İSMAİL GÜMÜŞSOY, Şuayip B. DUMAN, İbrahim S. BAYRAKDAR, YASİN YAŞA, Binali ÇAKUR

Correlations between fractal dimension of mandibular condylar bone and Degenerative Joint Disease - A CBCT based analysis

Aim: The aim of this study was to determine whether correlations existed between the fractal dimension (FD) value of the mandibular condyle and radiographic findings of degenerative joint disease (DJD) using cone beam CT (CBCT). Materials and Method: 100 TMJ CBCT images were retrospectively analyzed. CBCT images of patients were assessed with regard to erosive degenerative bone change (DBC) in the mandibular condyle. We divided each condyle into 3 groups and scored (0, 1, 2) according to diagnosis of DJD: with 0 indicating normal condyles or non-demonstrable change, 1 indicating mild erosive DBC and 2 indicating severe erosive DBC. Fractal analysis (FA) was applicated to CBCT image of mandibular condyle. FD values were compared with the radiographic diagnosis scores. Results: ANOVA test showed that there was statistically significant difference between the FD values of patient with erosive DBC and patient having no erosive change. The average FD value of patient group 0 was 1.079, the average FD value of patient group 1 was 1.052, the average FD value of patient group 2 was 1.036. Lower FD values and more severe degenerative changes were seen in patient group 2. Conclusion: In our study, we found that as the grade of bone degeneration increased, FD values decreased. These findings suggest a promising result in related topic. However, this paper is a preliminary study of FA and DBC. Further studies should be performed to ensure FA is clinically feasible.

Mandibular kondilar kemiğe ait fraktal boyut değerleri ve dejeneratif eklem hastalığı bulguları arasındaki korelasyon: Dental tomografi temelli bir analiz

Amaç: Bu çalışmanın amacı dental volumetrik tomografi (DVT) kullanılarak elde edilen dejeneratif eklem hastalığında mandibular kondile ait radyografik bulgular ile fractal boyut (FB) değerleri arasında korelasyon olup olmadığını araştırmaktır. Gereç ve Yöntem: 100 DVT eklem görüntüsü retrospektif olarak incelendi. Hastaların DVT görüntüleri mandibular kondilde eroziv dejeneratif kemik değişimi (DKD) açısından incelendi ve her bir kondil buna göre üç gruba ayrılarak skorlandı (0, 1, 2): 0 normal kondili, 1 kondilde hafif derece eroziv DKD, 2 kondilde ileri derece eroziv DKD göstermektedir. Fraktal analiz (FA), mandibular kondil DVT görüntüleri üzerine uygulandı ve radyografik diagnoz skorları ile karşılaştırıldı. Bulgular: Anova test değerleri, kondilde eroziv DKD olan hastaların FB değerleri ile olmayanlar arasında istatistiksel olarak anlamlı derecede farklılık olduğunu gösterdi. Hasta grubu 0’da ortalama FB değeri 1.079, grup 2’de 1.052 ve grup 3’de 1.036 idi. Daha yüksek dejeneratif değişimlerin görüldüğü hasta grubu 2’de daha düşük FB değerleri görüldü. Sonuç: Çalışmamızda, kemik dejenerasyon derecesi arttıkça FB değerlerinin de azaldığını gözlemledik. Bu bulgular konuyla ilgili umut verici bir sonuç ortaya koymakla beraber, bu araştırma FA ve DKD ile ilgili bir ön çalışmadır ve FA‘in klinik olarak uygulanabilir olması için daha ileri çalışmalar yapılmalıdır.

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1. Geraets WG, Van der Stelt PF. Fractal properties of bone. Dentomaxillofac Radiol 2000; 29: 144-53.

2. Updike SX, Nowzari H. Fractal analysis of dental radiographs to detect periodontitis-induced trabecular changes. J Periodontal Res 2008; 43: 658-64.

3. Mandelbrot B. Fractal Geometry of Nature. Edition. New York, ABD, W. H. Freeman and Company;1983.

4. Smith TG, Jr., Lange GD, Marks WB. Fractal methods and results in cellular morphology--dimensions, lacunarity and multifractals. J Neurosci Methods 1996; 69: 123- 136.

5. Tanaka E, Detamore MS, Mercuri LG. Degenerative disorders of the temporomandibular joint: etiology, diagnosis, and treatment. J Dent Res 2008; 87: 296-307.

6. dos Anjos Pontual ML, Freire JS, Barbosa JM, Frazao MA, dos Anjos Pontual A. Evaluation of bone changes in the temporomandibular joint using cone beam CT. Dentomaxillofac Radiol 2012; 41: 24-29.

7. Yi W-J, Heo M-S, Lee S-S, Choi S-C, Huh K-H, et al. Direct measurement of trabecular bone anisotropy using directional fractal dimension and principal axes of inertia. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 104: 110-116.

8. Fazzalari .L, Parkinson IH. Fractal properties of cancellous bone of the iliac crest in vertebral crush fracture. Bone 1998; 23: 53-57.

9. Law AN, Bollen AM, Chen SK. Detecting osteoporosis using dental radiographs: a comparison of four methods. J Am Dent Assoc 1996, 127: 1734-1742.

10. Southard TE, Southard KA, Jakobsen JR, Hillis SL, Najim CA. Fractal dimension in radiographic analysis of alveolar process bone. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1996; 82: 569-576.

11. Southard TE, Southard KA, Krizan KE, Hillis SL, Haller JW, et al. Mandibular bone density and fractal dimension in rabbits with induced osteoporosis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2000; 89: 244-249.

12. Southard TE, Southard KA, Lee A. Alveolar process fractal dimension and postcranial bone density. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2001; 91: 486- 4891.

13. White SC, Rudolph DJ. Alterations of the trabecular pattern of the jaws in patients with osteoporosis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1999; 88: 628-635.

14. Bollen AM, Taguchi A, Hujoel PP, Hollender LG. Fractal dimension on dental radiographs. Dentomaxillofac Radiol 2001; 30: 270-275.

15. Caligiuri P, Giger ML, Favus M. Multifractal radiographic analysis of osteoporosis. Med Phys 1994; 21: 503-508.

16. Tosoni GM, Lurie AG, Cowan AE, Burleson JA. Pixel intensity and fractal analyses: detecting osteoporosis in perimenopausal and postmenopausal women by using digital panoramic images. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2006; 102: 235-241.

17. Ingawale S, Goswami T. Temporomandibular joint: disorders, treatments, and biomechanics. Ann Biomed Eng 2009; 37: 976-996.

18. Muir CB, Goss AN. The radiologic morphology of asymptomatic temporomandibular joints. Oral Surg Oral Med Oral Pathol 1990; 70: 349-354.

19. 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: 767- 771.

20. White SC. Oral radiographic predictors of osteoporosis. Dentomaxillofac Radiol 2002; 31: 84-92.

21. Jett S, Shrout MK, Mailhot JM, Potter BJ, Borke JL. An evaluation of the origin of trabecular bone patterns using visual and digital image analysis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2004; 98: 598-604.

22. Zeytinoglu M, Ilhan B, Dundar N, Boyacioglu H. Fractal analysis for the assessment of trabecular peri-implant alveolar bone using panoramic radiographs. Clin Oral Investig 2015; 19: 519-524.

23. Ergun S, Saracoglu A, Guneri P, Ozpinar B. Application of fractal analysis in hyperparathyroidism. Dentomaxillofac Radiol 2009; 38: 281-288.

24. White SC, Cohen JM, Mourshed FA. Digital analysis of trabecular pattern in jaws of patients with sickle cell anemia. Dentomaxillofac Radiol 2000; 29: 119-124.

25. Pothuaud L, Lespessailles E, Harba R, Jennane R, Royant V, et al. Fractal analysis of trabecular bone texture on radiographs: discriminant value in postmenopausal osteoporosis. Osteoporos Int 1998;8:618-625.

26. Ruttimann UE, Webber RL, Hazelrig JB. Fractal dimension from radiographs of peridental alveolar bone. A possible diagnostic indicator of osteoporosis. Oral Surg Oral Med Oral Pathol 1992; 74: 98-110.

27. Saeed SS, Ibraheem UM, Alnema MM. Quantitative Analysis by Pixel Intensity and Fractal Dimensions for Imaging Diagnosis of Periapical Lesions. Int J Enhanced Research in Science Technology & Engineering 2014; 3: 138-144.

28. Yasar F, Akgunlu F. The differences in panoramic mandibular indices and fractal dimension between patients with and without spinal osteoporosis. Dentomaxillofac Radiol 2006; 35: 1-9.

29. Arsan B, Köse TE, Çene E, Özcan İ. Assessment of the trabecular structure of mandibular condyles in patients with temporomandibular disorders using fractal analysis. Oral Surg Oral Med Oral Pathol Oral Radiol 2017; 123: 382-391.

30. Demirbas AK, Ergun S, Guneri P, Aktener BO, Boyacioglu H. Mandibular bone changes in sickle cell anemia: fractal analysis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2008; 106: e41-e48.

31. Kayipmaz S, Akçay S, Sezgin ÖS, Çandirli C. Trabecular structural changes in the mandibular condyle caused by degenerative osteoarthritis: a comparative study by cone-beam computed tomography imaging. Oral Radiology 2019; 35: 51-58.

32. Akerman S, Kopp S, Rohlin M. Macroscopic and microscopic appearance of radiologic findings in temporomandibular joints from elderly individuals. An autopsy study. Int J Oral Maxillofac Surg 1988; 17: 58-63.

33. Flygare L, Rohlin M, Akerman S. Microscopy and tomography of erosive changes in the temporomandibular joint. An autopsy study. Acta Odontol Scand 1995; 53: 297-303.

34. Ahmad M, Schiffman EL. Temporomandibular Joint Disorders and Orofacial Pain. Dent Clin North Am 2016; 60:1 05-124.

35. Nah KS. Condylar bony changes in patients with temporomandibular disorders: a CBCT study. Imaging Sci Dent 2012; 42: 249-253.

36. Hussain AM, Packota G, Major PW, Flores-Mir C. Role of different imaging modalities in assessment of temporomandibular joint erosions and osteophytes: a systematic review. Dentomaxillofac Radiol 2008; 37: 63-71.

37. Devlin H, Karayianni K, Mitsea A, Jacobs R, Lindh C, et al. Diagnosing osteoporosis by using dental panoramic radiographs: the OSTEODENT project. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2007; 104: 821-828.

38. Kwong JC, Palomo JM, Landers MA, Figueroa A, Hans MG. Image quality produced by different cone-beam computed tomography settings. Am J Orthod Dentofacial Orthop 2008; 133: 317-327.

39. Ibrahim N, Parsa A, Hassan B, van der Stelt P, Aartman IHA, et al. Influence of object location in different FOVs on trabecular bone microstructure measurements of human mandible: a cone beam CT study. Dentomaxillofac Radiol 2014; 43: 20130329.