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The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans
Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In th...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4643661/ https://www.ncbi.nlm.nih.gov/pubmed/26568983 http://dx.doi.org/10.18383/j.tom.2015.00148 |
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author | Boes, Jennifer L. Bule, Maria Hoff, Benjamin A. Chamberlain, Ryan Lynch, David A. Stojanovska, Jadranka Martinez, Fernando J. Han, Meilan K. Kazerooni, Ella A. Ross, Brian D. Galbán, Craig J. |
author_facet | Boes, Jennifer L. Bule, Maria Hoff, Benjamin A. Chamberlain, Ryan Lynch, David A. Stojanovska, Jadranka Martinez, Fernando J. Han, Meilan K. Kazerooni, Ella A. Ross, Brian D. Galbán, Craig J. |
author_sort | Boes, Jennifer L. |
collection | PubMed |
description | Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPDGene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. |
format | Online Article Text |
id | pubmed-4643661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Grapho Publications, LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-46436612015-11-13 The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans Boes, Jennifer L. Bule, Maria Hoff, Benjamin A. Chamberlain, Ryan Lynch, David A. Stojanovska, Jadranka Martinez, Fernando J. Han, Meilan K. Kazerooni, Ella A. Ross, Brian D. Galbán, Craig J. Tomography Research Article Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPDGene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. Grapho Publications, LLC 2015-09 /pmc/articles/PMC4643661/ /pubmed/26568983 http://dx.doi.org/10.18383/j.tom.2015.00148 Text en © 2015 The Authors. Published by Grapho Publications, LLC http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Boes, Jennifer L. Bule, Maria Hoff, Benjamin A. Chamberlain, Ryan Lynch, David A. Stojanovska, Jadranka Martinez, Fernando J. Han, Meilan K. Kazerooni, Ella A. Ross, Brian D. Galbán, Craig J. The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title | The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title_full | The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title_fullStr | The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title_full_unstemmed | The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title_short | The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans |
title_sort | impact of sources of variability on parametric response mapping of lung ct scans |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4643661/ https://www.ncbi.nlm.nih.gov/pubmed/26568983 http://dx.doi.org/10.18383/j.tom.2015.00148 |
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