Quantitative Measurements Versus Receiver Operating Characteristics and Visual Grading Regression in CT Images Reconstructed with Iterative Reconstruction: A Phantom Study

Acad Radiol. 2018 Apr;25(4):509-518. doi: 10.1016/j.acra.2017.10.020. Epub 2017 Nov 29.

Abstract

Rationale and objectives: This study aimed to evaluate the correlation of quantitative measurements with visual grading regression (VGR) and receiver operating characteristics (ROC) analysis in computed tomography (CT) images reconstructed with iterative reconstruction.

Materials and methods: CT scans on a liver phantom were performed on CT scanners from GE, Philips, and Toshiba at three dose levels. Images were reconstructed with filtered back projection (FBP) and hybrid iterative techniques (ASiR, iDose, and AIDR 3D of different strengths). Images were visually assessed by five readers using a four- and five-grade ordinal scale for liver low contrast lesions and for 10 image quality criteria. The results were analyzed with ROC and VGR. Standard deviation, signal-to-noise ratios, and contrast-to-noise ratios were measured in the images.

Results: All data were compared to FBP. The results of the quantitative measurements were improved for all algorithms. ROC analysis showed improved lesion detection with ASiR and AIDR and decreased lesion detection with iDose. VGR found improved noise properties for all algorithms, increased sharpness with iDose and AIDR, and decreased artifacts from the spine with AIDR, whereas iDose increased the artifacts from the spine. The contrast in the spine decreased with ASiR and iDose.

Conclusions: Improved quantitative measurements in images reconstructed with iterative reconstruction compared to FBP are not equivalent to improved diagnostic image accuracy.

Keywords: CT iterative reconstruction; diagnostic accuracy; quantitative measurements; receiver operating characteristics; visual grading regression.

Publication types

  • Comparative Study

MeSH terms

  • Algorithms
  • Artifacts
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Liver / diagnostic imaging
  • Phantoms, Imaging
  • ROC Curve
  • Radiation Dosage
  • Radiographic Image Interpretation, Computer-Assisted*
  • Signal-To-Noise Ratio
  • Tomography, X-Ray Computed*