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Modern methods of radiological diagnosis of osteoporosis. Part 2: cone-beam CT, magnetic resonance imaging, texture analysis: a review

https://doi.org/10.22328/2079-5343-2025-16-4-18-26

Abstract

Introduction: Osteoporosis is characterized by a decrease in bone mass and deterioration of bone microarchitectonics. Osteoporosis often remains undetected until the first pathologic fracture of vertebrae, proximal femur or other bones. With the rapidly aging world population, early diagnosis of osteoporosis has become an important public health issue.

Objective: To present current data on the methods of radiologic diagnosis of osteoporosis using cone-beam computed tomography, magnetic resonance imaging, and texture analysis.

Material and methods: We searched for scientific publications and clinical recommendations in the information-analytical systems eLIBRARY.RU and PubMed for 2005–2024 using the following keywords: osteoporosis, cone-beam CT, magnetic resonance imaging, texture analysis, bone mineral density.

Results: A total of 454 articles were analyzed, 31 of which were used for the review.

Conclusions: The methods of radiologic diagnostics of osteoporosis presented in this review have their own prospects for development and improvement. The analysis of scientific data on the described methods shows the undying interest in each of the methods.

About the Authors

V. S. Blinov
Ural State Medical University ; Verkhnepyshminskaya Central City Hospital named after P. D. Borodin
Russian Federation

Vladislav S. Blinov — Cand. of Sci. (Med.), Head of the X-ray diagnostic department; Assistant at the Department of Oncology and Radiologic Diagnostics

624090, Russia, Verkhnyaya Pyshma, st. Chaykovskogo, 32 

620028, Ekaterinburg, st. Repina, 3 



Yu. S. Kitaeva
Ural State Medical University
Russian Federation

Yulia S. Kitaeva — Cand. of Sci. (Med.), Assistant of the Department of Propaedeutics of Internal Diseases 

620028, Ekaterinburg, st. Repina 



E. A. Praskurnichiy
Russian National Research Medical University named after. N. I. Pirogov
Russian Federation

Evgeniy A. Praskurnichiy — Dr. of Sci. (Med.), Head of Department of Therapy, Medical and Biological University  

117997, Moscow, st. Ostrovityanova, 1 



M. A. Chibisova
North-Western State Medical University named after I. I. Mechnikov
Russian Federation

Marina A. Chibisova — Dr. of Sci. (Med.), Professor, Professor of the Department of Clinical Dentistry, Professor of the Department of Pediatric and Therapeutic Dentistry named after Y. A. Fedorov

191015, St. Petersburg, st. Kirochnaya, 41 



References

1. Chibisova M.A., Batukov N.M. Methods of X-ray examination and modern radiation diagnostics used in dentistry. Institut stomatologii, 2020, No. 3 (88), pp. 24–33 (In Russ.).

2. Isayev A., Velieva N., Isedisha L. et al. Cone-Beam Computed Tomography as a Prediction Tool for Osteoporosis in Postmenopausal Women: A Systematic Literature Review // Diagnostics (Basel). 2023. No. 13 (6). doi: https://doi.org/10.3390/diagnostics13061027.

3. Hossain Sh.D., Petraikin A.V., Muraev A.A., Danaev A.B. et al. Bone mineral density radiopaque templates for cone beam computed tomography and multidetector computed tomography. Digital Diagnostics, 2023, No. 4 (3), pp. 292−305 (In Russ.). doi: https://doi.org/10.17816/DD501771.

4. Parsa A., Ibrahim N., Hassan B. et. al. Reliability of voxel gray values in cone beam computed tomography for preoperative implant planning assessment // Int. J. Oral. Maxillofac. Implants. 2012. No. 27. Р. 1438–1442. PMID: 23189294.

5. Arisan V., Karabuda Z.C., Avsever H., Ozdemir T. Conventional multi-slice computed tomography (CT) and cone-beam CT (CBCT) for computer-assisted implant placement. Part I: relationship of radiographic gray density and implant stability // Clin. Implant. Dent. Relat. Res. 2013. No. 15. Р. 893–906. doi: https://doi.org/10.1111/j.1708-8208.2011.00436.x.

6. Pauwels R., Nackaerts O., Bellaiche N. et al. Variability of dental cone beam CT grey values for density estimations // Br. J. Radiol. 2013. No. 86. Р. 1–9. doi: https://doi.org/10.1259/bjr.20120135.

7. Reeves T.E., Mah P., McDavid W.D. Deriving Hounsfield units using grey levels in cone beam CT: a clinical application // Dentomaxillofac. Radiol. 2012. No. 41. P. 500–508. doi: https://doi.org/10.1259/dmfr/31640433.

8. Cassetta M., Stefanelli L.V., Pacifici A., Pacifici L., Barbato E. How accurate is CBCT in measuring bone density? A comparative CBCT-CT in vitro study // Clin. Implant Dent. Relat. Res. 2014. No. 16 (4). P. 471–478. doi: https://doi.org/10.1111/cid.12027.

9. Barngkgei I., Al Haffar I., Khattab R. Osteoporosis prediction from the mandible using cone-beam computed tomography // Imaging Sci. Dent. 2014. No. 44. P. 263–271. doi: https://doi.org/10.5624/isd.2014.44.4.263.

10. Brasileiro C.B., Chalub L.H., Abreu M.G. et al. Use of cone beam computed tomography in identifying postmenopausal women with osteoporosis // Arch. Osteoporos. 2017. No. 12. doi: https://doi.org/10.1007/s11657-017-0314-7.

11. Barra S.G., Gomes I.P., Amaral T.M.P. et al. New mandibular indices in cone beam computed tomography to identify low bone mineral density in postmenopausal women // Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2021. No. 131 (3). P. 347–355. doi: https://doi.org/10.1016/j.oooo.2020.07.016.

12. Koh K.J., Kim K.A. Utility of the computed tomography indices on cone beam computed tomography images in the diagnosis of osteoporosis in women // Imaging Sci. Dent. 2011. No. 41. P. 101–106. doi: https://doi.org/10.5624/isd.2011.41.3.101.

13. Mostafa R.A., Arnout E.A., Abo El-Fotouh M.M. Feasibility of cone beam computed tomography radiomorphometric analysis and fractal dimension in assessment of postmenopausal osteoporosis in correlation with dual X-ray absorptiometry // Dentomaxillofac. Radiol. 2016. No. 45. P. 20160212. doi: https://doi.org/10.1259/dmfr.20160212.

14. Kulakov A.A., Kasparov A.S., Porfenchuk D.A. Factors affecting osteointegration and the use of early functional load to reduce the duration of treatment in dental implantation. Stomatology, 2019, No. 4, pp. 107–115 (In Russ.). doi: https://doi.org/10.17116/stomat201998041107.

15. Zarb G.U., Albrektsson T. Patient selection and preparation. Tissue integrated prostheses: osseointegration in clinical dentistry // Quintessence Publisher. 1985. P. 199–209.

16. Tang G.Y., Lv Z.W., Tang R.B. et al. Evaluation of MR spectroscopy and diffusion-weighted MRI in detecting bone marrow changes in postmenopausal women with osteoporosis // Clin. Radiol. 2010. No. 65. P. 377–381. doi: https://doi.org/10.1016/j.crad.2009.12.011.

17. Bandirali M., Di Leo G., Papini G.D. et al. A new diagnostic score to detect osteoporosis in patients undergoing lumbar spine MRI // Eur. Radiol. 2015. No. 25. P. 2951–2959. doi: https://doi.org/10.1007/s00330-015-3699-y.

18. Shayganfar A., Khodayi M., Ebrahimian S., Tabrizi Z. Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging // Br. J. Radiol. 2019. No. 92 (1097). P. 20180774. doi: https://doi.org/10.1259/bjr.20180774.

19. Chen Y., Mei X., Liang X. et al. Application of magnetic resonance image compilation (MAGiC) in the diagnosis of middle-aged and elderly women with osteoporosis // BMC Med. Imaging. 2023. No. 23 (1). pp. 63. doi: https://doi.org/10.1186/s12880-023-01010-9.

20. Kim D., Kim S.K., Lee S.J. et al. Simultaneous Estimation of the Fat Fraction and R2* Via T2*-Corrected 6-Echo Dixon Volumetric Interpolated Breath-hold Examination Imaging for Osteopenia and Osteoporosis Detection: Correlations with Sex, Age, and Menopause // Korean J. Radiol. 2019. No. 20 (6). P. 916–930. doi: https://doi.org/10.3348/kjr.2018.0032.

21. Lukashew A.D., Akhatov A.F., Ryzhkin S.A., Mikhailov M.K., Zalaeva D.R. Application of DIXON MRI sequencing in the diagnosis of changes in the spongy substance of vertebral bodies in comparison with osteodensitometry data. Medical Visualization, 2023, No. 27 (3), pp. 76–83 (In Russ.). doi: https://doi.org/10.24835/1607-0763-1201.

22. Dietrich O., Geith T., Reiser M.F., Baur-Melnyk A. Diffusion imaging of the vertebral bone marrow // NMR Biomed. 2017. No. 30 (3). doi: https://doi.org/10.1002/nbm.3333.

23. Tang G.Y., Lv Z.W., Tang R.B. et al. Evaluation of MR spectroscopy and diffusion-weighted MRI in detecting bone marrow changes in postmenopausal women with osteoporosis // Clin. Radiol. 2010. No. 65 (5). P. 377–381. doi: https://doi.org/10.1016/j.crad.2009.12.011.

24. Griffith J.F., Yeung D.K., Antonio G.E. et al. Vertebral marrow fat content and diffusion and perfusion indexes in women with varying bone density: MR evaluation // Radiology. 2006. No. 241 (3). P. 831–838. doi: https://doi.org/10.1148/radiol.2413051858.

25. Ueda Y., Miyati T., Ohno N. et al. Apparent diffusion coefficient and fractional anisotropy in the vertebral bone marrow // J. Magn. Reson. Imaging. 2010. No. 31 (3). P. 632–635. doi: https://doi.org/10.1002/jmri.22073.

26. Dietrich O., Geith T., Reiser M.F., Baur-Melnyk A. Diffusion imaging of the vertebral bone marrow // NMR Biomed. 2017. No. 30 (3). doi: https://doi.org/10.1002/nbm.3333.

27. Guglielmi G., Muskarella S. Integred imaging approach to osteoporosis: state-of-the-art review and update // Radiographiks. 2011. No. 31 (5). P. 1343–1364. doi: https://doi:10.1148/rg.315105712.

28. Cavalcante D.S, Silva P.G. et al. Is jaw fractal dimension a reliable biomarker for osteoporosis screening? A systematic review and meta-analysis of diagnostic test accuracy studies // Dentomaxillofacial Radiology. 2022. No. 51. Р. 210365. doi: https://doi.org/10.1259/dmfr.20210365.

29. 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. 2012. No. 23. P. 1631–1636. doi: https://doi.org/10.1007/s00198-011-1678-y.

30. Kavitha M.S., An S.Y. et al. Texture analysis of mandibular cortical bone on digital dental panoramic radiographs for the diagnosis of osteoporosis in Korean women // Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2015. No. 119. P. 346–356. doi: https://doi.org/10.1016/j.oooo.2014.11.009.

31. Franciotti R., Moharrami M., Quaranta A. et al. Use of fractal analysis in dental images for osteoporosis detection: a systematic review and meta-analysis // Osteoporos Int. 2021. No. 32 (6). P. 1041–1052. doi: https://doi.org/10.1007/s00198-021-05852-3.


Review

For citations:


Blinov V.S., Kitaeva Yu.S., Praskurnichiy E.A., Chibisova M.A. Modern methods of radiological diagnosis of osteoporosis. Part 2: cone-beam CT, magnetic resonance imaging, texture analysis: a review. Diagnostic radiology and radiotherapy. 2025;16(4):18-26. (In Russ.) https://doi.org/10.22328/2079-5343-2025-16-4-18-26

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