Osteoporosis detection using radiomorphometric examination and fractal dimensions through cone-beam computed tomography

https://doi.org/10.22146/majkedgiind.74535

Efie Mariyam Nursari(1), Bramma Kiswanjaya(2*), Menik Priaminiarti(3), Hanna H Bachtiar-Iskandar(4)

(1) Dentomaxillofacial Radiology Specialty Program, Faculty of Dentistry, Universitas Indonesia, Jakarta
(2) Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Indonesia, Jakarta
(3) Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Indonesia, Jakarta
(4) Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Indonesia, Jakarta
(*) Corresponding Author

Abstract


Cone-beam computed tomography (CBCT) is becoming more widely used in the field of dentomaxillofacial radiography, but its utility for bone quality assessment is still limited. This study was conducted to describe the use of radiomorphometric examination and fractal dimensions (FDs) for osteoporosis risk detection through CBCT in elderly patients. Medical databases (PubMed, Scopus, Elsevier, and Directory of Open Access Journals (DOAJ)) were searched using the keywords osteoporosis, radiomorphometric, fractal dimension, and fractal analysis. The search limits applied were available full-text articles, publication years 2012-2021, and articles published available in English. Then, the articles included were systematically reviewed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A total of four studies were included in this review. Seven radiomorphometric indices were used, and most indices were adopted from panoramic radiographs, such as the computed tomography
cortical index, computed tomography mental index, computed tomography index, and four other indices along the mandible, which are the S (symphysis), A (anterior), M (molar), and P (posterior) indices. All of the radiomorphometric studies show similar results. These indices can identify osteoporosis-related changes and are useful as osteoporosis screening tools on CBCT. However, all FD studies show different methods and discover heterogeneous results. Radiomorphometric measurement methods in CBCT can be used to detect patients at risk for osteoporosis. The FD analysis method still finds heterogeneous research results, so it is recommended to standardize the method in terms of the shape, size, and location of the region of interest.


Keywords


cone-beam computed tomography; fractals; mandible; osteoporosis; radiomorphometric

Full Text:

PDF


References

1. Mostafa RA, Arnout EA, El-Fotouh MMA. 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; 45(7): 1–8. doi: 10.1259/dmfr.20160212

2. Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C. The epidemiology of
osteoporosis. Br Med Bull. 2020; 133(1): 105–117. doi: 10.1093/bmb/ldaa005

3. Curtis E, Moon R, Harvey N, Cooper C. The impact of fragility fracture and approaches
to osteoporosis risk assessment worldwide. Bone. 2017; 104: 29–38.
doi: 10.1016/j.bone.2017.01.024

4. Mithal A, Bansal B, Kyer CS, Ebeling P. The Asia-Pacific regional audit-epidemiology,
costs, and burden of osteoporosis in India 2013: a report of International Osteoporosis
Foundation. Indian J Endocrinol Metab. 2014; 18(4): 449–454. doi: 10.4103/2230-8210.137485.

5. Yeap SS, Jaisamrarn U, Park Y-S, Takeuchi Y, Xia W, Ang S Bin. The Asian Federation
of Osteoporosis Societies’ call to action to improve the undertreatment of osteoporosis
in Asia. Osteoporos Sarcopenia. 2017; 3(4): 161–163. doi: 10.1016/j.afos.2017.11.002

6. Madarina A, Kusdhany LS, Mahiddin FG. Mandibular bone osteoporosis and oral
health-related quality of life in the elderly. Journal of International Dental and Medical
Research. 2017; 10(Specialissue): 423–428.

7. Setyohadi B, Hutagalung EU, Adam JMF, Suryaatmadja M, Budiparama NC, Jatim SANM, Suherman SK, Kusumawijaya K, Tirtarahardja G, Rotikan TTM, Rudijanto A, Suryana BPP. Summary of the Indonesian guidelines for diagnosis and management of osteoporosis. Journal of the ASEAN Federation of Endocrine Societies. 2012; 27(2): 147–150. doi: 10.15605/jafes.027.02.02

8. Kanis JA, Cooper C, Rizzoli R, Reginster J-Y. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int. 2019; 30(1): 3–44. doi: 10.1007/s00198-018-4704-5

9. Hua Y, Nackaerts O, Duyck J, Maes F, Jacobs R. Bone quality assessment based on cone
beam computed tomography imaging. Clin Oral Implants Res. 2009; 20(8): 767–771.
doi: 10.1111/j.1600-0501.2008.01677.x

10. Güngör E, Yildirim D, Çevik R. Evaluation of osteoporosis in jaw bones using cone beam
CT and dual-energy X-ray absorptiometry. J Oral Sci. 2016; 58(2): 185–194.
doi: 10.2334/josnusd.15-0609

11. Haseltine KN, Chukir T, Smith PJ, Jacob JT, Bilezikian JP, Farooki A. Bone mineral
density: clinical relevance and quantitative assessment. J Nucl Med. 2021; 62(4): 446–454. doi: 10.2967/jnumed.120.256180

12. Delsmann MM, Strahl A, Mühlenfeld M, Jandl NM, Beil FT, Ries C, Rolvien T. High prevalence and undertreatment of osteoporosis in elderly patients undergoing total hip arthroplasty. Osteoporos Int. 2021; 32(8): 1661–1668. doi: 10.1007/s00198-021-05881-y.

13. Alonso MBCC, Vasconcelos TV, Lopes LJ, Watanabe PCA, Freitas DQ. Validation of cone-beam computed tomography as a predictor of osteoporosis using the Klemetti classification. Braz Oral Res. 2016; 30(1): S1806-83242016000100263.
doi:10.1590/1807-3107BOR-2016.vol30.0073

14. Sghaireen MG, Ganji KK, Alam MK, Srivastava KC, Shrivastava D, Rahman SA, Patil SR, Habib SA. Comparing the diagnostic accuracy of CBCT grayscale values with DXA values for the detection of osteoporosis. Appl Sci. 2020; 10(13): 4584. doi: 10.3390/app10134584

15. Kiswanjaya B, Yoshihara A, Miyazaki H. Low body mass index as a risk factor for the onset of
porosity of the mandibular bone in the elderly. Pesquisa Brasileira em Odontopediatria e
Clinica Integrada. 2021; 21: 1–8. doi: 10.1590/pboci.2021.052

16. Barngkgei I, Haffar I Al, Khattab R. Osteoporosis prediction from the mandible using cone-beam computed tomography. Imaging Sci Dent. 2014; 44(4): 263–271.
doi: 10.5624/isd.2014.44.4.263

17. Koh KJ, Kim KA. Utility of the computed tomography indices on cone beam computed
tomography images in the diagnosis of osteoporosis in women. Imaging Sci Dent.
2011; 41(3): 101–106. doi: 10.5624/isd.2011.41.3.101

18. Guerra ENS, Almeida FT, Bezerra FV, Figueiredo PTDS, Silva MAG, Canto GDL, Pacheco-Pereira C, Leote AF. Capability of CBCT to identify patients with low bone mineral
density: A systematic review. Dentomaxillofac Radiol. 2017; 46(8): 20160475.
doi: 10.1259/dmfr.20160475

19. Barra SG, Gomes IP, Amaral TMP, Brasileiro CB, Abreu LG, Mesquita RA. 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; 131(3): 347–355. doi: 10.1016/j.oooo.2020.07.016

20. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic
reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009; 6(7): e1000097.
doi: 10.1371/journal.pmed.1000097

21. Brasileiro CB, Chalub LLFH, Abreu MHNG, Barreiros ID, Amaral TMP, Kakehasi AM,
Mesquita RA. Use of cone beam computed tomography in identifying postmenopausal
women with osteoporosis. Arch Osteoporos. 2017; 12(1): 26.
doi: 10.1007/s11657-017-0314-7

22. Mansour S, Alghamdi AST, Javed F, Marzouk H, Khan EA. Panoramic radiomorphometric
indices as reliable parameters in predicting osteoporosis. Am J Med Sci. 2013; 346(6): 473–
478. doi: 10.1097/MAJ.0b013e3182972148

23. Valerio CS, Trindade AM, Mazzieiro ÊT, Amaral TP, Manzi FR. Use of digital panoramic radiography as an auxiliary means of low bone mineral density detection in postmenopausal
women. Dentomaxillofac Radiol. 2013; 42(10): 20120059. doi: 10.1259/dmfr.20120059

24. Alam T, Alshahrani I, Assiri KI, Almoammar S, Togoo RA, Luqman M. Evaluation of clinical
and radiographic parameters as dental indicators for postmenopausal osteoporosis.
Oral Health Prev Dent. 2020; 18(1): 499–504. doi: 10.3290/j.ohpd.a44688

25. Balto KA, Gomaa MM, Feteih RM, AlAmoudi NM, Elsamanoudy AZ, Hassanien MA, Ardawai
MSM. Dental panoramic radiographic indices as a predictor of osteoporosis in Postmenopausal
Saudi Women. J Bone Metab. 2018; 25(3): 165-173. doi: 10.11005/jbm.2018.25.3.165

26. Calciolari E, Donos N, Park JC, Petrie A, Mardas N. Panoramic measures for oral bone
mass in detecting osteoporosis: a systematic review and meta-analysis. J Dent Res. 2015;
94(3 Suppl): 17S-27S. doi: 10.1177/0022034514554949

27. Camargo AJ, Cortes ARG, Aoki EM, Baladi MG, Arita ES, Watanabe PCA. Diagnostic
performance of fractal dimension and radiomorphometric indices from digital panoramic radiographs for screening low bone mineral density. Braz. J. Oral Sci. 2016; 15(2):
131–136. doi: 10.20396/bjos.v15i2.8648764

28. Kinalski MA, Boscato N, Damian MF. The accuracy of panoramic radiography as a
screening of bone mineral density in women: a systematic review. Dentomaxillofac Radiol.
2020; 49(2): 20190149. doi: 10.1259/dmfr.20190149

29. Munhoz L, Morita L, Nagai AY, Moreira J, Arita ES. Mandibular cortical index in the screening
of postmenopausal at low mineral density risk: a systematic review. Dentomaxillofac Radiol.
2021; 50(4): 1–14. doi: 10.1259/dmfr.20200514

30. Klemetti E, Kolmakow S. Morphology of the mandibular cortex on panoramic
radiographs as an indicator of bone quality. Dentomaxillofac Radiol. 1997; 26(1): 22–25.
doi: 10.1038/sj.dmfr.4600203

31. Ledgerton D, Homer K, Devlin H, Worthington H. Radiomorphometric indices of the mandible
in a British female population. Dentomaxillofac Radiol. 1999; 28(3): 173–181.
doi: 10.1038/sj.dmfr.4600435

32. Kato CN, Tavares NPK, Barra SG, Amaral TMP, Brasileiro CB, Abreu LG, Mesquita RA. Digital panoramic radiography and conebeam ct as ancillary tools to detect low bone mineral density in postmenopausal women. Dentomaxillofac Radiol. 2019; 48(2): 3–9. doi: 10.1259/dmfr.20180254

33. Leite AF, de Souza Figueiredo PT, Caracas H, Sindeaux R, Guimarães ATB, Lazarte L, de
Paula AP, de Melo NS. Systematic review with hierarchical clustering analysis for the fractal
dimension in assessment of skeletal bone mineral density using dental radiographs. Oral
Radiol. 2015; 31: 1–13. doi: 10.1007/s11282-014-0188-y

34. Franciotti R, Moharrami M, Quaranta A, Bizzoca MEE, Piattelli A, Aprile G, Perrotti V.
Use of fractal analysis in dental images for osteoporosis detection: a systematic review and meta-analysis. Osteoporos Int. 2021; 32(6): 1041–1052. doi: 10.1007/s00198-021-05852-3

35. Alman AC, Johnson LR, Calverley DC, Grunwald GK, Lezotte DC, Hokanson JE. Diagnostic capabilities of fractal dimension and mandibular cortical width to identify men and women with decreased bone mineral density. Osteoporos Int. 2012; 23(5): 1631–1636. doi: 10.1007/s00198-011-1678-y

36. Koh K-J, Park H-N, Kim K-A. Prediction of agerelated osteoporosis using fractal analysis on
panoramic radiographs. Imaging Sci Dent. 2012; 42(4): 231–235.
doi: 10.5624/isd.2012.42.4.231

37. Sindeaux R, Figueiredo PTDS, De Melo NS, Guimarães ATB, Lazarte L, Pereira FB,
de Paula AP, Leite AF. Fractal dimension and mandibular cortical width in normal and
osteoporotic men and women. Maturitas. 2014; 77(2): 142–148.
doi: 10.1016/j.maturitas.2013.10.011

38. Ling H, Yang X, Li P, Megalooikonomou V, Xu Y, Yang J. Cross gender – age
trabecular texture analysis in cone beam CT. Dentomaxillofac Radiol. 2014; 43(4):
20130324. doi: 10.1259/dmfr.20130324

39. Kavitha MS, Kumar PG, Park SY, Huh KH, Heo MS, Kurita T, Asano A, An SY, Chien SI.
Automatic detection of osteoporosis based on hybrid genetic swarm fuzzy classifier
approaches. Dentomaxillofac Radiol. 2016; 45(7): 20160076. doi: 10.1259/dmfr.20160076

40. Kato CNAO, Barra SG, Tavares NPK, Amaral TMP, Brasileiro CB, Mesquita RA, et al. Use of
fractal analysis in dental images: a systematic review. Dentomaxillofac Radiol. 2020; 49(2):
20180457. doi: 10.1259/dmfr.20180457

41. Ibrahim N, Parsa A, Hassan B, Van Der Stelt P, Aartman IHA, Wismeijer D. The effect of
scan parameters on cone beam CT trabecular bone microstructural measurements of the
human mandible. Dentomaxillofac Radiol. 2013; 42(10): 20130206.
doi: 10.1259/dmfr.20130206

42. Ibrahim N, Parsa A, Hassan B, Van Der Stelt P, Aartman IHA, Nambiar P. Influence of
object location in different FOVs on trabecular bone microstructure measurements of
human mandible: A cone beam CT study. Dentomaxillofac Radiol. 2014; 43(2):
20130329. doi: 10.1259/dmfr.20130329

43. Hayashi Y, Ito M, Imanishi Y, Watanabe K, Matsumoto K, Arai Y, Honda K. Use
of experimental phantoms to determine the accuracy and reliability of mandibular
cortical width measurements by panoramic radiography and cone-beam computed
tomography. J Oral Sci. 2020; 62(3): 303–307. doi: 10.2334/josnusd.19-0307



DOI: https://doi.org/10.22146/majkedgiind.74535

Article Metrics

Abstract views : 1417 | views : 1317

Refbacks

  • There are currently no refbacks.




Copyright (c) 2022 Majalah Kedokteran Gigi Indonesia

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


 

 View My Stats


real
time web analytics