TY - JOUR
AR - RDI-2020-2-105
TI - Sensitivity of Computer-Aided Detection (CAD) Device for Lung Nodule Detection on Chest Radiography: A Real-Life Application
AU - Ammar, Chaudhry
AU - William H. , Moore
JO - Radiology and Medical Diagnostic Imaging
PY - 2020
DA - Tue 09, Jun 2020
SN - 2613-7836
DO - http://dx.doi.org/10.31487/j.RDI.2020.02.05
UR - https://www.sciencerepository.org/sensitivity-of-computer-aided-detection-cad-device-for-lung-nodule_RDI-2020-2-105 
KW - Lung cancer, computer vision, computer aided detection, artificial intelligence
AB - Purpose: The radiographic diagnosis of lung nodules is associated with low sensitivity and specificity.
Computer-aided detection (CAD) system has been shown to have higher accuracy in the detection of lung
nodules. The purpose of this study is to assess the effect on sensitivity and specificity when a CAD system
is used to review chest radiographs in real-time setting.
Methods: Sixty-three patients, including 24 controls, who had chest radiographs and CT within three
months were included in this study. Three radiologists were presented chest radiographs without CAD and
were asked to mark all lung nodules. Then the radiologists were allowed to see the CAD region-of-interest
(ROI) marks and were asked to agree or disagree with the marks. All marks were correlated with CT studies.
Results: The mean sensitivity of the three radiologists without CAD was 16.1%, which showed a
statistically significant improvement to 22.5% with CAD. The mean specificity of the three radiologists was
52.5% without CAD and decreased to 48.1% with CAD. There was no significant change in the positive
predictive value or negative predictive value.
Conclusion: The addition of a CAD system to chest radiography interpretation statistically improves the
detection of lung nodules without affecting its specificity. Thus suggesting CAD would improve overall
detection of lung nodules.