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Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition.

Publication ,  Journal Article
Beaulieu, CF; Napel, S; Daniel, BL; Ch'en, IY; Rubin, GD; Johnstone, IM; Jeffrey, RB
Published in: J Comput Assist Tomogr
1998

PURPOSE: Virtual colonoscopy is a new method of colon examination in which computer-aided 3D visualization of spiral CT simulates fiberoptic colonoscopy. We used a colon phantom containing various-sized spheres to determine the influence of CT acquisition parameters on lesion detectability and sizing. METHOD: Spherical plastic beads with diameters of 2.5, 4, 6, 8 and 10 mm were randomly attached to the inner wall of segments of plastic tubing. Groups of three sealed tubes were scanned at 3/1, 3/2, 5/1 collimation (mm)/pitch settings in orientations perpendicular and parallel to the scanner gantry. For each acquisition, image sets were reconstructed at intervals from 0.5 to 5.0 mm. Two blinded reviewers assessed transverse cross-sections of the phantoms for bead detection, using source CT images for images for acquisitions obtained with the tubes oriented perpendicular to the gantry and using orthogonal reformatted images for scans oriented parallel to the gantry. RESULTS: Detection of beads of > or = 4 mm was 100% for both tube orientations and for all collimator/pitch settings and reconstruction intervals. For the 2.5 mm beads, detection decreased to 78-94% for 5 mm collimation/pitch 2 scans when the phantom sections were oriented parallel to the gantry (p = 0.01). Apparent elongation of beads in the slice direction occurred as the collimation and pitch increased. The majority of the elongation (approximately 75%) was attributable to changing the collimator from 3 to 5 mm, with the remainder of the elongation due to doubling the pitch from 1 to 2. CONCLUSION: CT scanning at 5 mm collimation and up to pitch 2 is adequate for detection of high contrast lesions as small as 4 mm in this model. However, lesion size and geometry are less accurately depicted than at narrower collimation and lower pitch settings.

Duke Scholars

Published In

J Comput Assist Tomogr

DOI

ISSN

0363-8715

Publication Date

1998

Volume

22

Issue

4

Start / End Page

656 / 663

Location

United States

Related Subject Headings

  • User-Computer Interface
  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Poisson Distribution
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Humans
  • Fiber Optic Technology
  • Equipment Design
  • Confidence Intervals
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Beaulieu, C. F., Napel, S., Daniel, B. L., Ch’en, I. Y., Rubin, G. D., Johnstone, I. M., & Jeffrey, R. B. (1998). Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition. J Comput Assist Tomogr, 22(4), 656–663. https://doi.org/10.1097/00004728-199807000-00028
Beaulieu, C. F., S. Napel, B. L. Daniel, I. Y. Ch’en, G. D. Rubin, I. M. Johnstone, and R. B. Jeffrey. “Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition.J Comput Assist Tomogr 22, no. 4 (1998): 656–63. https://doi.org/10.1097/00004728-199807000-00028.
Beaulieu CF, Napel S, Daniel BL, Ch’en IY, Rubin GD, Johnstone IM, et al. Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition. J Comput Assist Tomogr. 1998;22(4):656–63.
Beaulieu, C. F., et al. “Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition.J Comput Assist Tomogr, vol. 22, no. 4, 1998, pp. 656–63. Pubmed, doi:10.1097/00004728-199807000-00028.
Beaulieu CF, Napel S, Daniel BL, Ch’en IY, Rubin GD, Johnstone IM, Jeffrey RB. Detection of colonic polyps in a phantom model: implications for virtual colonoscopy data acquisition. J Comput Assist Tomogr. 1998;22(4):656–663.

Published In

J Comput Assist Tomogr

DOI

ISSN

0363-8715

Publication Date

1998

Volume

22

Issue

4

Start / End Page

656 / 663

Location

United States

Related Subject Headings

  • User-Computer Interface
  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Poisson Distribution
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Humans
  • Fiber Optic Technology
  • Equipment Design
  • Confidence Intervals