Informatics in radiology: sliding-thin-slab averaging for improved depiction of low-contrast lesions with radiation dose savings at thin-section CT

Radiographics. 2010 Mar;30(2):317-26. doi: 10.1148/rg.302096007. Epub 2010 Jan 12.

Abstract

Current multidetector computed tomography (CT) scanners allow volumetric data acquisition with thin-section collimations and overlapping section reconstructions. The resultant nearly isotropic data sets help minimize partial-volume averaging effects and are ideal for two- and three-dimensional postprocessing and software-assisted lesion detection and quantification. However, the section thickness, image noise, and radiation dose are closely related, and when one parameter must be altered to suit the clinical setting, the others may be affected. When the clinical purpose demands both high spatial resolution and low image noise (eg, for the detection of hypoattenuating lesions in organs such as the kidneys and liver), the necessary trade-off--an increase in the radiation dose to the patient--may be unacceptable. The application of a sliding-thin-slab averaging algorithm during image postprocessing and review helps overcome this limitation by reconstructing thicker sections with lower noise levels from thin-section data obtained with dose-saving protocols. In principle, a high noise level is acceptable in the initial reconstruction of the CT volume data set. During image review at the workstation, the section thickness can be interactively increased to minimize image noise and improve lesion detectability. The combination of thin-section scanning with thick-section display allows routine volumetric imaging without a general increase in radiation dose or a reduction in the detectability of low-contrast lesions. Supplemental material available at http://radiographics.rsna.org/lookup/suppl/doi:10.1148/rg.302096007/-/DC1.

Publication types

  • Evaluation Study

MeSH terms

  • Algorithms*
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Radiation Dosage
  • Radiographic Image Enhancement / methods
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed / methods*