Noise Texture Deviation: A Measure for Quantifying Artifacts in Computed Tomography Images With Iterative Reconstructions

Invest Radiol. 2017 Feb;52(2):87-94. doi: 10.1097/RLI.0000000000000312.


Objectives: The aims of this study were to introduce the measure noise texture deviation as quantitative parameter for evaluating iterative reconstruction (IR)-specific artifacts in computed tomography (CT) images and to test whether IR-specific artifacts, quantified through this measure, are reduced in advanced modeled IR (ADMIRE) as compared with sinogram-affirmed IR (SAFIRE) images of the liver ex vivo and in patients with hypodense liver lesions.

Materials and methods: In the ex vivo study part, an abdominal phantom was used. In the institutional review board-approved in vivo study part, 40 consecutive patients (mean age, 63 years) with hypodense liver lesions undergoing abdominal CT in the portal-venous phase were included. Images were reconstructed with filtered back projection, with the second-generation IR algorithm SAFIRE and with the third-generation IR algorithm ADMIRE. Noise power spectra and noise texture deviation were calculated in the phantom; image noise was measured in the phantom and in patients. Two blinded readers evaluated all image data regarding IR-specific artifacts (plastic-like, blotchy appearance); patient data were evaluated regarding conspicuity and confidence for detecting hypodense liver lesions.

Results: Image noise was significantly reduced at increasing IR levels (P < 0.001) with both algorithms, with no significant differences between corresponding strength levels of SAFIRE and ADMIRE (all, P > 0.05). Noise power spectra were similar at corresponding strength levels of SAFIRE and ADMIRE (all, P > 0.05). Noise texture deviation in ADMIRE was reduced compared with corresponding strength levels of SAFIRE (all, P < 0.001) and strongly correlated with subjective IR-specific artifacts (r = 0.88, P < 0.001). Iterative reconstruction-specific artifacts were significantly reduced in ADMIRE compared with that in SAFIRE images at strength levels 3 or greater, both ex vivo and in vivo (all, P < 0.001). There were no significant differences in the readers' ratings of lesion conspicuity and lesion confidence in detecting hypodense liver lesions between SAFIRE and ADMIRE (P > 0.05). Only lesion conspicuity was superior with SAFIRE and ADMIRE compared with filtered back projection (all, P < 0.001).

Conclusions: Noise texture deviation is a quantitative measure reflecting IR-specific artifacts and is reduced in CT images with ADMIRE compared with SAFIRE.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Artifacts*
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Liver / diagnostic imaging
  • Liver Neoplasms / diagnostic imaging*
  • Male
  • Middle Aged
  • Models, Theoretical
  • Noise
  • Phantoms, Imaging
  • Radiation Dosage
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Tomography, X-Ray Computed / methods*