title: Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT.
abstract: OBJECTIVE
  To evaluate how computer-aided diagnosis (CAD) can improve radiologists' recommendations for management of possible early lung cancers on CT.
  
  
  METHODS
  Twenty-eight lung cancers and 28 benign lesions were employed. Each group of 28 lesions was classified into subgroups of two sizes (9 between 6 and 10 mm and 19 between 11 and 20 mm) and three patterns (8 with pure ground glass opacity [GGO], 12 with mixed GGO and 8 solid lesions). Sixteen radiologists participated in the observer study, first without and then with CAD. Radiologists' recommendations, including (1) follow-up in 12 months, (2) in 6 months, (3) in 3 months, or (4) biopsy, were compared at three levels of their malignancy probability ratings (low: 1%-33%; medium: 34%-66%; high: 67%-99%) for 896 observations (56 lesions by the 16 radiologists) in the two size subgroups and three patterns.
  
  
  RESULTS
  The number of recommendations changed by radiologists by use of CAD was 163 (18%) among all 896 observations. Among these changed recommendations, the fraction showing a beneficial effect from CAD was 68% (111/163), and the fraction showing a beneficial effect regarding biopsy recommendations was 69% (48/70). With CAD, the radiologists' performance regarding biopsy recommendations was significantly improved for 43 lung cancers (31 changed to biopsy versus 12 changed away from biopsy; P = .003) and was also improved for 27 benign lesions (10 changed to biopsy versus 17 changed away from biopsy; P = .18). Most of the cancers with improved recommendations were solid lesions or mixed GGO and relatively large.
  
  
  CONCLUSIONS
  CAD has the potential to improve the appropriateness of radiologists' recommendations for small malignant and benign lesions on CT scans.
authors.affiliation: Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, Chicago, IL, USA. feng@uchicago.edu
authors.forename: Feng
authors.initials: F
authors.lastname: Li
authors.forename: Qiang
authors.initials: Q
authors.lastname: Li
authors.forename: Roger
authors.initials: R
authors.lastname: Engelmann
authors.forename: Masahito
authors.initials: M
authors.lastname: Aoyama
authors.forename: Shusuke
authors.initials: S
authors.lastname: Sone
authors.forename: Heber
authors.initials: H
authors.lastname: MacMahon
authors.forename: Kunio
authors.initials: K
authors.lastname: Doi
mesh_terms: D000368:Aged; D002983:Clinical Competence; D003937:Diagnosis, Differential; D003951:Diagnostic Errors / Q000517:prevention & control; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011857:Radiographic Image Interpretation, Computer-Assisted; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed