title: Impact of image quality on the performance of computer-aided detection of pulmonary embolism.
abstract: OBJECTIVE
  The purpose of this article is to assess the relationship between CT image quality and the number and type of false-positive (FP) findings found by a prototype computer-aided detection (CAD) algorithm for automatic detection of pulmonary embolism (PE).
  
  
  METHODS
  This retrospective study included 278 subjects (138 men and 140 women; mean age, 57 years; range, 18-88 years) who underwent consecutive CT pulmonary angiographies performed during off hours. Twenty-four percent (68/278) of studies were reported as positive for PE. CAD findings were classified as true-positive or FP by two independent readers and, in cases of discordance, by a third radiologist. Each FP result was classified according to underlying cause. The degree of vascular enhancement, image noise, motion artifacts, overall quality, and presence of underlying lung disease were rated on a 4- or 5-point scale. Chi-square tests and t tests were used to test significance of differences.
  
  
  RESULTS
  The mean number of FP CAD findings was 4.7 (median, 2) per examination. Most were caused by veins (30% [389/1,298]) or airspace consolidations (22% [286/1,298]). There was a significant positive association between the number of FP findings and image noise, motion artifacts, low vascular enhancement, low overall quality, and the extent of underlying disease. On a per-embolism basis, sensitivity decreased from 70.6% (214/303) for scans with zero to five FP findings, to 62.3% (33/53) for scans with six to 10 FP findings, to 60% (12/20) for scans with more than 10 FP findings.
  
  
  CONCLUSIONS
  There is a strong association between CT image quality and the number of FP findings indicated by a CAD algorithm for the detection of PE.
authors.affiliation: Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands. rianne_wittenberg@hotmail.com
authors.forename: Rianne
authors.initials: R
authors.lastname: Wittenberg
authors.forename: Joost F
authors.initials: JF
authors.lastname: Peters
authors.forename: Jeroen J
authors.initials: JJ
authors.lastname: Sonnemans
authors.forename: Shandra
authors.initials: S
authors.lastname: Bipat
authors.forename: Mathias
authors.initials: M
authors.lastname: Prokop
authors.forename: Cornelia M
authors.initials: CM
authors.lastname: Schaefer-Prokop
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000792:Angiography / Q000379:methods; D016009:Chi-Square Distribution; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011655:Pulmonary Embolism / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000379:methods*