CC BY 4.0 · Eur J Dent
DOI: 10.1055/s-0043-1772570
Original Article

The Suitability of Trabecular Patterns in the Assessment of Dental Implant Osseointegration Process through 2D Digital and 3D CBCT Radiographs

1   Department of Dentomaxillofacial Radiology Residency Program, Faculty of Dentistry, Padjadjaran University, Bandung, West Java, Indonesia
Farina Pramanik
1   Department of Dentomaxillofacial Radiology Residency Program, Faculty of Dentistry, Padjadjaran University, Bandung, West Java, Indonesia
Azhari Azhari
1   Department of Dentomaxillofacial Radiology Residency Program, Faculty of Dentistry, Padjadjaran University, Bandung, West Java, Indonesia
› Author Affiliations


Objective The research aims to determine the suitability of the trabecular pattern in the assessment of the dental implant osseointegration process through two-dimensional (2D) digital and three-dimensional (3D) cone-beam computed tomography (CBCT) radiographs.

Materials and Methods This is a correlation description that explains the relationship between variables. The population consisted of 24 data points on 3D CBCT and 2D digital radiographs from the procedure after dental implants were inserted into the tibia of a New Zealand white rabbit (Oryctolagus cuniculus) on days 3, 14, and 28. The radiograph was selected based on the region of interest (ROI), which covers the peri-implant area with a width of 1 mm and length following the height of the implant. The ROI was analyzed for trabecular thickness (Tb.Th), separation (Tb.Sp), number (Tb.N), and fractal dimension.

Statistical Analysis The intraclass correlation coefficient (ICC) was used to statistically test the data to assess the consistency of intraobserver measurements and the r value (Pearson's correlation coefficient). This determines the correlation between trabecular patterns in both radiographic modalities and the Bland–Altman plot to observe the limits of acceptable discrepancies.

Results The ICC test showed high intraobserver consistency in trabecular pattern measurements on 2D digital radiographs and 3D CBCT. The trabecular space pattern and number showed an r value of 0.88 with radiographic modalities of 0.72 mm and 0.018, respectively. Additionally, the trabecular thickness and fractal dimension had an insignificant correlation, with an r value of 0.22, and the mean of the 2D radiograph was lower than that of CBCT.

Conclusion The 2D radiograph and 3D CBCT showed correlations in the trabecular number and space results but had no correlation in the trabecular thickness and fractal dimension results. Based on intraclass correlation analysis, 3D CBCT appeared to be more reliable for measuring trabecular patterns (Tb.Th, Tb.Sp, Tb.N, and fractal dimension) than 2D radiograph.

Ethical Approval Statement

This study was approved by the Animal Ethics Committee of the Faculty of Veterinary Medicine, Bogor Agricultural University (006/KEH/SKE/III/2021).

Publication History

Article published online:
20 September 2023

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  • References

  • 1 Zarb GA, Koka S. Osseointegration: promise and platitudes. Int J Prosthodont 2012; 25 (01) 11-12
  • 2 Gill A, Rao P. Primary stability: the password of implant integration. J Dent Implant 2012; 2 (02) 103
  • 3 Patil R, Bharadwaj D. Is primary stability a predictable parameter for loading implant?. J. Int. Clin. Dent. Res. Organ. 2016; 8 (01) 84
  • 4 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 (05) 1009-1013
  • 5 Corpas LdosS, Jacobs R, Quirynen M, Huang Y, Naert I, Duyck J. Peri-implant bone tissue assessment by comparing the outcome of intra-oral radiograph and cone beam computed tomography analyses to the histological standard. Clin Oral Implants Res 2011; 22 (05) 492-499
  • 6 Nicolielo LFP, Van Dessel J, Jacobs R, Quirino Silveira Soares M, Collaert B. Relationship between trabecular bone architecture and early dental implant failure in the posterior region of the mandible. Clin Oral Implants Res 2020; 31 (02) 153-161
  • 7 Van Dessel J, Nicolielo LFP, Huang Y. et al. Accuracy and reliability of different cone beam computed tomography (CBCT) devices for structural analysis of alveolar bone in comparison with multislice CT and micro-CT. Eur J Oral Implantology 2017; 10 (01) 95-105
  • 8 Pothuaud L, Carceller P, Hans D. Correlations between grey-level variations in 2D projection images (TBS) and 3D microarchitecture: applications in the study of human trabecular bone microarchitecture. Bone 2008; 42 (04) 775-787
  • 9 Huang Y, Dessel JV, Depypere M. et al. Validating cone-beam computed tomography for peri-implant bone morphometric analysis. Bone Res 2014; 2 (February): 14010
  • 10 Kulah K, Gulsahi A, Kamburoğlu K. et al. Evaluation of maxillary trabecular microstructure as an indicator of implant stability by using 2 cone beam computed tomography systems and micro-computed tomography. Oral Surg Oral Med Oral Pathol Oral Radiol 2019; 127 (03) 247-256
  • 11 Ibrahim N, Parsa A, Hassan B, van der Stelt P, Aartman IH, Wismeijer D. The effect of scan parameters on cone beam CT trabecular bone microstructural measurements of human mandible. Dentomaxillofac Radiol 2013; 42 (10) 20130206
  • 12 Vidor MM, Liedke GS, Fontana MP. et al. Is cone beam computed tomography accurate for postoperative evaluation of implants? An in vitro study. Oral Surg Oral Med Oral Pathol Oral Radiol 2017; 124 (05) 500-505
  • 13 Zhang CN, Zhu Y, Fan LF, Zhang X, Jiang YH, Gu YX. Intra- and inter-observer agreements in detecting peri-implant bone defects between periapical radiography and cone beam computed tomography: a clinical study. J Dent Sci 2021; 16 (03) 948-956
  • 14 Song D, Shujaat S, de Faria Vasconcelos K. et al. Diagnostic accuracy of CBCT versus intraoral imaging for assessment of peri-implant bone defects. BMC Med Imaging 2021; 21 (01) 23
  • 15 Bohner LOL, Mukai E, Oderich E. et al. Comparative analysis of imaging techniques for diagnostic accuracy of peri-implant bone defects: a meta-analysis. Oral Surg Oral Med Oral Pathol Oral Radiol 2017; 124 (04) 432-440.e5
  • 16 Jacobs R, Vranckx M, Vanderstuyft T, Quirynen M, Salmon B. CBCT vs other imaging modalities to assess peri-implant bone and diagnose complications: a systematic review. Eur J Oral Implantology 2018; 11 (Suppl. 01) 77-92
  • 17 Brånemark P-I. Introduction to Osseointegration. Chicago, IL: Quintessence Publishing Co.; 1985: 11-76
  • 18 Sakka S, Coulthard P. Bone quality: a reality for the process of osseointegration. Implant Dent 2009; 18 (06) 480-485
  • 19 Karhula SS, Finnilä MAJ, Rytky SJO. et al. Quantifying subresolution 3D morphology of bone with clinical computed tomography. Ann Biomed Eng 2020; 48 (02) 595-605
  • 20 Furuya N, Nakamura K, Kashima I. Morphometric analysis of digital radiographic bone images for trabecular bone structure. Oral Radiol 2002; 18 (02) 17-29
  • 21 Van Dessel J, Nicolielo LF, Huang Y. et al. Quantification of bone quality using different cone beam computed tomography devices: accuracy assessment for edentulous human mandibles. Eur J Oral Implantology 2016; 9 (04) 411-424
  • 22 Bouxsein ML, Boyd SK, Christiansen BA, Guldberg RE, Jepsen KJ, Müller R. Guidelines for assessment of bone microstructure in rodents using micro-computed tomography. J Bone Miner Res 2010; 25 (07) 1468-1486
  • 23 Bohner L, Tortamano P, Gremse F, Chilvarquer I, Kleinheinz J, Hanisch M. Assessment of trabecular bone during dental implant planning using cone-beam computed tomography with high-resolution parameters. Open Dent J 2021; 15 (01) 57-63
  • 24 Parfitt AM. Bone histomorphometry: standardization of nomenclature, symbols and units. Summary of proposed system. Bone Miner 1988; 4 (01) 1-5
  • 25 Feldkamp LA, Goldstein SA, Parfitt AM, Jesion G, Kleerekoper M. The direct examination of three-dimensional bone architecture in vitro by computed tomography. J Bone Miner Res 1989; 4 (01) 3-11
  • 26 Pothuaud L, Benhamou CL, Porion P, Lespessailles E, Harba R, Levitz P. Fractal dimension of trabecular bone projection texture is related to three-dimensional microarchitecture. J Bone Miner Res 2000; 15 (04) 691-699
  • 27 Wancket LM. Animal models for evaluation of bone implants and devices: comparative bone structure and common model uses. Vet Pathol 2015; 52 (05) 842-850
  • 28 Pearce AI, Richards RG, Milz S, Schneider E, Pearce SG. Animal models for implant biomaterial research in bone: a review. Eur Cell Mater 2007; 13 (00) 1-10
  • 29 Doube M, Kłosowski MM, Arganda-Carreras I. et al. BoneJ: free and extensible bone image analysis in ImageJ. Bone 2010; 47 (06) 1076-1079
  • 30 Schindelin J, Arganda-Carreras I, Frise E. et al. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012; 9 (07) 676-682
  • 31 Steiner L, Synek A, Pahr DH. Comparison of different microCT-based morphology assessment tools using human trabecular bone. Bone Rep 2020; 12: 100261
  • 32 Hafshah LA, Azhari A, Pramanik F. Differences in the assessment of dental implant osseointegration with changes in orthopantomography exposure settings on the rabbit tibia. World J Dent 2022; 13 (S2): S119-S124
  • 33 Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. [published correction appears in J Chiropr Med. 2017 Dec;16(4):346] J Chiropr Med 2016; 15 (02) 155-163
  • 34 Bland JM, Altman DG. Comparing methods of measurement: why plotting difference against standard method is misleading. Lancet 1995; 346 (8982): 1085-1087
  • 35 Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res 1999; 8 (02) 135-160
  • 36 Trochim B, Borowska M, Szarmach J. Analysis of X-rays in bone remodelling around active and replace dental implants. Signal Image Video Process 2022; 16 (01) 111-118
  • 37 Jacobs R, Salmon B, Codari M, Hassan B, Bornstein MM. Cone beam computed tomography in implant dentistry: recommendations for clinical use. BMC Oral Health 2018; 18 (01) 88
  • 38 Wang L, Gao Z, Su Y, Liu Q, Ge Y, Shan Z. Osseointegration of a novel dental implant in canine. Sci Rep 2021; 11 (01) 4317
  • 39 Fang L, Ding X, Wang HM, Zhu XH. Chronological changes in the microstructure of bone during peri-implant healing: a microcomputed tomographic evaluation. Br J Oral Maxillofac Surg 2014; 52 (09) 816-821
  • 40 Chang PC, Lang NP, Giannobile WV. Evaluation of functional dynamics during osseointegration and regeneration associated with oral implants. Clin Oral Implants Res 2010; 21 (01) 1-12
  • 41 Ko TJ, Byrd KM, Kim SA. The chairside periodontal diagnostic toolkit: past, present, and future. Diagnostics (Basel) 2021; 11 (06) 932
  • 42 Parsa A, Ibrahim N, Hassan B, Motroni A, van der Stelt P, Wismeijer D. Influence of cone beam CT scanning parameters on grey value measurements at an implant site. Dentomaxillofac Radiol 2013; 42 (03) 79884780
  • 43 Toghyani S, Nasseh I, Aoun G, Noujeim M. Effect of image resolution and compression on fractal analysis of the periapical bone. Acta Inform Med 2019; 27 (03) 167-170
  • 44 Van Dessel J, Huang Y, Depypere M, Rubira-Bullen I, Maes F, Jacobs R. A comparative evaluation of cone beam CT and micro-CT on trabecular bone structures in the human mandible. Dentomaxillofac Radiol 2013; 42 (08) 20130145
  • 45 Waarsing JH, Day JS, Weinans H. An improved segmentation method for in vivo microCT imaging. J Bone Miner Res 2004; 19 (10) 1640-1650
  • 46 Rovaris K, Queiroz PM, Vasconcelos KF, Corpas LDS, Silveira BMD, Freitas DQ. Segmentation methods for micro CT images: a comparative study using human bone samples. Braz Dent J 2018; 29 (02) 150-153
  • 47 Karthik K, , Sivakumar, Sivaraj, Thangaswamy V. Evaluation of implant success: a review of past and present concepts. J Pharm Bioallied Sci 2013; 5 (Suppl. 01) S117-S119