title: An Improved Index of Image Quality for Task-based Performance of CT Iterative Reconstruction across Three Commercial Implementations.
abstract: OBJECTIVE
  To develop and validate a metric of computed tomographic (CT) image quality that incorporates the noise texture and resolution properties of an image.
  
  
  METHODS
  Images of the American College of Radiology CT quality assurance phantom were acquired by using three commercial CT systems at seven dose levels with filtered back projection (FBP) and iterative reconstruction (IR). Image quality was characterized by the contrast-to-noise ratio (CNR) and a detectability index (d') that incorporated noise texture and spatial resolution. The measured CNR and d' were compared with a corresponding observer study by using the Spearman rank correlation coefficient to determine how well each metric reflects the ability of an observer to detect subtle lesions. Statistical significance of the correlation between each metric and observer performance was determined by using a Student t distribution; P values less than .05 indicated a significant correlation. Additionally, each metric was used to estimate the dose reduction potential of IR algorithms while maintaining image quality.
  
  
  RESULTS
  Across all dose levels, scanner models, and reconstruction algorithms, the d' correlated strongly with observer performance in the corresponding observer study (ρ = 0.95; P < .001), whereas the CNR correlated weakly with observer performance (ρ = 0.31; P = .21). Furthermore, the d' showed that the dose-reduction capabilities differed between clinical implementations (range, 12%-35%) and were less than those predicted from the CNR (range, 50%-54%).
  
  
  CONCLUSIONS
  The strong correlation between the observer performance and the d' indicates that the d' is superior to the CNR for the evaluation of CT image quality. Moreover, the results of this study indicate that the d' improves less than the CNR with the use of IR, which indicates less potential for IR dose reduction than previously thought.
authors: From the Department of Radiology, Duke University Medical Center, 2424 Erwin Rd, Suite 302, Durham, NC 27705 (O.C., E.S.); Department of Diagnostic Radiology, University of Maryland Medical Center, Baltimore, Md (J.J.S.C., Z.Y., C.T., E.L.S.); and Department of Software and Systems, National Institute of Standards and Technology, Gaithersburg, Md (G.S., A.D., J.J.F., A.P.).
authors: Olav
authors: O
authors: Christianson
authors: Joseph J S
authors: JJ
authors: Chen
authors: Zhitong
authors: Z
authors: Yang
authors: Ganesh
authors: G
authors: Saiprasad
authors: Alden
authors: A
authors: Dima
authors: James J
authors: JJ
authors: Filliben
authors: Adele
authors: A
authors: Peskin
authors: Christopher
authors: C
authors: Trimble
authors: Eliot L
authors: EL
authors: Siegel
authors: Ehsan
authors: E
authors: Samei
mesh_terms: D004867:Equipment Design; D007091:Image Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D013647:Task Performance and Analysis; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000592:standards*