title: Temporal subtraction for detection of solitary pulmonary nodules on chest radiographs: evaluation of a commercially available computer-aided diagnosis system.
abstract: OBJECTIVE
  To evaluate the usefulness of a commercially available computer-aided diagnosis (CAD) system that incorporates temporal subtraction for the detection of solitary pulmonary nodules on chest radiographs by readers with different levels of experience.
  
  
  METHODS
  Sixty pairs of chest radiographs in 30 patients with newly detected solitary pulmonary nodules and 30 normal cases, all confirmed with serial chest computed tomography (CT), were obtained from screen-film or digital radiographic systems and were digitized (spatial resolution, 0.171 mm/pixel). Temporal subtraction images were produced with an iterative image-warping technique. Five chest radiologists and five residents evaluated both image sets for solitary nodules: set A, current and prior radiographs with temporal subtraction images, and set B, current and prior radiographs only. Assessment was performed with receiver operating characteristic (ROC) analysis of the images on a monitor (pixel size, 1,280 x 1,024) equipped with the system. The reading time needed by each reader was recorded in each case.
  
  
  RESULTS
  For the chest radiologists, no statistically significant difference was found between set A (area under the ROC curve [A(z)] = 0.934) and set B (A(z) = 0.964). For the residents, however, observer performance in set A (A(z) = 0.907) was superior to that in set B (A(z) = 0.855) (P <.05). For both groups, the mean reading time per case for set A (chest radiologists, 16.7 seconds; residents, 15.7 seconds) was significantly (P <.05) shorter than that for set B (chest radiologists, 20.4 seconds; residents, 26.2 seconds).
  
  
  CONCLUSIONS
  For the detection of solitary pulmonary nodules, the CAD system with temporal subtraction can promote efficiency for established chest radiologists and improvement in accuracy for less experienced readers.
authors.affiliation: Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.johkoh@radiol.med.osaka-u.ac.jp
authors.forename: Takeshi
authors.initials: T
authors.lastname: Johkoh
authors.forename: Takenori
authors.initials: T
authors.lastname: Kozuka
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Tomiyama
authors.forename: Seiki
authors.initials: S
authors.lastname: Hamada
authors.forename: Osamu
authors.initials: O
authors.lastname: Honda
authors.forename: Naoki
authors.initials: N
authors.lastname: Mihara
authors.forename: Mitsuhiro
authors.initials: M
authors.lastname: Koyama
authors.forename: Mitsuko
authors.initials: M
authors.lastname: Tsubamoto
authors.forename: Munehiro
authors.initials: M
authors.lastname: Maeda
authors.forename: Hironobu
authors.initials: H
authors.lastname: Nakamura
authors.forename: Hironori
authors.initials: H
authors.lastname: Saki
authors.forename: Keiichi
authors.initials: K
authors.lastname: Fujiwara
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods; D013902:Radiography, Thoracic; D012680:Sensitivity and Specificity; D013382:Subtraction Technique