Phantom study for CT artifacts of dental titanium implants and zirconia upper structures: the effects of occlusal plane angle setting and SEMAR algorithm

Chen YC, Chen MY, Chen TY. Improving dental implant outcomes: CNN-Based system accurately measures degree of peri-implantitis damage on periapical film. Bioengineering (Basel). 2023;10:640.

Article  PubMed  Google Scholar 

Sohmura T, Hojoh H, Kusumoto N. A novel method of removing artifacts because of metallic dental restorations in 3-D CT images of jaw bone. Clin Oral Implants Res. 2005;16:728–35.

Article  PubMed  Google Scholar 

Almohandes A, Lund H, Carcuac O. Accuracy of bone-level assessments following reconstructive surgical treatment of experimental peri-implantitis. Clin Oral Implants Res. 2022;33:433–40.

Article  PubMed  PubMed Central  Google Scholar 

Klinke T, Daboul A, Maron J. Artifacts in magnetic resonance imaging and computed tomography caused by dental materials. PLoS ONE. 2012;7: e31766.

Article  PubMed  PubMed Central  Google Scholar 

Wagenaar D, van der Graaf ER, van der Schaaf A. Quantitative comparison of commercial and non-commercial metal artifact reduction techniques in computed tomography. PLoS ONE. 2015;10: e0127932.

Article  PubMed  PubMed Central  Google Scholar 

Dong J, Hayakawa Y, Kannenberg S. Metal-induced streak artifact reduction using iterative reconstruction algorithms in X-ray computed tomography image of the dentoalveolar region. Oral Surg Oral Med Oral Pathol Oral Radiol. 2013;115:e63-73.

Article  PubMed  Google Scholar 

Gondim Teixeira PA, Meyer JB, Baumann C. Total hip prosthesis CT with single-energy projection-based metallic artifact reduction: impact on the visualization of specific periprosthetic soft tissue structures. Skeletal Radiol. 2014;43:1237–46.

Article  PubMed  Google Scholar 

De Crop A, Casselman J, Van Hoof T. Analysis of metal artifact reduction tools for dental hardware in CT scans of the oral cavity: kVp, iterative reconstruction, dual-energy CT, metal artifact reduction software: does it make a difference? Neuroradiology. 2015;57:841–9.

Article  PubMed  Google Scholar 

Huflage H, Grunz JP, Hackenbroch C. Metal artefact reduction in low-dose computed tomography: benefits of tin prefiltration versus postprocessing of dual-energy datasets over conventional CT imaging. Radiography (Lond). 2022;28:690–6.

Article  PubMed  Google Scholar 

Branco D, Kry S, Taylor P, Rong J. Evaluation of image quality of a novel computed tomography metal artifact management technique on an anthropomorphic head and neck phantom. Phys Imaging Radiat Oncol. 2021;17:111–6.

Article  PubMed  PubMed Central  Google Scholar 

Chou R, Chi HY, Lin YH. Comparison of quantitative measurements of four manufacturer’s metal artifact reduction techniques for CT imaging with a self-made acrylic phantom. Technol Health Care. 2020;28:273–87.

Article  PubMed  PubMed Central  Google Scholar 

Demirturk Kocasarac H, Ustaoglu G, Bayrak S. Evaluation of artifacts generated by titanium, zirconium, and titanium-zirconium alloy dental implants on MRI, CT, and CBCT images: a phantom study. Oral Surg Oral Med Oral Pathol Oral Radiol. 2019;127:535–44.

Article  PubMed  Google Scholar 

Smeets R, Schöllchen M, Gauer T. Artefacts in multimodal imaging of titanium, zirconium and binary titanium-zirconium alloy dental implants: an in vitro study. Dentomaxillofac Radiol. 2017;46:20160267.

Article  PubMed  PubMed Central  Google Scholar 

Lell MM, Meyer E, Kuefner MA. Normalized metal artifact reduction in head and neck computed tomography. Invest Radiol. 2012;47:415–21.

Article  PubMed  Google Scholar 

Hakim A, Slotboom J, Lieger O. Clinical evaluation of the iterative metal artefact reduction algorithm for postoperative CT examination after maxillofacial surgery. Dentomaxillofac Radiol. 2017;46:20160355.

Article  PubMed  PubMed Central  Google Scholar 

Khaleghi G, Hosntalab M, Sadeghi M. Neural network performance evaluation of simulated and genuine head-and-neck computed tomography images to reduce metal artifacts. J Med Signals Sens. 2022;12:269–77.

Article  PubMed  PubMed Central  Google Scholar 

Zhou P, Zhang C, Gao Z. Evaluation of the quality of CT images acquired with smart metal artifact reduction software. Open Life Sci. 2018;13:155–62.

Article  PubMed  PubMed Central  Google Scholar 

Hilgenfeld T, Juerchott A, Deisenhofer UK. Accuracy of cone-beam computed tomography, dental magnetic resonance imaging, and intraoral radiography for detecting peri-implant bone defects at single zirconia implants-An in vitro study. Clin Oral Implants Res. 2018;29:922–30.

Article  PubMed  Google Scholar 

Fontenele RC, Nascimento EH, Vasconcelos TV. Magnitude of cone beam CT image artifacts related to zirconium and titanium implants: impact on image quality. Dentomaxillofac Radiol. 2018;47:20180021.

Article  PubMed  PubMed Central  Google Scholar 

Vasconcelos TV, Bechara BB, McMahan CA. Evaluation of artifacts generated by zirconium implants in cone-beam computed tomography images. Noujeim Oral Surg Oral Med Oral Pathol Oral Radiol. 2017;123:265–72.

Article  PubMed  Google Scholar 

Schulze R. CBCT artefact-burden of zirconia-based as compared to titanium implants for different beam energies: an analytical approach. Sci Rep. 2022;12:15276.

Article  PubMed  PubMed Central  Google Scholar 

Xavier PNI, Vizzotto MB, Arús NA, Tiecher PFDS, Gamba TO, Fontana MP, Beltrão RG, da Silveira HLD. Influence of the presence of dental implants on the accuracy and difficulty level of diagnosis of furcation involvement in molars: an in vitro CBCT study. Clin Oral Implants Res. 2023;34:1385. https://doi.org/10.1111/clr.14182.

Article  PubMed  Google Scholar 

Kim YH, Lee C, Han SS, Jeon KJ, Choi YJ, Lee A. Quantitative analysis of metal artifact reduction using the auto-edge counting method in cone-beam computed tomography. Sci Rep. 2020;10:8872.

Article  PubMed  PubMed Central  Google Scholar 

Khosravifard A, Saberi BV, Khosravifard N, Motallebi S, Kajan ZD, Ghaffari ME. Application of an auto-edge counting method for quantification of metal artifacts in CBCT images: a multivariate analysis of object position, field of view size, tube voltage, and metal artifact reduction algorithm. Oral Surg Oral Med Oral Pathol Oral Radiol. 2021;132:735–43.

Article  PubMed  Google Scholar 

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