The Ability of Cone Beam Computed Tomography to Predict Osteopenia and Osteoporosis via Radiographic Density Derived from Cervical Vertebrae

Document Type : Original Article

Authors

1 Department of Oral and Maxillofacial Radiology, Dental School, Urmia University of Medical Sciences, Urmia, Iran

2 Department of Endodontics, Dental School, Urmia University of Medical Sciences, Urmia, Iran

Abstract

Background and Aim: Osteoporosis (OP) is defined as a bone density-related disorder identified by a reduction of the microstructure quality of bone with increased fracture risk. The current study aimed to evaluate the ability of the cone-beam computed tomography (CBCT) imaging method to predict osteoporosis and osteopenia using Radiographic Density (RD) values derived from cervical vertebrae.
Materials and methods: This study was a descriptive-cross sectional study conducted on 54 research units suffering from osteopenia and osteoporosis in the hip, aged 42-72 years. Finally, the values of RD from the lateral mass of the first cervical vertebra on both right and left side and dens and body of the second cervical vertebrae were calculated by NNT viewer software.
Results: Comparing all values of RD obtained from the first cervical vertebrae and second cervical vertebrae revealed a statistically significant difference between the three groups (P-value <0.05).It was also found that the most accurate prediction of osteoporosis was related to the values of RD from body of C2 so that the accuracy equals 99% and cut-off point (Cut-point) of it was 293, respectively. Also, the most accurate prediction of hip-related osteopenia was for the values of RD from the body of C2 so that the accuracy is88%, and the cut-off point is also 375.
Conclusion: According to the findings of this study, osteoporosis and osteopenia status can be predicted through RD value amounts related to a body part of the second cervical vertebra, which was more precise than the other parts.

Keywords

References

  1. Consensus, N., Development panel on osteoporosis: prevention, diagnosis and therapy. Jama, 2001. 285(6): p. 785-795.
  2. Riera-Espinoza, G., Epidemiología de la osteoporosis en Latino América. Salud pública de México, 2009. 51: p. s52-s55.
  3. Johnell, O. and J. Kanis, Epidemiology of osteoporotic fractures. Osteoporosis international, 2005. 16(2): p. S3-S7.
  4. Cummings, S.R. and L.J. Melton, Epidemiology and outcomes of osteoporotic fractures. The Lancet, 2002. 359(9319): p. 1761-1767.
  5. Cooper, C., Epidemiology of osteoporosis. Osteoporosis International, 1999. 9(8): p. S2-S8.
  6. Pajouhi, M., et al., Bone Mineral Density in 10 to75 Year-Old Iranian Healthy Women: Population Base Study. Iranian Journal of Public Health, 2004: p. 57-63.
  7. Link, T.M., Osteoporosis imaging: state of the art and advanced imaging. Radiology, 2012. 263(1): p. 3-17.
  8. Siu, W.S., L. Qin, and K.S. Leung, pQCT bone strength index may serve as a better predictor than bone mineral density for long bone breaking strength. Journalof bone and mineral metabolism, 2003. 21(5): p. 316- 322.
  9. Eastell, R., Treatment of postmenopausal osteoporosis. New England journal of medicine, 1998. 338(11): p. 736-746.
  10. Organization, W.H., Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: report of a WHO study group [meeting held in Rome from 22 to 25 June 1992]. 1994.
  11. Lewiecki, E.M., et al., Official positions of the international society for clinical densitometry. The Journal of Clinical Endocrinology & Metabolism, 2004. 89(8): p. 3651-3655.
  12. Nomura, Y., et al., Stability of voxel values from cone‐beam computed tomography for dental use in evaluating bone mineral content. Clinical oral implants research, 2013. 24(5): p. 543-548.
  13. Mozzo, P., et al., A new volumetric CT machine for dental imaging based on the cone-beam technique: preliminary results. European radiology, 1998. 8(9): p. 1558-1564.
  14. Bornstein, M.M., et al., Cone beam computed tomography in implant dentistry: a systematic review focusing on guidelines, indications, and radiation dose risks. International journal of oral & maxillofacial implants, 2014. 29.
  15. Hua, Y., et al., Bone quality assessment based on cone beam computed tomography imaging. Clinical oral implants research, 2009. 20(8): p. 767-771.
  16. Spin-Neto, R., E. Gotfredsen, and A. Wenzel, Standardized method to quantify the variation in voxel value distribution in patient-simulated CBCT data sets. Dentomaxillofacial Radiology, 2014. 44(2): p. 20140283.
  17. Kasturi, G.C., D.X. Cifu, and R.A. Adler, A review of osteoporosis: Part I. Impact, pathophysiology, diagnosis and unique role of the physiatrist. PM&R, 2009. 1(3): p. 254-260.
  18. Genant, H., K. Engelke, and S. Prevrhal, Advanced CT bone imaging in osteoporosis. Rheumatology, 2008. 47(suppl 4): p. iv9-iv16.
  19. Naitoh, M., et al., Measurement of mandibles with micro focus x-ray computerized tomography and compact computerized tomography for dental use. International Journal of Oral & Maxillofacial Implants, 2004. 19(2).
  20. White, S.C. and M.J. Pharoah, The evolution and application of dental maxillofacial imaging modalities. Dental Clinics of North America, 2008. 52(4): p. 689-705.
  21. Barngkgei, I., I. Al Haffar, and R. Khattab, Osteoporosis prediction from the mandible using cone-beam computed tomography. Imaging science in dentistry, 2014. 44(4): p. 263-271.
  22. Pauwels, R., et al., CBCT-based bone quality assessment: are Hounsfield units applicable? Dentomaxillofacial Radiology, 2014. 44(1): p. 20140238.
International Journal of Scientific Research in Dental and Medical Sciences
Volume 1, Issue 2
June 2019
Pages 18-22

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History

  • Receive Date: 01 June 2019
  • Revise Date: 22 June 2019
  • Accept Date: 23 June 2019

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