3-dimensional adaptive raw-data filter: evaluation in low dose chest multidetector-row computed tomography

J Comput Assist Tomogr. 2006 Nov-Dec;30(6):933-8. doi: 10.1097/01.rct.0000221951.60393.64.

Abstract

Objectives: To evaluate a 3-dimensional adaptive raw-data filter in reducing streak artifacts in low dose chest computed tomographic (CT) images.

Methods: Fourteen adult patients who underwent low dose chest CT examination (parameters: 25 or 50 mAs, 120 kV) on 64-detector CTscanner were included in this study. We prepared 2 sets of contiguous 5-mm thick images by reconstruction with and without 3-dimensional adaptive raw-data filter (filter-processed and unprocessed images). Streak artifacts and visualization of peripheral vessels in both filter-processed and unprocessed images were evaluated using a 5-point scale. Upper, middle, and lower thorax were evaluated separately.

Results: The difference in artifact severity was statistically significant in upper and lower thorax (P = 0.002 and 0.03, respectively), whereas it was not significant in middle thorax (P = 0.13). The difference in the visibility of peripheral pulmonary vessels was not statistically significant in all anatomical regions.

Conclusions: The 3-dimensional adaptive raw-data filter reduced streak artifacts in low dose chest CT in upper and lower thorax.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Artifacts*
  • Female
  • Humans
  • Imaging, Three-Dimensional*
  • Male
  • Middle Aged
  • Radiation Dosage
  • Radiography, Thoracic / methods*
  • Tomography, X-Ray Computed / methods*