Fractal Dimension and Lacunarity Analyses of Root Canal Dentin with or without Smear Layer
Year 2023,
Volume: 24 Issue: 2, 137 - 141, 30.06.2023
Güniz Baksı Şen
,
Bilge Hakan Şen
Abstract
Objective: To investigate the fractal dimension (FD) and lacunarity of dentin in the presence or absence of a smear layer using scanning electron microscopy (SEM) images at various magnifications.
Materials and Methods: Extracted human mandibular premolar teeth were divided into two groups (n=5). After decoronation, the root canals were prepared. While the smear layer was left intact in the first group, it was removed with 5% EDTA and 2.5% NaOCl irrigation in the second group. The roots were split longitudinally and one half was prepared for SEM. Four images at 500 and 1000 magnifications were obtained from the middle thirds of the root canals of each specimen and saved in TIF format. The FD and lacunarity of the SEM images were calculated. Two-way ANOVA and Bonferroni tests were used for statistical analysis (p=0.05).
Results: The FD of dentin surfaces with or without a smear layer did not differ significantly (p>0.05). While magnification was an important factor in the FD of smear-free surfaces (p<0.01), it did not present any significant difference in the presence of a smear layer (p>0.05). Lacunarity showed a significant decrease in the images without a smear layer (p<0.0001). Although it demonstrated a slight increase with magnification, this increase was not significant (p>0.05).
Conclusions: Lacunarity was a differentiating factor in determining the presence or absence of the smear layer regardless of the magnification of the SEM images. FD was affected by magnification and could not discriminate the presence or absence of the smear layer. Lacunarity analysis may be a practical tool for evaluating SEM images of dentinal surfaces.
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Year 2023,
Volume: 24 Issue: 2, 137 - 141, 30.06.2023
Güniz Baksı Şen
,
Bilge Hakan Şen
References
-
1. Dawes TJW, Cai J, Quinlan M, de Marvao A, Ostrowski PJ, Tokarczuk PF, et al. Fractal Analysis of Right Ventricular Trabeculae in Pulmonary Hypertension. Radiology 2018; 288: 386-95.
-
2. Verma G, Luciani ML, Palombo A, Metaxa L, Panzironi G, Pediconi F, et al. Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer: A diagnostic perspective. Comput Biol Med 2018; 93: 1-6.
-
3. Kavitha MS, An SY, An CH, Huh KH, Yi WJ, Heo MS, 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; 119: 346-56.
-
4. Keni Zheng, Makrogiannis S. Bone texture characterization for osteoporosis diagnosis using digital radiography. Annu Int Conf IEEE Eng Med Biol Soc 2016; 2016: 1034-7.
-
5. Borowska M, Szarmach J, Oczeretko E. Fractal texture analysis of the healing process after bone loss. Comput Med Imaging Graph 2015; 46 Pt 2: 191-6.
-
6. 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.
-
7. Chen J, Zheng B, Chang YH, Shaw CC, Towers JD, Gur D. Fractal analysis of trabecular patterns in projection radiographs. An assessment. Invest Radiol 1994; 29: 624-9.
-
8. Mandelbrot BB. The Fractal Geometry of Nature, 3rd ed. New York: WH Freeman & Co; 1983.
-
9. Plotnick RE, Gardner RH, O’Neill RV. Lacunarity indices as measures of landscape texture. Landscape Ecol 1993; 8: 201–11.
-
10. Önem E, Baksı BG, Sogur E. Changes in the fractal dimension, feret diameter, and lacunarity of mandibular alveolar bone during initial healing of dental implants. Int J Oral Maxillofac Implants 2012; 27: 1009-13.
-
11. Ling EJ, Servio P, Kietzig AM. Fractal and Lacunarity Analyses: Quantitative Characterization of Hierarchical Surface Topographies. Microsc Microanal 2016; 22: 168-77.
-
12. 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: 628-35.
-
13. Yasar F, Akgünlü F. Fractal dimension and lacunarity analysis of dental radiographs. Dentomaxillofac Radiol 2005; 34: 261-7.
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14. Landini G. Fractals in microscopy. J Microsc 2011; 241: 1-8.
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15. Pribic J, Vasiljevic J, Kanjer K, Konstantinovic ZN, Milosevic NT, Vukosavljevic DN, et al. Fractal dimension and lacunarity of tumor microscopic images as prognostic indicators of clinical outcome in early breast cancer. Biomark Med 2015; 9: 1279-7.
-
16. de Souza Santos D, Dos Santos LC, de Albuquerque Tavares Carvalho A, Leão JC, Delrieux C, Stosic T, et al. Multifractal spectrum and lacunarity as measures of complexity of osseointegration. Clin Oral Investig 2016; 20: 1271-8.
-
17. Jelinek HF, Fernandez E. Neurons and fractals: how reliable and useful are calculations of fractal dimensions? J Neurosci Methods 1998; 81: 9-18.
-
18. Garding J. Properties of fractal intensity surfaces. Patt Recog Lett 1988; 8: 319-24.
-
19. Dubiusson MP, Dubes RC. Efficacy of fractal features in segmenting images of natural textures. Pattern Recog Lett 1994; 15: 419-31.
-
20. Smith TG Jr, Lange GD, Marks WB. Fractal methods and results in cellular morphology--dimensions, lacunarity and multifractals. J Neurosci Methods 1996; 69: 123-36.
-
21. Wendt U, Stiebe-Lange K, Smid M. On the influence of imaging conditions and algorithms on the quantification of surface topography. J Microsc 2002; 207: 169-79.
-
22. Davies ER. Handbook of Texture Analysis. London: Imperial College Press; 2008.