and morphological analysis of condyle and glenoid fossa on computed tomography. Eur Arch Otorhinolaryngol. 2020;277:2581-2587.
  • 15. Altan Şallı G, Öztürkmen Z. Semi-automated three-dimensional volumetric evaluation of mandibular condyles. Oral Radiol. 2021;37:66-73.
  • 16. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31:1116-1128.
  • 17. Bayram M, Kayipmaz S, Sezgin ÖS, Küçük M. Volumetric analysis of the mandibular condyle using cone beam computed tomography. Eur J Radiol. 2012;81:1812-1816.
  • 18. Tecco S, Saccucci M, Nucera R, Polimeni A, Pagnoni M, Cordasco G. Condylar volume and surface in Caucasian young adult subjects. BMC Med Imaging. 2010;10:1-10.
  • 19. Nguyen MS, Saag M, Jagomägi T, Nguyen QH, Voog-Oras Ü. The impact of occlusal support on temporomandibular disorders: a literature review. Proceedings of Singapore Healthcare. 2022;31:20101058211023779.
  • 20. Mathew AL, Sholapurkar AA, Pai KM. Condylar changes and its association with age, TMD, and dentition status: a cross-sectional study. Int J Dent. 2011;2011.
  • 21. Al-koshab M, Nambiar P, John J. Assessment of condyle and glenoid fossa morphology using CBCT in South-East Asians. PloS one. 2015;10:e0121682.
  • 22. Ishibashi H, Takenoshita Y, Ishibashi K, Oka M. Age-related changes in the human mandibular condyle: a morphologic, radiologic, and histologic study. J Oral Maxillofac Surg. 1995;53:1016-1023.
  • 23. Alexiou K, Stamatakis H, Tsiklakis K. Evaluation of the severity of temporomandibular joint osteoarthritic changes related to age using cone beam computed tomography. Dentomaxillofac Radiol. 2009;38:141-147.
  • 24. Zain-Alabdeen E, Alsadhan R. A comparative study of accuracy of detection of surface osseous changes in the temporomandibular joint using multidetector CT and cone beam CT. Dentomaxillofac Radiol. 2012;41:185-191.
  • 25. Vallaeys K, Kacem A, Legoux H, Le Tenier M, Hamitouche C, Arbab-Chirani R. 3D dento-maxillary osteolytic lesion and active contour segmentation pilot study in CBCT: semi-automatic vs manual methods. Dentomaxillofac Radiol. 2015;44:20150079.
  • 26. Dastidar P, Heinonen T, Numminen J, Rautiainen M, Laasonen E. Semi-automatic segmentation of computed tomographic images in volumetric estimation of nasal airway. Eur Arch Otorhinolaryngol. 1999;256:192-198.
  • 27. Liu Q, Wei X, Guan J, Wang R, Zou D, Yu L. Assessment of condylar morphology and position using MSCT in an Asian population. Clin Oral Investig. 2018;22:2653-2661.
  • 28. Song W-C, Kim J-I, Kim S-H, Shin D-H, Hu K-S, Kim H-J. Female-to-male proportions of the head and face in Koreans. J Craniofac Surg. 2009;20:356-361.
  • 29. Li G, Qian H, Guo S, Wang D, Sun C, Du Y. Assessment of aging characteristics of female condylar trabecular structure by cone-beam computed tomography. Oral Radiol. 2019;35:16-22.
  • 30. Levartovsky S, Gavish A, Nagar Y, Sarphati L, Levartovsky D, Winocur E. The association between dental status and temporomandibular osseous changes: a morphological study on R oman–B yzantine skeletons. J Oral Rehabil. 2012;39:888-895.
  • 31. Ahmed NF, Samir SM, Ashmawy MS, Farid MM. Cone beam computed tomographic assessment of mandibular condyle in Kennedy class I patients. Oral Radiol. 2020;36:356-364.
  • 32. Saccucci M, D’Attilio M, Rodolfino D, Festa F, Polimeni A, Tecco S. Condylar volume and condylar area in class I, class II and class III young adult subjects. Head Face Med. 2012;8:1-8.
  • 33. Ceratti C, Maspero C, Consonni D, Caprioglio A, Connelly ST, Inchingolo F. Cone-beam computed tomographic assessment of the mandibular condylar volume in different skeletal patterns: a retrospective study in adult patients. Bioengineering. 2022;9:102.
  • 34. Ueki K, Nakagawa K, Takatsuka S, Yamamoto E, Laskin DM. Comparison of the stress direction on the TMJ in patients with class I, II, and III skeletal relationships. Orthod Craniofac Res. 2008;11:43-50.
  • 35. Somay E, Yilmaz B. Comparison of clinical and magnetic resonance imagining data of patients with temporomandibular disorders. Niger J Clin Pract. 2020;23:376-380.
  • 36. Alarabawy RA, El Ahwal HM, El Sergany MAES, Mehrez WW. Magnetic resonance imaging evaluation of temporo-mandibular joint disorders, criterial analysis and significance in comparison with arthroscopy. Egypt J Radiol Nucl Med. 2016;47:467-475.

Three-Dimensional Analysis of Age and Eichner Index-Related Volumetric Changes in Mandibular Condyles

Year 2024, Volume: 27 Issue: 3, 194 - 200, 30.09.2024

Elif Meltem Aslan Öztürk , Aslıhan Artaş

https://doi.org/10.7126/cumudj.1473635

Abstract

Objective: The impact of condyle volume is influenced by the presence of posterior occlusal support and age. This study aimed to retrospectively explore how age, Eichner index, and gender influence condyle volume in three dimensions, through the classification of occlusal support using the Eichner index.
Material and Methods: Cone-beam computed tomography (CBCT) images of 232 patients (107 males and 125 females) aged 18-76 years were retrospectively analysed. ITK-SNAP open-source software was utilized to measure volume of condyles with semi-automated segmentation. CBCT images were analyzed based on age, gender, and the status of posterior occlusal support. Posterior occlusal support status was assessed by categorizing it into three groups according to the Eichner index: A) indicating no loss of posterior occlusal support; B) representing one to three units of occlusal support loss; and C) denoting four units of posterior occlusal support loss. For normality, Kolmogorov Smirnov test was performed and Pearson test was used to determine the correlations of continuous variables. Student's t test was used to investigate the difference between age and gender, and paired t test was used to evaluate the difference between left and right volume. P < 0.05 was considered significant.
Results: There was no statistically significant difference between the mean right and left condyle volume (p > 0.05). The mean condyle volume was higher in males than females, but this difference was not statistically significant (p > 0.05). A statistically significant negative correlation was detected between age and condyle volume (p < 0.05). Age and Eichner index were statistically significantly positively correlated (p < 0.05). A statistically significant negative correlation was determined between condyle volume and Eichner index (p < 0.05).
Conclusion: Volumetric measurement of the condyles using CBCT and comparison with Eichner index is crucial to assess abnormalities and bony changes affecting the TMJ in association with occlusal support and to examine and prevent complications. Although it was found that the condyle volume decreased significantly with increasing age and decreasing occlusal support, no significant difference was revealed between genders in the present study.

Keywords

Condyle volume semi-automated segmentation posterior occlusal support Eichner index cone-beam computed tomography

References

  • 1. Safi A-F, Kauke M, Grandoch A, Nickenig H-J, Zöller JE, Kreppel M. Age-related volumetric changes in mandibular condyles. J Craniofac Surg. 2018;29:510-513.
  • 2. Krisjane Z, Urtane I, Krumina G, Bieza A, Zepa K, Rogovska I. Condylar and mandibular morphological criteria in the 2D and 3D MSCT imaging for patients with Class II division 1 subdivision malocclusion. Stomatologija. 2007;9:67-71.
  • 3. Papadaki ME, Tayebaty F, Kaban LB, Troulis MJ. Condylar resorption. Oral Maxillofac Surg Clin North Am. 2007;19:223-234.
  • 4. Mercuri LG. Osteoarthritis, osteoarthrosis, and idiopathic condylar resorption. Oral Maxillofac Surg Clin North Am. 2008;20:169-183.
  • 5. Enomoto A, Watahiki J, Yamaguchi T, Irie T, Tachikawa T, Maki K. Effects of mastication on mandibular growth evaluated by microcomputed tomography. Eur J Orthod. 2010;32:66-70.
  • 6. Saccucci M, Polimeni A, Festa F, Tecco S. Do skeletal cephalometric characteristics correlate with condylar volume, surface and shape? A 3D analysis. Head Face Med. 2012;8:1-8.
  • 7. Hatch J, Shinkai R, Sakai S, Rugh J, Paunovich E. Determinants of masticatory performance in dentate adults. Arch Oral Biol. 2001;46:641-648.
  • 8. Paknahad M, Khojastepour L, Tabatabaei S, Mahjoori-Ghasrodashti M. Association between condylar bone changes and eichner index in patients with temporomandibular dysfunction: A cone beam computed tomography study. J Dent. 2023;24:12.
  • 9. Ikebe K, Matsuda K-i, Kagawa R, Enoki K, Okada T, Yoshida M. Masticatory performance in older subjects with varying degrees of tooth loss. J Dent. 2012;40:71-76.
  • 10. Ikebe K, Nokubi T, Morii K, Kashiwagi J, Furuya M. Association of bite force with ageing and occlusal support in older adults. J Dent. 2005;33:131-137.
  • 11. Boom H, Van Spronsen P, Van Ginkel F, Van Schijndel R, Castelijns J, Tuinzing D. A comparison of human jaw muscle cross-sectional area and volume in long-and short-face subjects, using MRI. Arch Oral Biol. 2008;53:273-281.
  • 12. Eichner K. Uber eine Gruppeneinteilung des Luckengebisse fur die Prothetik. Deutsche Zahnarztliche Zeitschriff. 1955;10:1831-1834.
  • 13. Paknahad M, Shahidi S, Akhlaghian M, Abolvardi M. Is mandibular fossa morphology and articular eminence inclination associated with temporomandibular dysfunction? J Dent. 2016;17:134.
  • 14. Serindere G, Aktuna Belgin C, Serindere M. Volumetric and morphological analysis of condyle and glenoid fossa on computed tomography. Eur Arch Otorhinolaryngol. 2020;277:2581-2587.
  • 15. Altan Şallı G, Öztürkmen Z. Semi-automated three-dimensional volumetric evaluation of mandibular condyles. Oral Radiol. 2021;37:66-73.
  • 16. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31:1116-1128.
  • 17. Bayram M, Kayipmaz S, Sezgin ÖS, Küçük M. Volumetric analysis of the mandibular condyle using cone beam computed tomography. Eur J Radiol. 2012;81:1812-1816.
  • 18. Tecco S, Saccucci M, Nucera R, Polimeni A, Pagnoni M, Cordasco G. Condylar volume and surface in Caucasian young adult subjects. BMC Med Imaging. 2010;10:1-10.
  • 19. Nguyen MS, Saag M, Jagomägi T, Nguyen QH, Voog-Oras Ü. The impact of occlusal support on temporomandibular disorders: a literature review. Proceedings of Singapore Healthcare. 2022;31:20101058211023779.
  • 20. Mathew AL, Sholapurkar AA, Pai KM. Condylar changes and its association with age, TMD, and dentition status: a cross-sectional study. Int J Dent. 2011;2011.
  • 21. Al-koshab M, Nambiar P, John J. Assessment of condyle and glenoid fossa morphology using CBCT in South-East Asians. PloS one. 2015;10:e0121682.
  • 22. Ishibashi H, Takenoshita Y, Ishibashi K, Oka M. Age-related changes in the human mandibular condyle: a morphologic, radiologic, and histologic study. J Oral Maxillofac Surg. 1995;53:1016-1023.
  • 23. Alexiou K, Stamatakis H, Tsiklakis K. Evaluation of the severity of temporomandibular joint osteoarthritic changes related to age using cone beam computed tomography. Dentomaxillofac Radiol. 2009;38:141-147.
  • 24. Zain-Alabdeen E, Alsadhan R. A comparative study of accuracy of detection of surface osseous changes in the temporomandibular joint using multidetector CT and cone beam CT. Dentomaxillofac Radiol. 2012;41:185-191.
  • 25. Vallaeys K, Kacem A, Legoux H, Le Tenier M, Hamitouche C, Arbab-Chirani R. 3D dento-maxillary osteolytic lesion and active contour segmentation pilot study in CBCT: semi-automatic vs manual methods. Dentomaxillofac Radiol. 2015;44:20150079.
  • 26. Dastidar P, Heinonen T, Numminen J, Rautiainen M, Laasonen E. Semi-automatic segmentation of computed tomographic images in volumetric estimation of nasal airway. Eur Arch Otorhinolaryngol. 1999;256:192-198.
  • 27. Liu Q, Wei X, Guan J, Wang R, Zou D, Yu L. Assessment of condylar morphology and position using MSCT in an Asian population. Clin Oral Investig. 2018;22:2653-2661.
  • 28. Song W-C, Kim J-I, Kim S-H, Shin D-H, Hu K-S, Kim H-J. Female-to-male proportions of the head and face in Koreans. J Craniofac Surg. 2009;20:356-361.
  • 29. Li G, Qian H, Guo S, Wang D, Sun C, Du Y. Assessment of aging characteristics of female condylar trabecular structure by cone-beam computed tomography. Oral Radiol. 2019;35:16-22.
  • 30. Levartovsky S, Gavish A, Nagar Y, Sarphati L, Levartovsky D, Winocur E. The association between dental status and temporomandibular osseous changes: a morphological study on R oman–B yzantine skeletons. J Oral Rehabil. 2012;39:888-895.
  • 31. Ahmed NF, Samir SM, Ashmawy MS, Farid MM. Cone beam computed tomographic assessment of mandibular condyle in Kennedy class I patients. Oral Radiol. 2020;36:356-364.
  • 32. Saccucci M, D’Attilio M, Rodolfino D, Festa F, Polimeni A, Tecco S. Condylar volume and condylar area in class I, class II and class III young adult subjects. Head Face Med. 2012;8:1-8.
  • 33. Ceratti C, Maspero C, Consonni D, Caprioglio A, Connelly ST, Inchingolo F. Cone-beam computed tomographic assessment of the mandibular condylar volume in different skeletal patterns: a retrospective study in adult patients. Bioengineering. 2022;9:102.
  • 34. Ueki K, Nakagawa K, Takatsuka S, Yamamoto E, Laskin DM. Comparison of the stress direction on the TMJ in patients with class I, II, and III skeletal relationships. Orthod Craniofac Res. 2008;11:43-50.
  • 35. Somay E, Yilmaz B. Comparison of clinical and magnetic resonance imagining data of patients with temporomandibular disorders. Niger J Clin Pract. 2020;23:376-380.
  • 36. Alarabawy RA, El Ahwal HM, El Sergany MAES, Mehrez WW. Magnetic resonance imaging evaluation of temporo-mandibular joint disorders, criterial analysis and significance in comparison with arthroscopy. Egypt J Radiol Nucl Med. 2016;47:467-475.
There are 36 citations in total.

Details

Primary Language English
Subjects Oral and Maxillofacial Radiology
Journal Section Original Research Articles
Authors

Elif Meltem Aslan Öztürk 0000-0002-1737-9585

Aslıhan Artaş 0000-0001-6410-9126

Publication Date September 30, 2024
Submission Date April 26, 2024
Acceptance Date July 19, 2024
Published in Issue Year 2024Volume: 27 Issue: 3

Cite

EndNote Aslan Öztürk EM, Artaş A (September 1, 2024) Three-Dimensional Analysis of Age and Eichner Index-Related Volumetric Changes in Mandibular Condyles. Cumhuriyet Dental Journal 27 3 194–200.
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