Computer-aided diagnosis of pulmonary nodules: results of a large-scale observer test.
OBJECTIVE
To determine the effect of computer-aided diagnosis (CAD) on the accuracy of pulmonary nodule detection.


METHODS
Twenty abnormal chest radiographs, each with a single nodule, and 20 normal radiographs were digitized with a laser scanner. These images were analyzed by using a computer program that indicates areas that may represent pulmonary nodules. The radiographs were displayed on computer workstations in randomized order, and an observer test was performed. One hundred forty-six observers participated, including 23 chest radiologists, 54 other radiologists, 27 radiology residents, and 42 nonradiologists. Cases were interpreted first without and then with the use of CAD. The observers' responses were recorded on a continuous confidence rating scale. Detection accuracy both with and without CAD was evaluated with receiver operating characteristic analysis.


RESULTS
The detection accuracy was significantly higher for all categories of observers when CAD was used (chest radiologists, P = 8 x 10(-6); other radiologists, P = 2 x 10(-16); radiology residents, P = 6 x 10(-7); and nonradiologists, P = 8 x 10(-9)).


CONCLUSIONS
CAD has the potential to improve diagnostic accuracy in the detection of lung nodules on digital radiographs.
MacMahon
H
H
Department of Radiology, University of Chicago, IL 60637, USA. macm@midway.uchicago.edu
Engelmann
R
R
Behlen
F M
FM
Hoffmann
K R
KR
Ishida
T
T
Roe
C
C
Metz
C E
CE
Doi
K
K
D003936:Diagnosis, Computer-Assisted; D006801:Humans; D015588:Observer Variation; D012372:ROC Curve; D011856:Radiographic Image Enhancement; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*