OBJECTIVE: The primary objective of our study was to compare the effect of a chest radiography computer-aided detection (CAD) system on the follow-up recommendations of chest radiologists, general radiologists, and pulmonologists. MATERIALS AND METHODS: A chest radiography CAD system (RapidScreen 1.1) that has been approved by the U.S. Food and Drug Administration (FDA) and a second-generation version of the system (OnGuard 3.0) not yet approved by the FDA were applied to single frontal radiographs of 200 patients at high risk for lung cancer. One hundred patients had actionable nodules (mean size, 16.9 mm) and 100 patients did not. Six chest radiologists, six general radiologists, and six pulmonologists independently interpreted each image first without CAD and then with CAD during blinded reading sessions. The frequency with which readers correctly referred patients for follow-up tests was measured. Differential effects based on nodule size, shape, location, density, and subtlety were tested with multiplevariable logistic regression. RESULTS: For patients without actionable lesions, pulmonologists showed an increase in their recommendations for follow-up from 0.46 unaided to 0.52 with CAD (p = 0.001), whereas chest and general radiologists had much lower average rates and were not affected by CAD's false marks (0.26 without CAD vs 0.25 with RapidScreen 1.1 and 0.26 with OnGuard 3.0, p ≥ 0.734). CAD improved all readers' detection of moderately subtle lesions (p = 0.013) but did not significantly increase follow-up rates overall for patients with actionable nodules (0.63 unaided vs 0.63 with RapidScreen 1.1, p = 0.795; and 0.63 unaided vs 0.64 with OnGuard 3.0, p = 0.187). CONCLUSION: The effect of CAD on readers' clinical decisions varies depending on the training of the reader. CAD did not improve the performance of chest or general radiologists. Nonradiologists are particularly vulnerable to CAD's false-positive marks.
OBJECTIVE: The primary objective of our study was to compare the effect of a chest radiography computer-aided detection (CAD) system on the follow-up recommendations of chest radiologists, general radiologists, and pulmonologists. MATERIALS AND METHODS: A chest radiography CAD system (RapidScreen 1.1) that has been approved by the U.S. Food and Drug Administration (FDA) and a second-generation version of the system (OnGuard 3.0) not yet approved by the FDA were applied to single frontal radiographs of 200 patients at high risk for lung cancer. One hundred patients had actionable nodules (mean size, 16.9 mm) and 100 patients did not. Six chest radiologists, six general radiologists, and six pulmonologists independently interpreted each image first without CAD and then with CAD during blinded reading sessions. The frequency with which readers correctly referred patients for follow-up tests was measured. Differential effects based on nodule size, shape, location, density, and subtlety were tested with multiplevariable logistic regression. RESULTS: For patients without actionable lesions, pulmonologists showed an increase in their recommendations for follow-up from 0.46 unaided to 0.52 with CAD (p = 0.001), whereas chest and general radiologists had much lower average rates and were not affected by CAD's false marks (0.26 without CAD vs 0.25 with RapidScreen 1.1 and 0.26 with OnGuard 3.0, p ≥ 0.734). CAD improved all readers' detection of moderately subtle lesions (p = 0.013) but did not significantly increase follow-up rates overall for patients with actionable nodules (0.63 unaided vs 0.63 with RapidScreen 1.1, p = 0.795; and 0.63 unaided vs 0.64 with OnGuard 3.0, p = 0.187). CONCLUSION: The effect of CAD on readers' clinical decisions varies depending on the training of the reader. CAD did not improve the performance of chest or general radiologists. Nonradiologists are particularly vulnerable to CAD's false-positive marks.
Authors: S Schalekamp; B van Ginneken; Bgf Heggelman; M Imhof-Tas; I Somers; M Brink; M Spee; Cm Schaefer-Prokop; N Karssemeijer Journal: Br J Radiol Date: 2014-02-17 Impact factor: 3.039
Authors: Ronald D Novak; Nicholas J Novak; Robert Gilkeson; Bahar Mansoori; Gunhild E Aandal Journal: J Digit Imaging Date: 2013-08 Impact factor: 4.056
Authors: Peter J Mazzone; Nancy Obuchowski; Michael Phillips; Barbara Risius; Bana Bazerbashi; Moulay Meziane Journal: PLoS One Date: 2013-03-20 Impact factor: 3.240