title: Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT.
abstract: OBJECTIVE
  To compare the dose-optimisation potential of a smoothing filtered backprojection (FBP) and a hybrid FBP/iterative algorithm to that of a standard FBP algorithm at three slice thicknesses for hepatic lesion detection with multidetector CT.
  
  
  METHODS
  A liver phantom containing a 9.5-mm opacity with a density of 10 HU below background was scanned at 125, 100, 75, 50 and 25 mAs. Data were reconstructed with standard FBP (B), smoothing FBP (A) and hybrid FBP/iterative (iDose(4)) algorithms at 5-, 3- and 1-mm collimation. 10 observers marked opacities using a four-point confidence scale. Jackknife alternative free-response receiver operating characteristic figure of merit (FOM), sensitivity and noise were calculated.
  
  
  RESULTS
  Compared with the 125-mAs/5-mm setting for each algorithm, significant reductions in FOM (p<0.05) and sensitivity (p<0.05) were found for all three algorithms for all exposures at 1-mm thickness and for all slice thicknesses at 25 mAs, with the exception of the 25-mAs/5-mm setting for the B algorithm. Sensitivity was also significantly reduced for all exposures at 3-mm thickness for the A algorithm (p<0.05). Noise for the A and iDose(4) algorithms was approximately 13% and 21% lower, respectively, than for the B algorithm.
  
  
  CONCLUSIONS
  Superior performance for hepatic lesion detection was not shown with either a smoothing FBP algorithm or a hybrid FBP/iterative algorithm compared with a standard FBP technique, even though noise reduction with thinner slices was demonstrated with the alternative approaches.
  
  
  CONCLUSIONS
  Reductions in image noise with non-standard CT algorithms do not necessarily translate to an improvement in low-contrast object detection.
authors: Medical Image Optimisation and Perception Group (MIOPeG), Medical Imaging & Radiation Sciences Faculty Research Group, Faculty of Health Sciences, University of Sydney, Sydney, Australia. Karen_Dobeli@health.qld.gov.au
authors: K L
authors: KL
authors: Dobeli
authors: S J
authors: SJ
authors: Lewis
authors: S R
authors: SR
authors: Meikle
authors: D L
authors: DL
authors: Thiele
authors: P C
authors: PC
authors: Brennan
mesh_terms: D000465:Algorithms; D006801:Humans; D008107:Liver Diseases / Q000000981:diagnostic imaging*; D061330:Multidetector Computed Tomography / Q000379:methods* / Q000592:standards; D019047:Phantoms, Imaging; D011829:Radiation Dosage
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