PUMA
Istituto di Fisiologia Clinica     
Miniati M., Coppini G., Monti S., Bottai M., Paterni M., Ferdeghini E. M. Computer-aided recognition of emphysema on digital chest radiography. In: European Journal of Radiology, vol. 80 pp. e169 - e175. elsevier, 2011.
 
 
Abstract
(English)
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.
DOI: 10.1016/j.ejrad.2010.08.021
Subject emphysema, diagnosis, chest computed tomography, digital radiography, neural networks


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional