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Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT
Quantitative measurement of lung perfusion is a promising tool to evaluate lung pathophysiology as well as to assess disease severity and monitor treatment. However, this novel technique has not been adopted clinically due to various technical and physiological challenges; and it is still in the ear...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804280/ https://www.ncbi.nlm.nih.gov/pubmed/33436837 http://dx.doi.org/10.1038/s41598-020-80177-5 |
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author | Jimenez-Juan, Laura Mehrez, Hatem Dey, Chris Homampour, Shabnam Salazar-Ferrer, Pascal Granton, John T. Lee, Ting-Yim Paul, Narinder |
author_facet | Jimenez-Juan, Laura Mehrez, Hatem Dey, Chris Homampour, Shabnam Salazar-Ferrer, Pascal Granton, John T. Lee, Ting-Yim Paul, Narinder |
author_sort | Jimenez-Juan, Laura |
collection | PubMed |
description | Quantitative measurement of lung perfusion is a promising tool to evaluate lung pathophysiology as well as to assess disease severity and monitor treatment. However, this novel technique has not been adopted clinically due to various technical and physiological challenges; and it is still in the early developmental phase where the correlation between lung pathophysiology and perfusion maps is being explored. The purpose of this research work is to quantify the impact of pulmonary artery occlusion on lung perfusion indices using lung dynamic perfusion CT (DPCT). We performed Lung DPCT in ten anesthetized, mechanically ventilated juvenile pigs (18.6–20.2 kg) with a range of reversible pulmonary artery occlusions (0%, 40–59%, 60–79%, 80–99%, and 100%) created with a balloon catheter. For each arterial occlusion, DPCT data was analyzed using first-pass kinetics to derive blood flow (BF), blood volume (BV) and mean transit time (MTT) perfusion maps. Two radiologists qualitatively assessed perfusion maps for the presence or absence of perfusion defects. Perfusion maps were also analyzed quantitatively using a linear segmented mixed model to determine the thresholds of arterial occlusion associated with perfusion derangement. Inter-observer agreement was assessed using Kappa statistics. Correlation between arterial occlusion and perfusion indices was evaluated using the Spearman-rank correlation coefficient. Our results determined that perfusion defects were detected qualitatively in BF, BV and MTT perfusion maps for occlusions larger than 55%, 80% and 55% respectively. Inter-observer agreement was very good with Kappa scores > 0.92. Quantitative analysis of the perfusion maps determined the arterial occlusion threshold for perfusion defects was 50%, 76% and 44% for BF, BV and MTT respectively. Spearman-rank correlation coefficients between arterial occlusion and normalized perfusion values were strong (− 0.92, − 0.72, and 0.78 for BF, BV and MTT, respectively) and were statically significant (p < 0.01). These findings demonstrate that lung DPCT enables quantification and stratification of pulmonary artery occlusion into three categories: mild, moderate and severe. Severe (occlusion ≥ 80%) alters all perfusion indices; mild (occlusion < 55%) has no detectable effect. Moderate (occlusion 55–80%) impacts BF and MTT but BV is preserved. |
format | Online Article Text |
id | pubmed-7804280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78042802021-01-13 Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT Jimenez-Juan, Laura Mehrez, Hatem Dey, Chris Homampour, Shabnam Salazar-Ferrer, Pascal Granton, John T. Lee, Ting-Yim Paul, Narinder Sci Rep Article Quantitative measurement of lung perfusion is a promising tool to evaluate lung pathophysiology as well as to assess disease severity and monitor treatment. However, this novel technique has not been adopted clinically due to various technical and physiological challenges; and it is still in the early developmental phase where the correlation between lung pathophysiology and perfusion maps is being explored. The purpose of this research work is to quantify the impact of pulmonary artery occlusion on lung perfusion indices using lung dynamic perfusion CT (DPCT). We performed Lung DPCT in ten anesthetized, mechanically ventilated juvenile pigs (18.6–20.2 kg) with a range of reversible pulmonary artery occlusions (0%, 40–59%, 60–79%, 80–99%, and 100%) created with a balloon catheter. For each arterial occlusion, DPCT data was analyzed using first-pass kinetics to derive blood flow (BF), blood volume (BV) and mean transit time (MTT) perfusion maps. Two radiologists qualitatively assessed perfusion maps for the presence or absence of perfusion defects. Perfusion maps were also analyzed quantitatively using a linear segmented mixed model to determine the thresholds of arterial occlusion associated with perfusion derangement. Inter-observer agreement was assessed using Kappa statistics. Correlation between arterial occlusion and perfusion indices was evaluated using the Spearman-rank correlation coefficient. Our results determined that perfusion defects were detected qualitatively in BF, BV and MTT perfusion maps for occlusions larger than 55%, 80% and 55% respectively. Inter-observer agreement was very good with Kappa scores > 0.92. Quantitative analysis of the perfusion maps determined the arterial occlusion threshold for perfusion defects was 50%, 76% and 44% for BF, BV and MTT respectively. Spearman-rank correlation coefficients between arterial occlusion and normalized perfusion values were strong (− 0.92, − 0.72, and 0.78 for BF, BV and MTT, respectively) and were statically significant (p < 0.01). These findings demonstrate that lung DPCT enables quantification and stratification of pulmonary artery occlusion into three categories: mild, moderate and severe. Severe (occlusion ≥ 80%) alters all perfusion indices; mild (occlusion < 55%) has no detectable effect. Moderate (occlusion 55–80%) impacts BF and MTT but BV is preserved. Nature Publishing Group UK 2021-01-12 /pmc/articles/PMC7804280/ /pubmed/33436837 http://dx.doi.org/10.1038/s41598-020-80177-5 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jimenez-Juan, Laura Mehrez, Hatem Dey, Chris Homampour, Shabnam Salazar-Ferrer, Pascal Granton, John T. Lee, Ting-Yim Paul, Narinder Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title | Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title_full | Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title_fullStr | Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title_full_unstemmed | Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title_short | Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT |
title_sort | quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion ct |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804280/ https://www.ncbi.nlm.nih.gov/pubmed/33436837 http://dx.doi.org/10.1038/s41598-020-80177-5 |
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