title: Upgrade to iterative image reconstruction (IR) in MDCT imaging: a clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR) Part2: The chest.
abstract: OBJECTIVE
  To compare the image quality in dose-reduced 64-row CT of the chest at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed solely with filtered back projection (FBP) in a realistic upgrade scenario.
  
  
  METHODS
  A waiver of consent was granted by the institutional review board (IRB). The noise index (NI) relates to the standard deviation of Hounsfield units in a water phantom. Baseline exams of the chest (NI = 29; LightSpeed VCT XT, GE Healthcare) were intra-individually compared to follow-up studies on a CT with ASIR after system upgrade (NI = 45; Discovery HD750, GE Healthcare), n = 46. Images were calculated in slice and volume mode with ASIR levels of 0 - 100 % in the standard and lung kernel. Three radiologists independently compared the image quality to the corresponding full-dose baseline examinations (-2: diagnostically inferior, -1: inferior, 0: equal, + 1: superior, + 2: diagnostically superior). Statistical analysis used Wilcoxon's test, Mann-Whitney U test and the intraclass correlation coefficient (ICC).
  
  
  RESULTS
  The mean CTDIvol decreased by 53 % from the FBP baseline to 8.0 ± 2.3 mGy for ASIR follow-ups; p < 0.001. The ICC was 0.70. Regarding the standard kernel, the image quality in dose-reduced studies was comparable to the baseline at ASIR 70 % in volume mode (-0.07 ± 0.29, p = 0.29). Concerning the lung kernel, every ASIR level outperformed the baseline image quality (p < 0.001), with ASIR 30 % rated best (slice: 0.70 ± 0.6, volume: 0.74 ± 0.61).
  
  
  CONCLUSIONS
  Vendors' recommendation of 50 % ASIR is fair. In detail, the ASIR 70 % in volume mode for the standard kernel and ASIR 30 % for the lung kernel performed best, allowing for a dose reduction of approximately 50 %.
authors.affiliation: Institut für klinische Radiologie, Ludwig-Maximilian-University München, Nussbaumstraße 20, 80336 München, Germany. fabian.mueck@med.unimuenchen.de
authors.forename: F G
authors.initials: FG
authors.lastname: Mueck
authors.forename: L
authors.initials: L
authors.lastname: Michael
authors.forename: Z
authors.initials: Z
authors.lastname: Deak
authors.forename: M K
authors.initials: MK
authors.lastname: Scherr
authors.forename: D
authors.initials: D
authors.lastname: Maxien
authors.forename: L L
authors.initials: LL
authors.lastname: Geyer
authors.forename: M
authors.initials: M
authors.lastname: Reiser
authors.forename: S
authors.initials: S
authors.lastname: Wirth
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055815:Young Adult