Computer-aided recognition of emphysema on digital chest radiography.
BACKGROUND
Computed tomography (CT) is the benchmark for diagnosis emphysema, but is costly and imparts a substantial radiation burden to the patient.


OBJECTIVE
To develop a computer-aided procedure that allows recognition of emphysema on digital chest radiography by using simple descriptors of the lung shape. The procedure was tested against CT.


METHODS
Patients (N=225), who had undergone postero-anterior and lateral digital chest radiographs and CT for diagnostic purposes, were studied and divided in a derivation (N=118) and in a validation sample (N=107). CT images were scored for emphysema using the picture-grading method. Simple descriptors that measure the bending characteristics of the lung profile on chest radiography were automatically extracted from the derivation sample, and applied to train a neural network to assign a probability of emphysema between 0 and 1. The diagnostic performance of the procedure was described by the area under the receiver operating characteristic curve (AUC).


RESULTS
AUC was 0.985 (95% confidence interval, 0.965-0.998) in the derivation sample, and 0.975 (95% confidence interval, 0.936-0.998) in the validation sample. At a probability cutpoint of 0.55, the procedure yielded 92% sensitivity and 96% specificity in the derivation sample; 90% sensitivity and 97% specificity in the validation sample. False negatives on chest radiography had trace or mild emphysema on CT.


CONCLUSIONS
The computer-aided procedure is simple and inexpensive, and permits quick recognition of emphysema on digital chest radiographs.
Miniati
Massimo
M
Department of Medical and Surgical Critical Care, University of Florence, 50134 Florence, Italy. Massimo.Miniati@unifi.it
Coppini
Giuseppe
G
Monti
Simonetta
S
Bottai
Matteo
M
Paterni
Marco
M
Ferdeghini
Ezio Maria
EM
D000368:Aged; D019540:Area Under Curve; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D011656:Pulmonary Emphysema / Q000000981:diagnostic imaging*; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000379:methods