title: Potential contribution of multiplanar reconstruction (MPR) to computer-aided detection of lung nodules on MDCT.
abstract: OBJECTIVE
  To evaluate potential benefits of using multiplanar reconstruction (MPR) in computer-aided detection (CAD) of lung nodules on multidetector computed tomography (MDCT).
  
  
  METHODS
  MDCT datasets of 60 patients with suspected lung nodules were retrospectively collected. Using "second-read" CAD, two radiologists (Readers 1 and 2) independently interpreted these datasets for the detection of non-calcified nodules (≥ 4 mm) with concomitant confidence rating. They did this task twice, first without MPR (using only axial images), and then 4 weeks later with MPR (using also coronal and sagittal MPR images), where the total reading time per dataset, including the time taken to assess the detection results of CAD software (CAD assessment time), was recorded. The total reading time and CAD assessment time without MPR and those with MPR were statistically compared for each reader. The radiologists' performance for detecting nodules without MPR and the performance with MPR were compared using jackknife free-response receiver operating characteristic (JAFROC) analysis.
  
  
  RESULTS
  Compared to the CAD assessment time without MPR (mean, 69s and 57s for Readers 1 and 2), the CAD assessment time with MPR (mean, 46s and 45s for Readers 1 and 2) was significantly reduced (P<0.001). For Reader 1, the total reading time was also significantly shorter in the case with MPR. There was no significant difference between the detection performances without MPR and with MPR.
  
  
  CONCLUSIONS
  The use of MPR has the potential to improve the workflow in CAD of lung nodules on MDCT.
authors.affiliation: Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan. sumatsu@med.kobe-u.ac.jp
authors.forename: Sumiaki
authors.initials: S
authors.lastname: Matsumoto
authors.forename: Yoshiharu
authors.initials: Y
authors.lastname: Ohno
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Yamagata
authors.forename: Munenobu
authors.initials: M
authors.lastname: Nogami
authors.forename: Atsushi
authors.initials: A
authors.lastname: Kono
authors.forename: Kazuro
authors.initials: K
authors.lastname: Sugimura
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*