Improved detection of pulmonary nodules on energy-subtracted chest radiographs with a commercial computer-aided diagnosis software: comparison with human observers

Abstract

Objective: To retrospectively analyze the performance of a commercial computer-aided diagnosis (CAD) software in the detection of pulmonary nodules in original and energy-subtracted (ES) chest radiographs.

Methods: Original and ES chest radiographs of 58 patients with 105 pulmonary nodules measuring 5-30 mm and images of 25 control subjects with no nodules were randomized. Five blinded readers evaluated firstly the original postero-anterior images alone and then together with the subtracted radiographs. In a second phase, original and ES images were analyzed by a commercial CAD program. CT was used as reference standard. CAD results were compared to the readers' findings. True-positive (TP) and false-positive (FP) findings with CAD on subtracted and non-subtracted images were compared.

Results: Depending on the reader's experience, CAD detected between 11 and 21 nodules missed by readers. Human observers found three to 16 lesions missed by the CAD software. CAD used with ES images produced significantly fewer FPs than with non-subtracted images: 1.75 and 2.14 FPs per image, respectively (p = 0.029). The difference for the TP nodules was not significant (40 nodules on ES images and 34 lesions in non-subtracted radiographs, p = 0.142).

Conclusion: CAD can improve lesion detection both on energy subtracted and non-subtracted chest images, especially for less experienced readers. The CAD program marked less FPs on energy-subtracted images than on original chest radiographs.