Literature DB >> 26737750

Development and analysis of a finite element model to simulate pulmonary emphysema in CT imaging.

Stefano Diciotti, Alessandro Nobis, Stefano Ciulli, Nicholas Landini, Mario Mascalchi, Nicola Sverzellati, Bernardo Innocenti.   

Abstract

In CT imaging, pulmonary emphysema appears as lung regions with Low-Attenuation Areas (LAA). In this study we propose a finite element (FE) model of lung parenchyma, based on a 2-D grid of beam elements, which simulates pulmonary emphysema related to smoking in CT imaging. Simulated LAA images were generated through space sampling of the model output. We employed two measurements of emphysema extent: Relative Area (RA) and the exponent D of the cumulative distribution function of LAA clusters size. The model has been used to compare RA and D computed on the simulated LAA images with those computed on the models output. Different mesh element sizes and various model parameters, simulating different physiological/pathological conditions, have been considered and analyzed. A proper mesh element size has been determined as the best trade-off between reliable results and reasonable computational cost. Both RA and D computed on simulated LAA images were underestimated with respect to those calculated on the models output. Such underestimations were larger for RA (≈ -44 ÷ -26%) as compared to those for D (≈ -16 ÷ -2%). Our FE model could be useful to generate standard test images and to design realistic physical phantoms of LAA images for the assessment of the accuracy of descriptors for quantifying emphysema in CT imaging.

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Year:  2015        PMID: 26737750     DOI: 10.1109/EMBC.2015.7319850

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  Development of digital phantoms based on a finite element model to simulate low-attenuation areas in CT imaging for pulmonary emphysema quantification.

Authors:  Stefano Diciotti; Alessandro Nobis; Stefano Ciulli; Nicholas Landini; Mario Mascalchi; Nicola Sverzellati; Bernardo Innocenti
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-11-12       Impact factor: 2.924

  1 in total

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