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Jimenez-Juan L, Mehrez H, Dey C, Homampour S, Salazar-Ferrer P, Granton JT, Lee TY, Paul N. Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT. Sci Rep 2021; 11:483. [PMID: 33436837 PMCID: PMC7804280 DOI: 10.1038/s41598-020-80177-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 12/14/2020] [Indexed: 11/09/2022] Open
Abstract
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.
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Affiliation(s)
- Laura Jimenez-Juan
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.,Department of Medical Imaging, Sunnybrook Health Science Centre, Toronto, ON, Canada
| | - Hatem Mehrez
- Canon Medical Systems Canada, Markham, ON, Canada
| | - Chris Dey
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.,Department of Medical Imaging, Sunnybrook Health Science Centre, Toronto, ON, Canada
| | - Shabnam Homampour
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.,Joint Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada
| | | | - John T Granton
- Division of Respirology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Ting-Yim Lee
- Imaging Division, Lawson Health Research Institute, Imaging Research Laboratories, Research Institute, London, ON, Canada
| | - Narinder Paul
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada. .,Joint Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada. .,Department of Medical Imaging, London Health Sciences Centre, St Joseph's Hospital, Western University, London, ON, Canada.
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