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CBCT Artifact Evaluation in a Single Device: Insights and Limitations

Year 2024, Volume: 14 Issue: 2, 349 - 356, 28.06.2024
https://doi.org/10.33808/clinexphealthsci.1291106

Abstract

Objective: To classify the types of artifacts in cone-beam computed tomography (CBCT) and to evaluate them according to age and gender.
Methods: CBCT images of 1500 patients (766 males and 734 females) aged 5-92 (mean age: 40.89 ± 18.82 years) were retrospectively evaluated and the patients were categorized into 4 age groups: under 20 years old, 20-39 ages, 40-59 and over 60 years old. The types of artifacts encountered in CBCT images were classified. The relationship between the artifact types with age and gender were investigated. Chi-square test was applied to analyze the relationships between variables and distribution of parameters.
Results: Of the cases, 284 (18.9%) were under the age of 20, 389 (25.9%) were between the ages of 20-39, 554 (36.9%) were between the ages of 40-59 and 273 (18.2%) were over the age of 60. Moire artifact was observed at the highest rate (100%), while motion artifact was determined at the lowest rate (19.5%), and no ring artifact was detected in the analyzed images. Metallic artifact, metallic artifact removal, streak artifact and presence of dark bands were found to be statistically significant in females (p = .002, p = .001, p = .002 and p = .002, respectively). There was no statistically significant correlation between cupping artifact, metallic artifact, metallic artifact removal, streak artifact, dark band and noise, and stitched artifact (p > .05).
Conclusion: Both device and patient-based artifacts in CBCT images should be known, as well as the ways to prevent them.

References

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  • Tsiklakis K, Donta C, Gavala S. Dose reduction in maxillofacial imaging using low dose Cone Beam CT. Eur J Radiol. 2005;56(3):413-417. DOI: 10.1016/j.ejrad.2005.05.011
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  • Rigolone M, Pasqualini D, Bianchi L, Berutti E, Bianchi SD. Vestibular surgical access to the palatine root of the superior first molar: “Low-dose cone-beam” CT analysis of the pathway and its anatomic variations. J Endod. 2003;29(11):773-775. DOI: 10.1097/00004770-200311000-00021
  • Schulze R, Heil U, Groβ D. Artefacts in CBCT: A review. Dentomaxillofac Radiol. 2011;40(5):265-273. DOI: 10.1259/dmfr/30642039
  • Jaju PP, Jain M, Singh A, Gupta A. Artefacts in cone beam CT. Open J Stomatol. 2013; 3(05):292. DOI: 10.4236/ojst.2013.35049
  • Nagarajappa AK, Dwivedi N, Tiwari R. Artifacts: The downturn of CBCT image. J Int Soc Prev Community Dent. 2015;5(6):440. DOI: 10.4103/2231-0762.170523
  • Makins SR. Artifacts interfering with interpretation of cone beam computed tomography images. Dent Clin North Am. 2014;58(3):485-495. DOI: 10.1016/j.cden.2014.04.007
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  • Scarfe WC, Farman AG. What is cone-beam CT and how does it work? Dent Clin North Am. 2008;52(4):707-730. DOI: 10.1016/j.cden.2008.05.005
  • Nardi C, Borri C, Regini F, Calistri L, Castellani A, Lorini C. Metal and motion artifacts by cone beam computed tomography (CBCT) in dental and maxillofacial study. Radiol Med. 2015;120(7):618-626. DOI: 10.1007/s11547-015-0496-2
  • Donaldson K, O'Connor S, Heath N. Dental cone beam CT image quality possibly reduced by patient movement. Dentomaxillofac Radiol. 2013;42(2):91866873. DOI: 10.1259/dmfr/91866873
  • Santaella GM, Wenzel A, Haiter-Neto F, Rosalen PL, Spin-Neto R. Impact of movement and motion-artefact correction on image quality and interpretability in CBCT units with aligned and lateral-offset detectors. Dentomaxillofac Radiol. 2020;49(1):20190240. DOI: 10.1259/dmfr/91866873
  • Yildizer Keris E , Demirel O, Ozdede M. Evaluation of motion artifacts in cone-beam computed tomography with three different patient positioning. Oral Radiol. 2021;37:276-281. DOI: 10.1007/s11282-020-00446-x
  • Washio H, Ohira S, Funama Y. Metal artifact reduction using iterative CBCT reconstruction algorithm for head and neck radiation therapy: A phantom and clinical study. Eur J Radiol. 2020;132:109293. DOI: 10.1016/j.ejrad.2020.109293
  • de Faria Vasconcelos K, Queiroz PM, Codari M. A quantitative analysis of metal artifact reduction algorithm performance in volume correction with 3 CBCT devices. Oral Surg Oral Med Oral Pathol Oral Radiol. 2020;130(3):328-335. DOI: 10.1016/j.oooo.2020.03.049
  • Fontenele RC, Nascimento EH, Santaella GM, Freitas DQ. Does the metal artifact reduction algorithm activation mode influence the magnitude of artifacts in CBCT images? Imaging Sci Dent. 2020;50(1):23. DOI: 10.5624/isd.2020.50.1.23?
  • Phaneuf T, Kishen A, Moayedi M, Lam EW. Effectiveness of commercial software–enhanced image artifact reduction software. J Endod. 2021;47(5):820-826. DOI: 10.1016/j.joen.2020.11.028
  • Sun T, Jacobs R, Pauwels R. A motion correction approach for oral and maxillofacial cone-beam CT imaging. Phys Med Biol. 2021;66(12):125008. DOI 10.1088/1361-6560/abfa38
  • Yıldızer Keriş E. Effect of patient anxiety on image motion artefacts in CBCT. BMC Oral Health 2017;17(1):1-9. DOI: 10.1186/s12903-017-0367-4
  • White SC, Pharoah MJ. Oral radiol E-Book: Principles and interpretation: Elsevier Health Sciences; 2014. ISNB: 978-0-323-09633-1
  • Gross D, Heil U, Schulze R, Schoemer E, Schwanecke U. GPU-based volume reconstruction from very few arbitrarily aligned X-ray images. SIAM J Sci Comput. 2010;31(6):4204-4221. DOI: 10.1137/080736739
  • Hunter AK, McDavid W. Characterization and correction of cupping effect artefacts in cone beam CT. Dentomaxillofac Radiol. 2012;41(3):217-223. DOI: 10.1259/dmfr/19015946
  • Luckow M, Deyhle H, Beckmann F, Dagassan-Berndt D, Müller B. Tilting the jaw to improve the image quality or to reduce the dose in cone-beam computed tomography. Eur J Radiol. 2011;80(3):e389-393. DOI: 10.1016/j.ejrad.2010.10.001
  • Spin-Neto R, Mudrak J, Matzen L. Cone beam CT image artefacts related to head motion simulated by a robot skull: Visual characteristics and impact on image quality. Dentomaxillofac Radiol. 2013;42(2):32310645. DOI: 10.1259/dmfr/32310645
  • Scarfe WC, Li Z, Aboelmaaty W, Scott SA, Farman AG. Maxillofacial cone beam computed tomography: Essence, elements and steps to interpretation. Aust Dent J. 2012;57:46-60. DOI: 10.1111/j.1834-7819.2011.01657.x
Year 2024, Volume: 14 Issue: 2, 349 - 356, 28.06.2024
https://doi.org/10.33808/clinexphealthsci.1291106

Abstract

References

  • Bhoosreddy AR, Sakhavalkar PU. Image deteriorating factors in cone beam computed tomography, their classification, and measures to reduce them: A pictorial essay. JAMA Oncol. 2014;26(3):293. DOI: 10.4103/0972-1363.145009
  • Tsiklakis K, Donta C, Gavala S. Dose reduction in maxillofacial imaging using low dose Cone Beam CT. Eur J Radiol. 2005;56(3):413-417. DOI: 10.1016/j.ejrad.2005.05.011
  • Miracle A, Mukherji S. Cone beam CT of the head and neck, part 1: Physical principles. AJNR Am J Neuroradiol. 2009;30(6):1088-1095. DOI: 10.3174/ajnr.A1653
  • Rigolone M, Pasqualini D, Bianchi L, Berutti E, Bianchi SD. Vestibular surgical access to the palatine root of the superior first molar: “Low-dose cone-beam” CT analysis of the pathway and its anatomic variations. J Endod. 2003;29(11):773-775. DOI: 10.1097/00004770-200311000-00021
  • Schulze R, Heil U, Groβ D. Artefacts in CBCT: A review. Dentomaxillofac Radiol. 2011;40(5):265-273. DOI: 10.1259/dmfr/30642039
  • Jaju PP, Jain M, Singh A, Gupta A. Artefacts in cone beam CT. Open J Stomatol. 2013; 3(05):292. DOI: 10.4236/ojst.2013.35049
  • Nagarajappa AK, Dwivedi N, Tiwari R. Artifacts: The downturn of CBCT image. J Int Soc Prev Community Dent. 2015;5(6):440. DOI: 10.4103/2231-0762.170523
  • Makins SR. Artifacts interfering with interpretation of cone beam computed tomography images. Dent Clin North Am. 2014;58(3):485-495. DOI: 10.1016/j.cden.2014.04.007
  • Sinha A, Mishra A, Srivastava S, Sinha PM, Chaurasia A. Understanding artifacts in cone beam computed tomography. Int J Maxillofac Imaging. 2016;2:51-54. https://www.academia.edu/download/47580007/IJMI_22_51-54.pdf
  • Scarfe WC, Farman AG. What is cone-beam CT and how does it work? Dent Clin North Am. 2008;52(4):707-730. DOI: 10.1016/j.cden.2008.05.005
  • Nardi C, Borri C, Regini F, Calistri L, Castellani A, Lorini C. Metal and motion artifacts by cone beam computed tomography (CBCT) in dental and maxillofacial study. Radiol Med. 2015;120(7):618-626. DOI: 10.1007/s11547-015-0496-2
  • Donaldson K, O'Connor S, Heath N. Dental cone beam CT image quality possibly reduced by patient movement. Dentomaxillofac Radiol. 2013;42(2):91866873. DOI: 10.1259/dmfr/91866873
  • Santaella GM, Wenzel A, Haiter-Neto F, Rosalen PL, Spin-Neto R. Impact of movement and motion-artefact correction on image quality and interpretability in CBCT units with aligned and lateral-offset detectors. Dentomaxillofac Radiol. 2020;49(1):20190240. DOI: 10.1259/dmfr/91866873
  • Yildizer Keris E , Demirel O, Ozdede M. Evaluation of motion artifacts in cone-beam computed tomography with three different patient positioning. Oral Radiol. 2021;37:276-281. DOI: 10.1007/s11282-020-00446-x
  • Washio H, Ohira S, Funama Y. Metal artifact reduction using iterative CBCT reconstruction algorithm for head and neck radiation therapy: A phantom and clinical study. Eur J Radiol. 2020;132:109293. DOI: 10.1016/j.ejrad.2020.109293
  • de Faria Vasconcelos K, Queiroz PM, Codari M. A quantitative analysis of metal artifact reduction algorithm performance in volume correction with 3 CBCT devices. Oral Surg Oral Med Oral Pathol Oral Radiol. 2020;130(3):328-335. DOI: 10.1016/j.oooo.2020.03.049
  • Fontenele RC, Nascimento EH, Santaella GM, Freitas DQ. Does the metal artifact reduction algorithm activation mode influence the magnitude of artifacts in CBCT images? Imaging Sci Dent. 2020;50(1):23. DOI: 10.5624/isd.2020.50.1.23?
  • Phaneuf T, Kishen A, Moayedi M, Lam EW. Effectiveness of commercial software–enhanced image artifact reduction software. J Endod. 2021;47(5):820-826. DOI: 10.1016/j.joen.2020.11.028
  • Sun T, Jacobs R, Pauwels R. A motion correction approach for oral and maxillofacial cone-beam CT imaging. Phys Med Biol. 2021;66(12):125008. DOI 10.1088/1361-6560/abfa38
  • Yıldızer Keriş E. Effect of patient anxiety on image motion artefacts in CBCT. BMC Oral Health 2017;17(1):1-9. DOI: 10.1186/s12903-017-0367-4
  • White SC, Pharoah MJ. Oral radiol E-Book: Principles and interpretation: Elsevier Health Sciences; 2014. ISNB: 978-0-323-09633-1
  • Gross D, Heil U, Schulze R, Schoemer E, Schwanecke U. GPU-based volume reconstruction from very few arbitrarily aligned X-ray images. SIAM J Sci Comput. 2010;31(6):4204-4221. DOI: 10.1137/080736739
  • Hunter AK, McDavid W. Characterization and correction of cupping effect artefacts in cone beam CT. Dentomaxillofac Radiol. 2012;41(3):217-223. DOI: 10.1259/dmfr/19015946
  • Luckow M, Deyhle H, Beckmann F, Dagassan-Berndt D, Müller B. Tilting the jaw to improve the image quality or to reduce the dose in cone-beam computed tomography. Eur J Radiol. 2011;80(3):e389-393. DOI: 10.1016/j.ejrad.2010.10.001
  • Spin-Neto R, Mudrak J, Matzen L. Cone beam CT image artefacts related to head motion simulated by a robot skull: Visual characteristics and impact on image quality. Dentomaxillofac Radiol. 2013;42(2):32310645. DOI: 10.1259/dmfr/32310645
  • Scarfe WC, Li Z, Aboelmaaty W, Scott SA, Farman AG. Maxillofacial cone beam computed tomography: Essence, elements and steps to interpretation. Aust Dent J. 2012;57:46-60. DOI: 10.1111/j.1834-7819.2011.01657.x
There are 26 citations in total.

Details

Primary Language English
Subjects Oral and Maxillofacial Radiology
Journal Section Articles
Authors

Eda Didem Yalçın 0000-0001-8970-7579

Elif Meltem Aslan Öztürk 0000-0002-1737-9585

Publication Date June 28, 2024
Submission Date May 4, 2023
Published in Issue Year 2024 Volume: 14 Issue: 2

Cite

APA Yalçın, E. D., & Aslan Öztürk, E. M. (2024). CBCT Artifact Evaluation in a Single Device: Insights and Limitations. Clinical and Experimental Health Sciences, 14(2), 349-356. https://doi.org/10.33808/clinexphealthsci.1291106
AMA Yalçın ED, Aslan Öztürk EM. CBCT Artifact Evaluation in a Single Device: Insights and Limitations. Clinical and Experimental Health Sciences. June 2024;14(2):349-356. doi:10.33808/clinexphealthsci.1291106
Chicago Yalçın, Eda Didem, and Elif Meltem Aslan Öztürk. “CBCT Artifact Evaluation in a Single Device: Insights and Limitations”. Clinical and Experimental Health Sciences 14, no. 2 (June 2024): 349-56. https://doi.org/10.33808/clinexphealthsci.1291106.
EndNote Yalçın ED, Aslan Öztürk EM (June 1, 2024) CBCT Artifact Evaluation in a Single Device: Insights and Limitations. Clinical and Experimental Health Sciences 14 2 349–356.
IEEE E. D. Yalçın and E. M. Aslan Öztürk, “CBCT Artifact Evaluation in a Single Device: Insights and Limitations”, Clinical and Experimental Health Sciences, vol. 14, no. 2, pp. 349–356, 2024, doi: 10.33808/clinexphealthsci.1291106.
ISNAD Yalçın, Eda Didem - Aslan Öztürk, Elif Meltem. “CBCT Artifact Evaluation in a Single Device: Insights and Limitations”. Clinical and Experimental Health Sciences 14/2 (June 2024), 349-356. https://doi.org/10.33808/clinexphealthsci.1291106.
JAMA Yalçın ED, Aslan Öztürk EM. CBCT Artifact Evaluation in a Single Device: Insights and Limitations. Clinical and Experimental Health Sciences. 2024;14:349–356.
MLA Yalçın, Eda Didem and Elif Meltem Aslan Öztürk. “CBCT Artifact Evaluation in a Single Device: Insights and Limitations”. Clinical and Experimental Health Sciences, vol. 14, no. 2, 2024, pp. 349-56, doi:10.33808/clinexphealthsci.1291106.
Vancouver Yalçın ED, Aslan Öztürk EM. CBCT Artifact Evaluation in a Single Device: Insights and Limitations. Clinical and Experimental Health Sciences. 2024;14(2):349-56.

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