Evaluation of the interference of metallic dental artifacts with virtual implant planning on CBCT
Main Article Content
Abstract
Introduction: The quality of cone-beam computed tomography (CBCT) images can be affected by patient factors, including metal artifacts, which may compromise diagnosis and surgical planning. Objective: To evaluate the interference of metal restoration artifacts with superimposed DICOM and STL files using automatic segmentation in CBCT planning software and compare it with image acquisition. Methods: Subjects were divided into three groups: group 0 (zero to two restorations), group 1 (three to five restorations), and group 2 (six or more restorations). DICOM files were superimposed on STL files using four fixed anatomical positions in 3D arches for standardization. Statistical analysis included Shapiro-Wilk normality, Levene, Kruskal-Wallis, Dunn's post-tests, and Mann-Whitney U Test, with a 5% significance level. Results: The mean deviation was 0.489 mm (SD ±1.353 mm). The number of restorations significantly influenced deviations in the horizontal/anterior position (p=0.009). Group 1 differed significantly from group 2, while group 0 showed no significant differences from either. Comparing occlusion and non-occlusion, Vertical/Posterior (VP) and Vertical/Anterior (VA) positions showed significant differences, with higher means for group 1. Conclusion: Metal artifacts did not affect vertical analyses in CBCT planning but caused discrepancies in horizontal DICOM-STL segmentation adjustments.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY) that allows others to share and adapt the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.References
1. Flügge TV, Att W, Metzger MC, Nelson K. Precision of dental implant digitization using intraoral scanners. Int J Prosthodont. 2016;29(3):277-83. https://doi.org/10.11607/ijp.4417
2. Kamio T, Suzuki M, Asaumi R, Kawai T. DICOM segmentation and STL creation for 3D printing: a process and software package comparison for osseous anatomy. 3D Print Med. 2020;6(1):17. https://doi.org/10.1186/s41205-020-00069-2
3. 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(1):88. https://doi.org/10.1186/s12903-018-0523-5
4. Oliveira MR, Sousa TO, Caetano AF, Paiva RR, Valladares-Neto J, Yamamoto-Silva FP, et al. Influence of CBCT metal artifact reduction on vertical radicular fracture detection. Imaging Sci Dent. 2021;51(1):55-62. https://doi.org/10.5624/isd.20200191
5. Terrabuio BR, Carvalho CG, Peralta-Mamani M, Santos PSS, Rubira-Bullen IRF, Rubira CMF. Cone-beam computed tomography artifacts in the presence of dental implants and associated factors: an integrative review. Imaging Sci Dent. 2021;51(2):93-106. https://doi.org/10.5624/isd.20200320
6. Pinheiro LR, Gaia BF, Sales MAO, Umetsubo OS, Santos Junior O, Cavalcanti MG. Effect of field of view in the detection of chemically created peri-implant bone defects in bovine ribs using cone beam computed tomography: an in vitro study. Oral Surg Oral Med Oral Pathol Oral Radiol. 2015;120(1):69-77. https://doi.org/10.1016/j.oooo.2015.04.006
7. Pinheiro LR, Scarfe WC, Augusto de Oliveira Sales M, Gaia BF, Cortes AR, Cavalcanti MG. Effect of Cone-Beam Computed Tomography Field of View and Acquisition Frame on the Detection of Chemically Simulated Peri-Implant Bone Loss In Vitro. J Periodontol. 2015;86(10):1159-65. https://doi.org/10.1902/jop.2015.150223
8. Chagas MM, Kobayashi-Velasco S, Gimenez T, Cavalcanti MGP. Diagnostic accuracy of imaging examinations for peri-implant bone defects around titanium and zirconium dioxide implants: A systematic review and meta-analysis. Imaging Sci Dent. 2021;51(4):363-72. https://doi.org/10.5624/isd.20210120
9. Varga Jr E, Hammer B, Hardy BM, Kamer L. The accuracy of three-dimensional model generation. What makes it accurate to be used for surgical planning? Int J Oral Maxillofac Surg. 2013;42(9):1159-66. https://doi.org/10.1016/j.ijom.2013.02.006
10. Yousefi F, Shokri A, Zahedi F, Farhadian M. Assessment of the accuracy of laser-scanned models and 3-dimensional rendered cone-beam computed tomographic images compared to digital caliper measurements on plaster casts. Imaging Sci Dent. 2021;51(4):429-38. https://doi.org/10.5624/isd.20210142
11. Rangel FA, Maal TJJ, Bronkhorst EM, Breuning KH, Schols JGJH, Bergé SJ, et al. Accuracy and reliability of a novel method for fusion of digital dental casts and cone beam computed tomography scans. PLoS One. 2013;8(3):e59130. https://doi.org/10.1371/journal.pone.0059130
12. Flügge T, Derksen W, Poel JT, Hassan B, Nelson K, Wismeijer D. Registration of cone beam computed tomography data and intraoral surface scans - A prerequisite for guided implant surgery with CAD/CAM drilling guides. Clin Oral Implants Res. 2017;28(9):1113-18. https://doi.org/10.1111/clr.12925
13. Freitas APLF, Peixoto LR, Suassuna FCM, Bento PM, Amorim AMAM, et al. The effects of different metal posts, cements, and exposure parameters on cone-beam computed tomography artifacts. Imaging Sci Dent. 2023;53(2):127-35. https://doi.org/10.5624/isd.20220185
14. Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, Schwanecke U, et al. Artefacts in CBCT: a review. Dentomaxillofac Radiol. 2011;40(5):265-73. https://doi.org/10.1259/dmfr/30642039
15. Nkenke E, Zachow S, Benz M, Maier T, Veit K, Kramer M, et al. Fusion of computed tomography data and optical 3D images of the dentition for streak artefact correction in the simulation of orthognathic surgery. Dentomaxillofac Radiol. 2004;33(4):226-32. https://doi.org/10.1259/dmfr/27071199
16. Swennen GR, Barth EL, Eulzer C, Schutyser F. The use of a new 3D splint and double CT scan procedure to obtain an accurate anatomic virtual augmented model of the skull. Int J Oral Maxillofac Surg. 2007;36(2):146-52. https://doi.org/10.1016/j.ijom.2006.09.019
17. Swennen GR, Mommaerts MY, Abeloos J, De Clercq C, Lamoral P, Neyt N, et al. The use of a wax bite wafer and a double computed tomography scan procedure to obtain a three-dimensional augmented virtual skull model. J Craniofac Surg. 2007;18(3):533-9. https://doi.org/10.1097/scs.0b013e31805343df
18. Plooij JM, Maal TJJ, Haers P, Borstlap WA, Kuijpers-Jagtman AM, Bergé SJ. Digital three-dimensional image fusion processes for planning and evaluating orthodontics and orthognathic surgery. A systematic review. Int J Oral Maxillofac Surg. 2011;40(4):341-52. https://doi.org/10.1016/j.ijom.2010.10.013
19. Cavalcanti MGP. Cone beam computed tomographic imaging: perspective, challenges, and the impact of near-trend future applications. J Caniofac Surg. 2012;23(1):279-82. https://doi.org/10.1097/SCS.0b013e318241ba64
20. Behneke A, Burwinkel M, Behneke N. Factors influencing transfer accuracy of cone beam CT-derived template-based implant placement. Clin Oral Implants Res. 2012;23(4):416-23. https://doi.org/10.1111/j.1600-0501.2011.02337.x
21. Queiroz PM, Santaella GM, Paz TDJ, Freitas DQ. Evaluation of a metal artefact reduction tool on different positions of a metal object in the FOV. Dentomaxillofac Radiol. 2017;46(3):20160366. https://doi.org/10.1259/dmfr.20160366
22. Sheikhi M, Behfarnia P, Mostajabi M, Nasri N. The efficacy of metal artifact reduction (MAR) algorithm in cone-beam computed tomography on the diagnostic accuracy of fenestration and dehiscence around dental implants. J Periodontol. 2020;91(2):209-14. https://doi.org/10.1002/JPER.18-0433
23. Tahmaseb A, Wu V, Wismeijer D, Coucke W, Evans C. The accuracy of static computer-aided implant surgery: A systematic review and meta-analysis. Clin Oral Implants Res. 2018;29(Suppl 16):416-35. https://doi.org/10.1111/clr.13346
24. Tahmaseb A, Wismeijer D, Coucke W, Derksen W. Computer technology applications in surgical implant dentistry: a systematic review. Int J Oral Maxillofac Implants. 2014;29(Suppl):25-42. https://doi.org/10.11607/jomi.2014suppl.g1.2
25. Modica F, Fava C, Benech A, Preti G. Radiologic-prosthetic planning of the surgical phase of the treatment of edentulism by osseointegrated implants: An in vitro study. J Prosthet Dent. 1991;65(4):541-6. https://doi.org/10.1016/0022-3913(91)90297-a
26. Vercruyssen M, Jacobs R, Van Assche N, van Steenberghe D. The use of CT scan-based planning for oral rehabilitation using implants and its transfer to the surgical field: A critical review on accuracy. J. Oral Rehabil. 2008;35(6):454-74. https://doi.org/10.1111/j.1365-2842.2007.01816.x
27. Kernen F, Kramer J, Wanner L, Wismeijer D, Nelson K, Flügge T. A review of virtual planning software for guided implant surgery - Data import and visualization, drill guide design and manufacturing. BMC Oral Health. 2020;20(1):251. https://doi.org/10.1186/s12903-020-01208-1
28. Wismeijer D, Joda T, Flügge T, Fokas G, Tahmaseb A, Bechelli, D, et al. Group 5 ITI Consensus Report: Digital technologies. Clin Oral Implant. Res. 2018;29(Suppl 16):436-42. https://doi.org/10.1111/clr.13309
29. Cattoni F, Chirico L, Merlone A, Manacorda M, Vinci R, Gherlone EF. Digital Smile Designed Computer-Aided Surgery versus Traditional Workflow in “All on Four” Rehabilitations: A Randomized Clinical Trial with 4-Year Follow-Up. Int J Environ Res Public Health 2021;18(7):3449. https://doi.org/10.3390/ijerph18073449
30. Vahdani N, Moudi E, Ghobadi F, Mohammadi E, Bijani A, Haghanifar S. Evaluation of the Metal Artifact Caused by Dental Implants in Cone Beam Computed Tomography Images. Maedica (Bucur). 2020;15(2):224-9. https://doi.org/10.26574/maedica.2020.15.2.224
31. Machado AH, Fardim KAC, Souza CF, Sotto-Maior BS, Assis NMSP, Devito KL. Effect of anatomical region on the formation of metal artefacts produced by dental implants in cone beam computed tomographic images. Dentomaxillofac Radiol. 2018;47(3):20170281. https://doi.org/10.1259/dmfr.20170281
32. Cebe F, Aktan AM, Ozsevik AS, Ciftci ME, Surmelioglu HD. The effects of different restorative materials on the detection of approximal caries in cone-beam computed tomography scans with and without metal artifact reduction mode. Oral Surg Oral Med Oral Pathol Oral Radiol. 2017;123(3):392-400. https://doi.org/10.1016/j.oooo.2016.11.008
33. Alaidrous M, Finkelman M, Kudara Y, Campos HC, Kim Y, Souza AB. Influence of zirconia crown artifacts on cone beam computed tomography scans and image superimposition of tomographic image and tooth surface scan: An in vitro study. J Prosthet Dent. 2021;125(4):684.e1-684.e8. https://doi.org/10.1016/j.prosdent.2020.06.028
34. Kocasarac H, Koenig LJ, Ustaoglu G, Oliveira ML, Freitas DQ. CBCT image artefacts generated by implants located inside the field of view or in the exomass. Dentomaxillofac Radiol. 2022;51(2):20210092. https://doi.org/10.1259/dmfr.20210092
35. Hinchy NV, Anderson NK, Mahdian M. Metal artifact reduction using common dental materials. Dentomaxillofac Radiol 2022:51(2):20210302. https://doi.org/10.1259/dmfr.20210302
36. Fontenele RC, Nascimento EH, Vasconcelos TV, Noujeim M, Freitas DQ. Magnitude of cone beam CT image artifacts related to zirconium and titanium implants: impact on image quality. Dentomaxillofac Radiol. 2018;47(6):20180021. https://doi.org/10.1259/dmfr.20180021