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.
RCT Entities:
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.
Authors: Leo P Lawler; Susan A Wood; Harpreet K Pannu; Elliot K Fishman; Harpreet S Pannu Journal: J Digit Imaging Date: 2003-12-15 Impact factor: 4.056
Authors: Feng Li; Roger Engelmann; Lorenzo L Pesce; Kunio Doi; Charles E Metz; Heber Macmahon Journal: Radiology Date: 2011-09-23 Impact factor: 11.105