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


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Volume 1, Issue 2
June 2019
Pages 18-22
  • Receive Date: 01 June 2019
  • Revise Date: 22 June 2019
  • Accept Date: 23 June 2019
  • First Publish Date: 23 June 2019