title: Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance.
abstract: OBJECTIVE
  To evaluate the effect of computer-aided diagnosis (CAD) on radiologists' detection of pulmonary nodules.
  
  
  METHODS
  Fifty chest computed tomographic (CT) examination cases were used. The mean nodule size was 0.81 cm +/- 0.60 (SD) (range, 0.3-2.9 cm). Alternative free-response receiver operating characteristic (ROC) analysis with a continuous rating scale was used to compare the observers' performance in detecting nodules with and without use of CAD. Five board-certified radiologists and five radiology residents participated in an observer performance study. First they were asked to rate the probability of nodule presence without using CAD; then they were asked to rate the probability of nodule presence by using CAD.
  
  
  RESULTS
  For all radiologists, the mean areas under the best-fit alternative free-response ROC curves (Az) without and with CAD were 0.64 +/- 0.08 and 0.67 +/- 0.09, respectively, indicating a significant difference (P <.01). For the five board-certified radiologists, the mean Az values without and with CAD were 0.63 +/- 0.08 and 0.66 +/- 0.09, respectively, indicating a significant difference (P <.01). For the five resident radiologists, the mean Az values without and with CAD were 0.66 +/- 0.04 and 0.68 +/- 0.04, respectively, indicating a significant difference (P =.02). At observer performance analyses, there were no significant differences in Az values obtained either without (P =.61) or with (P =.88) CAD between the board-certified radiologists and the residents. For all radiologists, in the detection of pulmonary nodules 1.0 cm in diameter or smaller, the mean Az values without and with CAD were 0.60 +/- 0.11 and 0.64 +/- 0.11, respectively, indicating a significant difference (P <.01).
  
  
  CONCLUSIONS
  Use of the CAD system improved the board-certified radiologists' and residents' detection of pulmonary nodules at chest CT.
authors.affiliation: Department of Radiology, Kinki University School of Medicine, 377-2 Oono-higashi, Osaka-Sayama City, Osaka 589-8511, Japan.
authors.forename: Kazuo
authors.initials: K
authors.lastname: Awai
authors.forename: Kohei
authors.initials: K
authors.lastname: Murao
authors.forename: Akio
authors.initials: A
authors.lastname: Ozawa
authors.forename: Masanori
authors.initials: M
authors.lastname: Komi
authors.forename: Haruo
authors.initials: H
authors.lastname: Hayakawa
authors.forename: Shinichi
authors.initials: S
authors.lastname: Hori
authors.forename: Yasumasa
authors.initials: Y
authors.lastname: Nishimura
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D002983:Clinical Competence; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007396:Internship and Residency; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011237:Predictive Value of Tests; D012372:ROC Curve; D011871:Radiology / Q000193:education*; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D036542:Tomography, Spiral Computed