title: Assessing the use of digital radiography and a real-time interactive pulmonary nodule analysis system for large population lung cancer screening.
abstract: OBJECTIVE
  To assess the use of chest digital radiograph (DR) assisted with a real-time interactive pulmonary nodule analysis system in large population lung cancer screening.
  
  
  METHODS
  346 DR/CR patient studies with corresponding CT images were selected from 12,500 patients screened for lung cancer from year 2007 to 2009. Two expert chest radiologists established CT-confirmed Gold Standard of nodules on DR/CR images with consensus. These cases were read by eight other chest radiologists (participating radiologists) first without using a real-time interactive pulmonary nodule analysis system and then re-read using the system. Performances of participating radiologists and the computer system were analyzed.
  
  
  RESULTS
  The computer system achieved similar performance on DR and CR images, with a detection rate of 76% and an average FPs of 2.0 per image. Before and after using the computer-aided detection system, the nodule detection sensitivities of the participating radiologists were 62.3% and 77.3% respectively, and the A(z) values increased from 0.794 to 0.831. Statistical analysis demonstrated statically significant improvement for the participating radiologists after using the computer analysis system with a P-value 0.05.
  
  
  CONCLUSIONS
  The computer system could help radiologists identify more lesions, especially small ones that are more likely to be overlooked on chest DR/CR images, and could help reduce inter-observer diagnostic variations, while its FPs were easy to recognize and dismiss. It is suggested that DR/CR assisted by the real-time interactive pulmonary nodule analysis system may be an effective means to screen large populations for lung cancer.
authors.affiliation: The Department of Radiology, Beijing Friendship Hospital-Affiliated Capital Medical University, 95 YongAn Road, XuanWu District, Beijing 100050, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Xu
authors.forename: Daqing
authors.initials: D
authors.lastname: Ma
authors.forename: Wen
authors.initials: W
authors.lastname: He
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002681:China / Q000453:epidemiology; D003199:Computer Systems; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000517:prevention & control; D008297:Male; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015995:Prevalence; D011856:Radiographic Image Enhancement / Q000379:methods*; D013902:Radiography, Thoracic / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*; D014584:User-Computer Interface