Imaging Sci Dent.  2017 Mar;47(1):11-15. 10.5624/isd.2017.47.1.11.

Intraobserver and interobserver reproducibility in linear measurements on axial images obtained by cone-beam computed tomography

Affiliations
  • 1São Leopoldo Mandic Research Center, Department of Oral Radiology, College of Dentistry, São Paulo, SP, Brazil. ricardoraitz@ig.com.br
  • 2Department of Oral Radiology, College of Dentistry, Catholic University of Brasilia, São Paulo, SP, Brazil.

Abstract

PURPOSE
This study was performed to investigate the intra- and inter-observer variability in linear measurements with axial images obtained by PreXion (PreXion Inc., San Mateo, USA) and i-CAT (Imaging Sciences International, Xoran Technologies Inc., Hatfield, USA) CBCT scanners, with different voxel sizes.
MATERIALS AND METHODS
A cylindrical object made from nylon with radiopaque markers (phantom) was scanned by i-CAT and PreXion 3D devices. For each axial image, measurements were taken twice in the horizontal (distance A-B) and vertical (distance C-D) directions, randomly, with a one-week interval between measurements, by four oral radiologists with five years or more experience in the use of these measuring tools.
RESULTS
All of the obtained linear measurements had lower values than those of the phantom. The statistical analysis showed high intra- and inter-observer reliability (p=0.297). Compared to the real measurements, the measurements obtained using the i-CAT device and PreXion tomography, on average, revealed absolute errors ranging from 0.22 to 0.59 mm and from 0.23 to 0.63 mm, respectively.
CONCLUSION
It can be concluded that both scanners are accurate, although the linear measurements are underestimations, with no significant differences between the evaluators.

Keyword

Cone-Beam Computed Tomography; Dimensional Measurement Accuracy; Reproducibility of Results

MeSH Terms

Cone-Beam Computed Tomography*
Dimensional Measurement Accuracy
Nylons
Observer Variation
Reproducibility of Results
Nylons

Figure

  • Fig. 1 The universal measuring machine.

  • Fig. 2 Phantom image with the coordinates A1, B1, C1, and D1.

  • Fig. 3 Identifying coordinates of the phantom.


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