title: A systematic approach towards the objective evaluation of low-contrast performance in MDCT: combination of a full-reference image fidelity metric and a software phantom.
abstract: OBJECTIVE
  To assess the feasibility of an objective approach for the evaluation of low-contrast detectability in multidetector computed-tomography (MDCT) by combining a virtual phantom containing simulated lesions with an image quality metric.
  
  
  METHODS
  A low-contrast phantom containing hypodense spheric lesions (-20 HU) was scanned on a 64-slice MDCT scanner at 4 different dose levels (25, 50, 100, 200 mAs). In addition, virtual round hypodense low-contrast lesions (20 HU object contrast) based on real CT data were inserted into the lesion-free section of the datasets. The sliding-thin-slab algorithm was applied to the image data with an increasing slice-thickness from 1 to 15 slices. For each dataset containing simulated lesions a lesion-free counterpart was reconstructed and post-processed in the same manner. The low-contrast performance of all datasets containing virtual lesions was determined using a full-reference image quality metric (modified multiscale structural similarity index, MS-SSIM*). The results were validated against a reader-study of the real lesions.
  
  
  RESULTS
  For all dose levels and lesion sizes there was no statistically significant difference between the low-contrast performance as determined by the image quality metric when compared to the reader study (p<0.05). The intraclass correlation coefficient was 0.72, 0.82, 0.90 and 0.84 for lesion diameters of 4 mm, 5 mm, 8 mm and 10 mm, respectively. The use of the sliding-thin-slab algorithm improves lesion detectability by a factor ranging from 1.15 to 2.69 when compared with the original axial slice (0.625 mm).
  
  
  CONCLUSIONS
  The combination of a virtual phantom and a full-reference image quality metric enables a systematic, automated and objective evaluation of low-contrast detectability in MDCT datasets and correlates well with the judgment of human readers.
authors: Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany. Falck.Christian.von@mh-hannover.de
authors: Christian
authors: C
authors: von Falck
authors: Thomas
authors: T
authors: Rodt
authors: Stephan
authors: S
authors: Waldeck
authors: Dagmar
authors: D
authors: Hartung
authors: Bernhard
authors: B
authors: Meyer
authors: Frank
authors: F
authors: Wacker
authors: Hoen-oh
authors: HO
authors: Shin
mesh_terms: D000465:Algorithms; D005858:Germany; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods* / Q000592:standards*