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A computer aided diagnosis system for measurement of mandibular cortical thickness on dental panoramic radiographs in prediction of women with low bone mineral density

  • D. KathirveluEmail author
  • P. Vinupritha
  • V. Kalpana
Image & Signal Processing
  • 52 Downloads
Part of the following topical collections:
  1. Image & Signal Processing

Abstract

Osteoporosis detection at earlier stages can enhance the life span of an elderly individual. The aim of the study is to perform semi-automated measurement of mandibular cortical thickness (MCT) on a dental panoramic radiograph (DPR) and thereby to predict the risk of low BMD among the studied population. The study involved 76 women (mean age: 57.2 ± 12.6 years). The DPR was obtained using KODAK 8000C system. The BMD of right total hip (T-BMD) was obtained using DPX Prodigy Dual-energy X-ray absorptiometry (DXA) Scanner. The DPR obtained were subjected to image processing techniques to perform MCT measurement. The region of interest was manually selected around the mental foramen and enhanced using a median filter. The Ostu segmentation was performed and connected component labelling operation was performed to determine the lower boundary by finding the contour with maximum area. Subsequently, the haar wavelet operation was carried out to find the magnitude and thereby select the upper delineating cortical boundary. The Pearson test results revealed (r = 0.96, p < 0.01) for the standard (manual) MCT measurement against the MCT measured using the proposed semi-automated scheme. ROC analysis revealed that MCT = 2.5 mm could be an optimal threshold in spotting individuals at risk of low BMD. The results of the study revealed that the MCT measured on a DPR using the proposed approach could be helpful for identifying individuals at risk of low BMD.

Keywords

DPR Low BMD MCT Osteoporosis Ostu Segmentation DXA 

Notes

Acknowledgments

The authors wish to express their deep sense of gratitude to the management of SRM Hospital and Research Centre for providing the required facilitative infrastructure. The authors humbly wish to express their heartfelt sincere thanks to Dr. M. Anburajan who taught all nuances of osteoporosis research work. The authors also wish to thank Dr. V. Sapthagirivasan for his knowledge sharing and mentoring during the learning phases of research.

Funding

The study was not supported by any funding agencies. The expenditure incurred for the study was borne by the authors.

Compliance with Ethical Standards

The study was conducted with the consent of institutional ethical committee (SRMIST- Institutional Ethical Committee).

This article is original and has not been published by any other journal.

Conflict of Interest

The authors declare that they have no conflict of interest.

Informed Consent

An informed consent was obtained from all participants in their native language.

References

  1. 1.
    The International Osteoporosis Foundation. The Asian audit: epidemiology, costs and burden of osteoporosis in Asia. The International Osteoporosis Foundation, 2009.Google Scholar
  2. 2.
    Beloyartseva, M., Mithal, A., Kaur, P., Kalra, S., Baruah, M. P., Mukhopadhyay, S., Bantwal, G., and Bandgar, T. R., Widespread vitamin D deficiency among Indian health care professionals. Arch Osteoporos 1-2:187–192, 2012.CrossRefGoogle Scholar
  3. 3.
    Malhotra, N., and Mithal, A., Osteoporosis in Indians. Indian J Med Res 127(3):263–268, 2008.PubMedGoogle Scholar
  4. 4.
    Shatrugna, V., Kulkarni, B., Kumar, P. A., Rani, K. U., and Balakrishna, N., Bone status of Indian women from a low-income group and its relationship to the nutritional status. Osteoporos Int 16:18–27, 2005.CrossRefGoogle Scholar
  5. 5.
    Taguchi, A., Triage screening for osteoporosis in dental clinics using panoramic radiographs – a review. Oral Disease 16(4):316–327, 2010.CrossRefGoogle Scholar
  6. 6.
    Karayianni, K., Homer, K., Mitsea, A. et al., Accuracy in osteoporosis diagnosis of a combination of mandibular cortical width measurement on dental panoramic radiographs and a clinical risk index (OSIRIS): the OSTEODENT project. Bone 40(1):223–229, 2007.CrossRefGoogle Scholar
  7. 7.
    Alman, A. C., Johnson, L. R., Calverley, D. C. et al., Diagnostic capabilities of fractal dimension and mandibular cortical width to identify men and women with decreased bone mineral density. Osteoporos Int 23(5):1631–1636, 2012.CrossRefGoogle Scholar
  8. 8.
    Benson, B. W., Prihoda, T. J., and Glass, B. J., Variations in adult cortical bone mass as measured by a panoramic mandibular index. Oral Surg Oral Med Oral Pathol 71(3):349–356, 1991.CrossRefGoogle Scholar
  9. 9.
    Khojastehpour, L., Shahidi, S. H., Barghan, S. et al., Efficacy of panoramic mandibular index in diagnosing osteoporosis in women. J Dent Tehran Univ Med Sci 6(1):11–15, 2009.Google Scholar
  10. 10.
    Krejc, C. B., and Bissada, N. F., Women’s health issues and their relationship to periodontitis. J Am Dent Assoc 133(3):323–329, 2002.CrossRefGoogle Scholar
  11. 11.
    Jonasson, G., Bankvall, G., and Kiliaridis, S., Estimation of skeletal bone mineral density by means of the trabecular pattern of the alveolar bone, its interdental thickness, and the bone mass of the mandible. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 92(3):346–352, 2001.CrossRefGoogle Scholar
  12. 12.
    Jeffcoat, M. K., Lewis, C. E., Reddy, M. S. et al., Postmenopausal bone loss and its relationship to oral bone loss. Periodontol 23:94–102, 2000.CrossRefGoogle Scholar
  13. 13.
    Taguchi, A., Tanimoto, K., Suei, Y. et al., Tooth loss and mandibular osteopenia. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 79(1):127–132, 1995.CrossRefGoogle Scholar
  14. 14.
    Klemetti, E., Collin, H. L., Forss, H., Markkanen, H., and Lassila, V., Mineral status of skeleton and advanced periodontal disease. J. Clin. Periodontol 21:184–188, 1994.CrossRefGoogle Scholar
  15. 15.
    Klemetti, E., and Vainio, P., Effect of bone mineral density in skeleton and mandible on extraction of teeth and clinical alveolar height. J. Prosthet Dent 70:21–25, 1993.CrossRefGoogle Scholar
  16. 16.
    Sapthagirivasan, V., and Anburajan, M., Diagnosis of osteoporosis by extraction of trabecular features from hip radiographs using support vector machine: an investigation panorama with DXA. Comput Biol Med 43(11):1910–1919, 2013.CrossRefGoogle Scholar
  17. 17.
    Kavitha, M. S., Asano, A., Taguchi, A. et al., Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system. BMC Med Img 12(1):1–11, 2012.CrossRefGoogle Scholar
  18. 18.
    Muramatsu, C., Matsumoto, T., Hayashi, T. et al., Automated measurement of mandibular cortical width on dental panoramic radiographs. Int J Comput Assist Radiol Surg 8(6):877–885, 2013.CrossRefGoogle Scholar
  19. 19.
    Kathirvelu, D., and Anburajan, M., Prediction of low bone mass using a combinational approach of cortical and trabecular bone measures from dental panoramic radiographs. Proc Inst Mech Eng H. 228(9):890–898, 2014.CrossRefGoogle Scholar
  20. 20.
    Arifin, A. Z., Asano, A., Taguchi, A., Nakamoto, T., Ohtsuka, M., Tsuda, M., and KudoY, T. K., Computer-aided system for measuring the mandibular cortical width on dental panoramic radiographs in identifying postmenopausal women with low bone mineral density. Osteoporos Int 17:753–759, 2006.CrossRefGoogle Scholar
  21. 21.
    Mohajery, M., and Brooks, S. L., Oral radiographs in the detection of early signs of osteoporosis. Oral Surg Oral Med Oral Pathol 73:112–117, 1992.CrossRefGoogle Scholar
  22. 22.
    Damilakis, J., and Vlasiadis, K., Have panoramic indices the power to identify women with low BMD at the axial skeleton? Phys Med 27(1):39–43, 2011.CrossRefGoogle Scholar
  23. 23.
    Arifin, A. Z., Asano, A., Taguchi, A., Nakamoto, T., Ohtsuka, M. et al., Computer-aided system for measuring the mandibular cortical width on dental panoramic radiographs in identifying postmenopausal women with low bone mineral density. Osteoporos Int. 17(5):753–759, 2006.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringSRM Institute of Science and TechnologyKattankulathurIndia
  2. 2.Department of Chemistry, C. Kandasamy Naidu college for womenCuddaloreIndia

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