Computer-aided diagnosis of pulmonary nodules: results of a large-scale observer test.

PURPOSE To determine the effect of computer-aided diagnosis (CAD) on the accuracy of pulmonary nodule detection. MATERIALS AND METHODS Twenty abnormal chest radiographs, each with a single nodule, and 20 normal radiographs were digitized with a laser scanner. These images were analyzed by using a computer program that indicates areas that may represent pulmonary nodules. The radiographs were displayed on computer workstations in randomized order, and an observer test was performed. One hundred forty-six observers participated, including 23 chest radiologists, 54 other radiologists, 27 radiology residents, and 42 nonradiologists. Cases were interpreted first without and then with the use of CAD. The observers' responses were recorded on a continuous confidence rating scale. Detection accuracy both with and without CAD was evaluated with receiver operating characteristic analysis. RESULTS The detection accuracy was significantly higher for all categories of observers when CAD was used (chest radiologists, P = 8 x 10(-6); other radiologists, P = 2 x 10(-16); radiology residents, P = 6 x 10(-7); and nonradiologists, P = 8 x 10(-9)). CONCLUSION CAD has the potential to improve diagnostic accuracy in the detection of lung nodules on digital radiographs.

[1]  C. Metz,et al.  Visual detection and localization of radiographic images. , 1975, Radiology.

[2]  H L Kundel,et al.  Visual scanning, pattern recognition and decision-making in pulmonary nodule detection. , 1978, Investigative radiology.

[3]  C. Metz Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[4]  C. Metz ROC Methodology in Radiologic Imaging , 1986, Investigative radiology.

[5]  J. Hanley Receiver operating characteristic (ROC) methodology: the state of the art. , 1989, Critical reviews in diagnostic imaging.

[6]  J. Austin,et al.  Missed bronchogenic carcinoma: radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect. , 1992, Radiology.

[7]  M. Melamed,et al.  The effect of surgical treatment on survival from early lung cancer. Implications for screening. , 1992, Chest.

[8]  K. Sugimachi,et al.  Early squamous lung cancer and longer survival rates. , 1993, Respiration; international review of thoracic diseases.

[9]  K. Doi,et al.  Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs. , 1996, Radiology.

[10]  R. Swensson Unified measurement of observer performance in detecting and localizing target objects on images. , 1996, Medical physics.

[11]  M. Giger,et al.  Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. , 1997, Medical physics.

[12]  C E Metz,et al.  The "proper" binormal model: parametric receiver operating characteristic curve estimation with degenerate data. , 1997, Academic radiology.

[13]  W Döhring,et al.  Subtle pulmonary abnormalities: detection on monitors with varying spatial resolutions and maximum luminance levels compared with detection on storage phosphor radiographic hard copies. , 1998, Radiology.

[14]  C. Metz,et al.  "Proper" Binormal ROC Curves: Theory and Maximum-Likelihood Estimation. , 1999, Journal of mathematical psychology.