Double reading improves detection of small lung tumors in chest radiographs: can a computer aided detection system replace the second reader?

Purpose: To investigate if a computer aided detection (CAD) system could replace a second human reader in a double reading process. Methods: We selected 300 posteroanterior and lateral digital chest radiographs(CXR), including 111 with a solitary CT proven pulmonary nodule with an average diameter of 16mm. Twelve radiologists read the CXRs having bone suppressed images available. Readers marked and scored suspicious regions on a continuous scale from 0 to 100. All images were also processed by a CAD system (ClearRead+Detect 5.2, Riverain Technologies) that also provided a score between 0 and 100 for each suspicious location it identified. Location based ROC analysis was used to measure nodule localization performance. Mean sensitivity in a false positive fraction range between 0 and 0.2 was used to compare reader performance. Double reading was evaluated by combining the findings of two readers: scores of findings at the same location were averaged while findings that were not identified by the second observer were averaged with 0. CAD results were treated similar as every observer for simulated double reading. A paired t-test was used to calculate differences. Results: The mean sensitivity was 64.0% for single reading (range 45.5%-78.2%). Combining the readings of two observers improved lung nodule detection on average to 73.1% (range 58.3%-83.8%; p=0.001). Performance with CAD as the second reader increased to 67.8% (range 58.1%-81.1%; p=0.02). Conclusion: Use of CAD as the second reader significantly improves detection of lung nodules, although it is not yet as good as double reading by two human readers.