Stefano Diciotti1, Alessandro Nobis2, Stefano Ciulli2,3,4, Nicholas Landini2, Mario Mascalchi2, Nicola Sverzellati5, Bernardo Innocenti6. 1. Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521, Cesena, Italy. stefano.diciotti@unibo.it. 2. Department of Clinical and Experimental Biomedical Sciences, University of Florence, Florence, Italy. 3. School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. 4. Medical Physics Section, Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy. 5. Section of Radiology, Department of Surgical Sciences, University of Parma, Parma, Italy. 6. BEAMS Department, École polytechnique de Bruxelles, ULB - Université Libre de Bruxelles, Bruxelles, Belgium.
Abstract
PURPOSE: To develop an innovative finite element (FE) model of lung parenchyma which simulates pulmonary emphysema on CT imaging. The model is aimed to generate a set of digital phantoms of low-attenuation areas (LAA) images with different grades of emphysema severity. METHODS: Four individual parameter configurations simulating different grades of emphysema severity were utilized to generate 40 FE models using ten randomizations for each setting. We compared two measures of emphysema severity (relative area (RA) and the exponent D of the cumulative distribution function of LAA clusters size) between the simulated LAA images and those computed directly on the models output (considered as reference). RESULTS: The LAA images obtained from our model output can simulate CT-LAA images in subjects with different grades of emphysema severity. Both RA and D computed on simulated LAA images were underestimated as compared to those calculated on the models output, suggesting that measurements in CT imaging may not be accurate in the assessment of real emphysema extent. CONCLUSIONS: Our model is able to mimic the cluster size distribution of LAA on CT imaging of subjects with pulmonary emphysema. The model could be useful to generate standard test images and to design physical phantoms of LAA images for the assessment of the accuracy of indexes for the radiologic quantitation of emphysema.
PURPOSE: To develop an innovative finite element (FE) model of lung parenchyma which simulates pulmonary emphysema on CT imaging. The model is aimed to generate a set of digital phantoms of low-attenuation areas (LAA) images with different grades of emphysema severity. METHODS: Four individual parameter configurations simulating different grades of emphysema severity were utilized to generate 40 FE models using ten randomizations for each setting. We compared two measures of emphysema severity (relative area (RA) and the exponent D of the cumulative distribution function of LAA clusters size) between the simulated LAA images and those computed directly on the models output (considered as reference). RESULTS: The LAA images obtained from our model output can simulate CT-LAA images in subjects with different grades of emphysema severity. Both RA and D computed on simulated LAA images were underestimated as compared to those calculated on the models output, suggesting that measurements in CT imaging may not be accurate in the assessment of real emphysema extent. CONCLUSIONS: Our model is able to mimic the cluster size distribution of LAA on CT imaging of subjects with pulmonary emphysema. The model could be useful to generate standard test images and to design physical phantoms of LAA images for the assessment of the accuracy of indexes for the radiologic quantitation of emphysema.
Entities:
Keywords:
Computed tomography; Emphysema; Finite element model; Phantom
Authors: Francisco S A Cavalcante; Satoru Ito; Kelly Brewer; Hiroaki Sakai; Adriano M Alencar; Murilo P Almeida; José S Andrade; Arnab Majumdar; Edward P Ingenito; Béla Suki Journal: J Appl Physiol (1985) Date: 2004-09-24
Authors: Jason H T Bates; Gerald S Davis; Arnab Majumdar; Kelly J Butnor; Béla Suki Journal: Am J Respir Crit Care Med Date: 2007-06-15 Impact factor: 21.405