Imaging Sci Dent.  2017 Sep;47(3):189-197. 10.5624/isd.2017.47.3.189.

Quantitative assessment of image artifacts from root filling materials on CBCT scans made using several exposure parameters

• Rabelo KA
• Cavalcanti YW
• de Oliveira Pinto MG
• Sousa Melo SL
• Campos PS
• de Andrade Freitas Oliveira LS
• de Melo DP

• KMID: 2390084
• DOI: http://doi.org/10.5624/isd.2017.47.3.189

Abstract

PURPOSE
To quantify artifacts from different root filling materials in cone-beam computed tomography (CBCT) images acquired using different exposure parameters.
MATERIALS AND METHODS
Fifteen single-rooted teeth were scanned using 8 different exposure protocols with 3 different filling materials and once without filling material as a control group. Artifact quantification was performed by a trained observer who made measurements in the central axial slice of all acquired images in a fixed region of interest using ImageJ. Hyperdense artifacts, hypodense artifacts, and the remaining tooth area were identified, and the percentages of hyperdense and hypodense artifacts, remaining tooth area, and tooth area affected by the artifacts were calculated. Artifacts were analyzed qualitatively by 2 observers using the following scores: absence (0), moderate presence (1), and high presence (2) for hypodense halos, hypodense lines, and hyperdense lines. Two-way ANOVA and the post-hoc Tukey test were used for quantitative and qualitative artifact analysis. The Dunnet test was also used for qualitative analysis. The significance level was set at P<.05.
RESULTS
There were no significant interactions among the exposure parameters in the quantitative or qualitative analysis. Significant differences were observed among the studied filling materials in all quantitative analyses. In the qualitative analyses, all materials differed from the control group in terms of hypodense and hyperdense lines (P<.05). Fiberglass posts did not differ statistically from the control group in terms of hypodense halos (P>.05).
CONCLUSION
Different exposure parameters did not affect the objective or subjective observations of artifacts in CBCT images; however, the filling materials used in endodontic restorations did affect both types of assessments.

Keyword

Imaging, Three-Dimensional; Cone-Beam Computed Tomography; Artifacts

MeSH Terms

Artifacts*
Cone-Beam Computed Tomography
Imaging, Three-Dimensional
Tooth

Figure

• 

  Fig. 1 A human skull is coated with a 5-mm-thick layer of wax to simulate soft tissue, then immersed in a in a styrofoam box filled with water. The skull is positioned in the cone-beam computed tomography unit while taking the image.

• 

  Fig. 2 Axial cone-beam computed tomography images show a tooth with the 4 root filling conditions that were studied. A. Empty filling. B. ProTaper F5 gutta-percha point. C. Type III gold-alloy post. D. Prefabricated fiberglass post.

• 

  Fig. 3 Quantification of the hypodense area of image artifacts is performed with a limited threshold using ImageJ tools. A. Axial image of the tooth selected for artifact quantification. B. Hyperdense area selected based on the manually determined threshold range. C. Hyperdense area determined by ImageJ selection according to the threshold range. D. Resultant value of the selected area.

• 

  Fig. 4 Quantification of hyperdense of image artifacts is performed with a limited threshold using ImageJ tools. A. Axial image of the tooth selected for artifact quantification. B. Hypodense area selected based on the manually determined threshold range. C. Hypodense area determined by ImageJ selection according to the threshold range. D. Resultant value of the selected area.

Reference

1. Pauwels R, Stamatakis H, Bosmans H, Bogaerts R, Jacobs R, Horner K, et al. Quantification of metal artifacts on cone beam computed tomography images. Clin Oral Implants Res. 2013; 24:Suppl A100. 94–99.

2. Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, Schwanecke U, et al. Artefacts in CBCT: a review. Dentomaxillofac Radiol. 2011; 40:265–273.

3. Benic GI, Sancho-Puchades M, Jung RE, Deyhle H, Hämmerle CH. In vitro assessment of artifacts induced by titanium dental implants in cone beam computed tomography. Clin Oral Implants Res. 2013; 24:378–383.

4. Hassan B, Couto Souza P, Jacobs R, de Azambuja Berti S, van der Stelt P. Influence of scanning and reconstruction parameters on quality of three-dimensional surface models of the dental arches from cone beam computed tomography. Clin Oral Investig. 2010; 14:303–310.

5. Hunter AK, McDavid WD. Characterization and correction of cupping effect artefacts in cone beam CT. Dentomaxillofac Radiol. 2012; 41:217–223.

6. Nardi C, Borri C, Regini F, Calistri L, Castellani A, Lorini C, et al. Metal and motion artifacts by cone beam computed tomography (CBCT) in dental and maxillofacial study. Radiol Med. 2015; 120:618–626.

7. Vasconcelos KF, Nicolielo LF, Nascimento MC, Haiter-Neto F, Bóscolo FN, Van Dessel J, et al. Artefact expression associated with several cone-beam computed tomographic machines when imaging root filled teeth. Int Endod J. 2015; 48:994–1000.

8. Boas FE, Fleischmann D. Evaluation of two iterative techniques for reducing metal artifacts in computed tomography. Radiology. 2011; 259:894–902.

9. Bezerra IS, Neves FS, Vasconcelos TV, Ambrosano GM, Freitas DQ. Influence of the artifact reduction algorithm of Picasso Trio CBCT system on the diagnosis of vertical root fractures in teeth with metal posts. Dentomaxillofac Radiol. 2015; 44:20140428.

10. Chindasombatjaroen J, Kakimoto N, Murakami S, Maeda Y, Furukawa S. Quantitative analysis of metallic artefacts caused by dental metals: comparison of cone-beam and multi-detector row CT scanners. Oral Radiol. 2011; 27:114–120.

11. Bamba J, Araki K, Endo A, Okano T. Image quality assessment of three cone beam CT machines using the SEDENTEXCT CT phantom. Dentomaxillofac Radiol. 2013; 42:20120445.

12. Nackaerts O, Maes F, Yan H, Couto Souza P, Pauwels R, Jacobs R. Analysis of intensity variability in multislice and cone beam computed tomography. Clin Oral Implants Res. 2011; 22:873–879.

13. Bryant JA, Drage NA, Richmond S. Study of the scan uniformity from an i-CAT cone beam computed tomography dental imaging system. Dentomaxillofac Radiol. 2008; 37:365–374.

14. Pinto MGO, Rabelo KA, Sousa Melo SL, Campos PSF, Oliveira LSAF, Bento PM, et al. Influence of exposure parameters on the detection of simulated root fractures in the presence of various intracanal materials. Int Endod J. 2017; 50:586–594.

15. Scarfe WC, Farman AG. What is cone-beam CT and how does it work? Dent Clin North Am. 2008; 52:707–730.

16. Nagarajappa AK, Dwivedi N, Tiwari R. Artifacts: the downturn of CBCT image. J Int Soc Prev Community Dent. 2015; 5:440–445.

17. Barrett JF, Keat N. Artifacts in CT: recognition and avoidance. Radiographics. 2004; 24:1679–1691.

18. Bechara B, McMahan CA, Noujeim M, Faddoul T, Moore WS, Teixeira FB, et al. Comparison of cone beam CT scans with enhanced photostimulated phosphor plate images in the detection of root fracture of endodontically treated teeth. Dentomaxillofac Radiol. 2013; 42:20120404.

19. Esmaeili F, Johari M, Haddadi P. Beam hardening artifacts by dental implants: comparison of cone-beam and 64-slice computed tomography scanners. Dent Res J (Isfahan). 2013; 10:376–381.

20. Kamburoglu K, Onder B, Murat S, Avsever H, Yüksel S, Paksoy CS. Radiographic detection of artificially created horizontal root fracture using different cone beam CT units with small fields of view. Dentomaxillofac Radiol. 2013; 42:20120261.

21. de Rezende Barbosa GL, Sousa Melo SL, Alencar PN, Nascimento MC, Almeida SM. Performance of an artefact reduction algorithm in the diagnosis of in vitro vertical root fracture in four different root filling conditions on CBCT images. Int Endod J. 2016; 49:500–508.

22. Helvacioglu-Yigit D, Demirturk Kocasarac H, Bechara B, Noujeim M. Evaluation and reduction of artifacts generated by 4 different root-end filling materials by using multiple cone-beam computed tomography imaging settings. J Endod. 2016; 42:307–314.

23. de-Azevedo-Vaz SL, Peyneau PD, Ramirez-Sotelo LR, Vasconcelos Kde F, Campos PS, Haiter-Neto F. Efficacy of a cone beam computed tomography metal artifact reduction algorithm for the detection of peri-implant fenestrations and dehiscences. Oral Surg Oral Med Oral Pathol Oral Radiol. 2016; 121:550–556.

24. Draenert FG, Coppenrath E, Herzog P, Müller S, Mueller-Lisse UG. Beam hardening artefacts occur in dental implant scans with the NewTom cone beam CT but not with the dental 4-row multidetector CT. Dentomaxillofac Radiol. 2007; 36:198–203.

25. Schulze RK, Berndt D, d’Hoedt B. On cone-beam computed tomography artifacts induced by titanium implants. Clin Oral Implants Res. 2010; 21:100–107.

26. Jaju PP, Jain M, Singh A, Gupta A. Artefacts in cone beam CT. Open J Stomatol. 2013; 3:292–297.

27. van der Schaaf I, van Leeuwen M, Vlassenbroek A, Velthuis B. Minimizing clip artifacts in multi CT angiography of clipped patients. AJNR Am J Neuroradiol. 2006; 27:60–66.

28. Araki K, Okano T. The effect of surrounding conditions on pixel value of cone beam computed tomography. Clin Oral Implants Res. 2013; 24:862–865.

29. Bechara BB, Moore WS, McMahan CA, Noujeim M. Metal artefact reduction with cone beam CT: an in vitro study. Dentomaxillofac Radiol. 2012; 41:248–253.

30. Bechara B, McMahan CA, Geha H, Noujeim M. Evaluation of a cone beam CT artefact reduction algorithm. Dentomaxillofac Radiol. 2012; 41:422–428.

31. Ferreira LM, Visconti MA, Nascimento HA, Dallemolle RR, Ambrosano GM, Freitas DQ. Influence of CBCT enhancement filters on diagnosis of vertical root fractures: a simulation study in endodontically treated teeth with and without intracanal posts. Dentomaxillofac Radiol. 2015; 44:20140352.