A Comparison of Computer-Aided Detection (CAD) Effectiveness in Pulmonary Nodule Identification Using Different Methods of Bone Suppression in Chest Radiographs |
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Authors: | Ronald D Novak Nicholas J Novak Robert Gilkeson Bahar Mansoori Gunhild E Aandal |
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Institution: | 1. Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, USA 2. Department of Radiology, University Hospitals of Cleveland—Case Medical Center, 11100 Euclid Avenue, BSH 5056, Cleveland, OH, 44106, USA 3. Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA
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Abstract: | This study aimed to compare the diagnostic effectiveness of computer-aided detection (CAD) software (OnGuard™ 5.2) in combination with hardware-based bone suppression (dual-energy subtraction radiography (DESR)), software-based bone suppression (SoftView™, version 2.4), and standard posteroanterior images with no bone suppression. A retrospective pilot study compared the diagnostic performance of two commercially available methods of bone suppression when used with commercially available CAD software. Chest images from 27 patients with computed tomography (CT) and pathology-proven malignant pulmonary nodules (8–34 mm) and 25 CT-negative patient controls were used for analysis. The Friedman, McNemar, and chi-square tests were used to compare diagnostic performance and the kappa statistic was used to evaluate method agreement. The average number of regions of interest and false-positives per image identified by CAD were not found to be significantly different regardless of the bone suppression methods evaluated. Similarly, the sensitivity, specificity, and test efficiency were not found to be significantly different. Agreement between the methods was between poor and excellent. The accuracy of CAD (OnGuard™, version 5.2) is not statistically different with either DESR or SoftView™ (version 2.4) bone suppression technology in digital chest images for pulmonary nodule identification. Low values for sensitivity (<80 %) and specificity (<50 %) may limit their utility for clinical radiology. |
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Keywords: | Computer-aided detection Pulmonary nodule Digital chest radiography Image analysis method Dual-energy subtraction |
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