Home Probing Changes in Lung Physiology in COPD Using CT, Perfusion MRI, and Hyperpolarized Xenon-129 MRI
Post
Cancel

Probing Changes in Lung Physiology in COPD Using CT, Perfusion MRI, and Hyperpolarized Xenon-129 MRI

Posted Feb 28, 2019 Updated Apr 10, 2023
By Kun Qing PhD , Nicholas J. Tustison DSc , John P. Mugler PhD , Jaime F. Mata PhD , Zixuan Lin BS , Li Zhao PhD , Da Wang PhD , Xue Feng PhD , Ji Young Shin MD , Sean J. Callahan MD , Michael P. Bergman MD , Kai Ruppert PhD , Talissa A. Altes MD , Joanne M. Cassani , Y. Michael Shim MD BS
13 min read

Rationale and Objectives

Chronic obstructive pulmonary disease (COPD) is highly heterogeneous and not well understood. Hyperpolarized xenon-129 (Xe129) magnetic resonance imaging (MRI) provides a unique way to assess important lung functions such as gas uptake. In this pilot study, we exploited multiple imaging modalities, including computed tomography (CT), gadolinium-enhanced perfusion MRI, and Xe129 MRI, to perform a detailed investigation of changes in lung morphology and functions in COPD. Utility and strengths of Xe129 MRI in assessing COPD were also evaluated against the other imaging modalities.

Materials and Methods

Four COPD patients and four age-matched normal subjects participated in this study. Lung tissue density measured by CT, perfusion measures from gadolinium-enhanced MRI, and ventilation and gas uptake measures from Xe129 MRI were calculated for individual lung lobes to assess regional changes in lung morphology and function, and to investigate correlations among the different imaging modalities.

Results

No significant differences were found for all measures among the five lobes in either the COPD or age-matched normal group. Strong correlations ( R > 0.5 or < −0.5, p < 0.001) were found between ventilation and perfusion measures. Also gas uptake by blood as measured by Xe129 MRI showed strong correlations with CT tissue density and ventilation measures ( R > 0.5 or < −0.5, p < 0.001) and moderate to strong correlations with perfusion measures ( R > 0.4 or < −0.5, p < 0.01). Four distinctive patterns of functional abnormalities were found in patients with COPD.

Conclusion

Xe129 MRI has high potential to uniquely identify multiple changes in lung physiology in COPD using a single breath-hold acquisition.

Introduction

Chronic obstructive pulmonary disease (COPD) is a leading cause of death and disability around the world. Clinical diagnosis and prognosis of COPD are still primarily based on irreversible airflow limitation measured by spirometry. However, multiple studies reported heterogeneous phenotypes of COPD that are far more complicated than being simply defined by irreversible airflow limitation ( ). Loss of lung function and abnormalities of gas exchange develop early ( ) and increase in prevalence as the severity of COPD increases ( ). Chronic hypoxemia was reported to be closely related to decline in the patient’s quality of life, reduced exercise tolerance, and greater risk of death ( ).

There are numerous unanswered questions about the mechanisms of hypoxemia in COPD. Whether hypoxemia is merely caused by ventilation-perfusion (V/Q) mismatch or diffusion impairment is unclear ( ). Conventional imaging techniques, such as computed tomography (CT) and nuclear medicine scans, have limitations in the assessment of COPD. For example, chest CT provides detailed information about changes in lung morphometry, such as emphysema and bronchiectasis ( ), but limited information about lung function. Dual energy chest CT scan can provide iodine distribution maps, which can be used as a surrogate for pulmonary perfusion ( ). Nuclear medicine V/Q scan quantifies ventilation and perfusion ( ), but with limited spatial and temporal resolution. In addition, pulmonary function testing (PFT) provides whole lung measurements of lung function, but lacks regional localization of abnormalities. Therefore, reliable, noninvasive imaging techniques that can offer detailed assessment and accurate quantification of regional lung function will not only promote the understanding of the pathophysiology of COPD, but will also provide directions for treatment and valuable information about prognosis.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Materials and Methods

Human Subjects

Get Radiology Tree app to read full this article<

Image Acquisitions

Computed Tomography

Get Radiology Tree app to read full this article<

Gd-Enhanced Perfusion MRI

Get Radiology Tree app to read full this article<

Combined Hyperpolarized Xe129 and Proton MRI

Get Radiology Tree app to read full this article<

Imaging Postprocessing

Computed Tomography

Get Radiology Tree app to read full this article<

Gd-Enhanced Perfusion MRI

Get Radiology Tree app to read full this article<

Combined Hyperpolarized Xe129 and Proton MRI

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Data Analysis

Get Radiology Tree app to read full this article<

Institutional Review Board

Get Radiology Tree app to read full this article<

Results

Subject Features

Get Radiology Tree app to read full this article<

Table 1

Subject demographics and PFT results

Sex Age FEV 1 /FVC FEV 1 %Pred DLCO %Pred DLCO/Va %Pred 6MW_H1_ F52 \* 91111 91 93587H2 F 6174 106 8277 487H3 F 60 839393114442H4 F62 \* 79 9977 78 450C1 F66 59 62 60 75 424C2 F5669 638596 425C3 M 64 5780 77 76495C4 M 5824254449225

Bold + underline means lower limit for measurement in each group.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Global and Regional Differences in Lung Function

Global Evaluation

Get Radiology Tree app to read full this article<

Table 2

Whole-lung average measurements obtained from imaging acquisitions

CT Gd-MRI HP Xe129 MRI Perc15 PBV PBF MTT %V D Tissue/Gas RBC/Gas RBC/Tissue H1 −881 6.6 77 8.9 21 0.950.340.35 H2 − 889 \* 11.4135 8.4140.79 0.28 0.27 H3 − 833 \* 8.7 1188.3 31 0.92 0.280.20 H4 −8495.9689.6361.060.26 0.21 C1 −8978.21197.3260.89 0.230.20 C2 − 884 6.7 69 10.1 38 0.850.27 0.18 C3 −905 7.8 80 9.1 34 0.36 0.21 0.18 C4 − 9413.63011.9620.250.150.11

Bold + underline means lower limit for measurement in each group.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Lobar Evaluation

Get Radiology Tree app to read full this article<

Table 3

Comparison of lobar mean values from AMN and COPD groups a

CT Gd-MRI HP Xe129 MRI Perc15 PBV PBF MTT %V D Tissue/gas RBC/gas RBC/tissue AMN 1 b − 843 \* 9.11089.0 29 1.06 0.29 0.26 2 −876 8.0 96 9.0 21 0.92 0.25 0.24 3 −848 7.9 1008.4 26 1.01 0.29 0.28 4 − 890 \* 6.679 8.9 24 0.74 0.23 0.28 5 −872 8.2 100 8.8 28 0.82 0.25 0.25 P_Lob b c 0.12 0.61 0.67 0.81 0.90 0.18 0.42 0.95 COPD 1 −892 6.7 75 9.4350.650.180.18 2 − 924 6.4 74 9.844 0.60 0.16 0.16 3 − 8877.1 759.9 40 0.59 0.160.15 4 −9195.9689.4 36 0.550.15 0.18 5 −915 6.577 9.6 410.53 0.15 0.17 P_Lob 0.24 0.99 0.99 0.98 0.99 0.95 0.86 0.87 P_Grp d ≤ 0.001 0.190.047 0.070.006≤ 0.001≤ 0.001≤ 0.001

Bold + underline means lower limit for measurement in each group.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Figure 1, Representative lobar segmentation of Xe129 MRI, Gd-enhanced perfusion MRI, and CT images. Left column : top row: ventilation image (“Gas”) overlaid on proton image acquired in the same breath-hold as Xe129 images; middle row: generated tissue-to-gas ratio map on top of proton image; bottom row: lobar segmentation for proton image acquired with Xe129 MRI acquisition. Middle column : top row: Gd-enhanced perfusion MRI image of the lung; middle row: generated pulmonary blood volume map (PBV) in the lung region; bottom row: lobar segmentation for Gd-enhanced perfusion MRI image. Right column : top row: high-resolution CT image of the lung with regions lower than −950 HU marked by red dots; bottom row: lobar segmentation for CT was done based on the fissure detected. Images showed a representative slice of the 3-D Xe129, Gd-enhanced perfusion MRI and HRCT acquisitions from approximately the same position of the lung. CT, computed tomography; HRCT, high-resolution computed tomography; HU, hounsfield unit; MRI, magnetic resonance imaging; Xe129, Xenon-129. (Color version of figure is available online.)

Get Radiology Tree app to read full this article<

Correlations and Differences Among Different Imaging Measurements

Get Radiology Tree app to read full this article<

Table 4

Correlation between different imaging measurements

GD-MRI XE129 MRI PBV PBF MTT %V D Tissue /Gas RBC/Gas RBC/Tissue CT 0.38(R) \* 0.42 − 0.36 − 0.33 0.740.62 0.26 PERC15 0.016(P) \* 0.007 0.022 0.04 ≤ 0.001≤ 0.001 0.10 PBV – – – − 0.59 0.37 0.42 0.35 ≤ 0.001 0.018 0.007 0.028 PBF – – – − 0.62 0.48 0.49 0.38 ≤ 0.001 0.002 0.002 0.015 MTT – – –0.59 −0.45 −0.52 − 0.48 ≤ 0.001 0.004 ≤ 0.001 0.002 %V D – − 0.51 − 0.64 − 0.67≤ 0.001≤ 0.001≤ 0.001

Significant correlations with P < 0.05 were highlighted in bold and underline.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Patterns of Functional Abnormalities

Get Radiology Tree app to read full this article<

Figure 2, Representative CT image, PBV, and Xe129 tissue-to-gas and RBC-to-gas ratio maps from subject C4 and C2. Alterations of lung function exhibited different patterns in the lung, as shown in Areas 1–4 in the figure. The RBC-to-gas ratio measured by Xe129 MRI reflecting overall gas exchange to the blood was found to be low in concordance with low tissue density measured by CT (Area 1), low perfusion measured by perfusion MRI (Area 3), or the combination of both (Area 2). CT, computed tomography; MRI, magnetic resonance imaging; PBV, pulmonary blood volume; RBC, red blood cells; Xe129, Xenon-129. (Color version of figure is available online.)

Figure 3, Representative CT images, PBV maps, and Xe129 tissue-to-gas and RBC-to-gas ratio maps from subject C1 and C2 showed that Xe129 MRI could uniquely detect low gas exchange to blood by either low gas ventilation (Area 4) or potentially impaired gas exchange from lung tissue to the blood (Area 5). This information was not accessible by perfusion MRI or CT. CT, computed tomography; PBV, pulmonary blood volume; Xe129, Xenon-129; RBC, red blood cells; MRI, magnetic resonance imaging. (Color version of figure is available online.)

Get Radiology Tree app to read full this article<

Discussion

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Acknowledgment

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

References

  • 1. Kim V, Han MK, Vance GB, et. al.: The chronic bronchitic phenotype of COPD: an analysis of the COPDGene study. Chest 2011; 140: pp. 626-633.

  • 2. Vestbo J, Agusti A, Wouters EF, et. al.: Should we view chronic obstructive pulmonary disease differently after ECLIPSE? A clinical perspective from the study team. Am J Resp Crit Care Med 2014; 189: pp. 1022-1030.

  • 3. Cosio MG, Guerassimov A: Chronic obstructive pulmonary disease. Inflammation of small airways and lung parenchyma. Am J Respiratory Crit Care Med 1999; 160: pp. S21-S25.

  • 4. Rodriguez-Roisin R, Drakulovic M, Rodriguez DA, et. al.: Ventilation-perfusion imbalance and chronic obstructive pulmonary disease staging severity. J Appl Physiol 2009; 106: pp. 1902-1908.

  • 5. Rabe KF, Hurd S, Anzueto A, et. al.: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Resp Crit Care Med 2007; 176: pp. 532-555.

  • 6. Kent BD, Mitchell PD, McNicholas WT: Hypoxemia in patients with COPD: cause, effects, and disease progression. Int J Chronic Obstr Pulm Dis 2011; 6: pp. 199-208.

  • 7. Young IH, Bye PT: Gas exchange in disease: asthma, chronic obstructive pulmonary disease, cystic fibrosis, and interstitial lung disease. Compr Physiol 2011; 1: pp. 663-697.

  • 8. Sverzellati N, Molinari F, Pirronti T, et. al.: New insights on COPD imaging via CT and MRI. Int J Chronic Obstr Pulm Dis 2007; 2: pp. 301-312.

  • 9. Fornaro J, Leschka S, Hibbeln D, et. al.: Dual- and multi-energy CT: approach to functional imaging. Insights into imaging 2011; 2: pp. 149-159.

  • 10. Roach PJ, Schembri GP, Bailey DL: V/Q scanning using SPECT and SPECT/CT. J Nucl Med 2013; 54: pp. 1588-1596.

  • 11. Qing K, Ruppert K, Jiang Y, et. al.: Regional mapping of gas uptake by blood and tissue in the human lung using hyperpolarized xenon-129 MRI. J Magn Reson Imaging 2014; 39: pp. 346-359.

  • 12. Qing K, Mugler JP, Altes TA, et. al.: Assessment of lung function in asthma and COPD using hyperpolarized 129Xe chemical shift saturation recovery spectroscopy and dissolved-phase MRI. NMR Biomed 2014; 27: pp. 1490-1501.

  • 13. Kaushik SS, Robertson SH, Freeman MS, et. al.: Single-breath clinical imaging of hyperpolarized (129)Xe in the airspaces, barrier, and red blood cells using an interleaved 3D radial 1-point Dixon acquisition. Magn Reson Med 2016; 75: pp. 1434-1443.

  • 14. Dregely I, Mugler JP, Ruset IC, et. al.: Hyperpolarized Xenon-129 gas-exchange imaging of lung microstructure: first case studies in subjects with obstructive lung disease. J Magn Reson Imag 2011; 33: pp. 1052-1062.

  • 15. Kaushik SS, Freeman MS, Yoon SW, et. al.: Measuring diffusion limitation with a perfusion-limited gas–hyperpolarized 129Xe gas-transfer spectroscopy in patients with idiopathic pulmonary fibrosis. J Appl Physiol 2014; 117: pp. 577-585.

  • 16. Vestbo J, Hurd SS, Agusti AG, et. al.: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Resp Crit Care Med 2013; 187: pp. 347-365.

  • 17. Labaki WW, Martinez CH, Martinez FJ, et. al.: The role of chest computed tomography in the evaluation and management of the patient with COPD. Am J Resp Crit Care Med 2017; 196: pp. 1372-1379.

  • 18. Kim S, Jacob JS, Kim DC, et. al.: Time-resolved dynamic contrast-enhanced MR urography for the evaluation of ureteral peristalsis: initial experience. J Magn Reson Imaging 2008; 28: pp. 1293-1298.

  • 19. Wild JM, Ajraoui S, Deppe MH, et. al.: Synchronous acquisition of hyperpolarised 3He and 1H MR images of the lungs—maximising mutual anatomical and functional information. NMR Biomed 2011; 24: pp. 130-134.

  • 20. Qing K, Altes TA, Tustison NJ, et. al.: Acquisition of spatially-registered helium-3 and proton 3D image sets of the lung in less than 10 seconds using compressed sensing (abstract). Proc Intl Soc Mag Reson Med 2011; 19: pp. 1349.

  • 21. Tustison NJ, Qing K, Wang C, et. al.: Atlas-based estimation of lung and lobar anatomy in proton MRI. Magn Reson Med 2016; 76: pp. 315-320.

  • 22. Dijkstra AE, Postma DS, ten Hacken N, et. al.: Low-dose CT measurements of airway dimensions and emphysema associated with airflow limitation in heavy smokers: a cross sectional study. Resp Res 2013; 14: pp. 11.

  • 23. Mets OM, van Hulst RA, Jacobs C, et. al.: Normal range of emphysema and air trapping on CT in young men. AJR Am J Roentgenol 2012; 199: pp. 336-340.

  • 24. Mohamed Hoesein FA, de Hoop B, Zanen P, et. al.: CT-quantified emphysema in male heavy smokers: association with lung function decline. Thorax 2011; 66: pp. 782-787.

  • 25. Ohno Y, Hatabu H, Murase K, et. al.: Quantitative assessment of regional pulmonary perfusion in the entire lung using three-dimensional ultrafast dynamic contrast-enhanced magnetic resonance imaging: preliminary experience in 40 subjects. J Magn Reson Imaging 2004; 20: pp. 353-365.

  • 26. Meier P, Zierler KL: On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol 1954; 6: pp. 731-744.

  • 27. Zierler K: Indicator dilution methods for measuring blood flow, volume, and other properties of biological systems: a brief history and memoir. Annals Biomed Eng 2000; 28: pp. 836-848.

  • 28. Tustison NJ, Avants BB, Flors L, et. al.: Ventilation-based segmentation of the lungs using hyperpolarized (3)He MRI. J Magn Reson Imaging 2011; 34: pp. 831-841.

  • 29. Qing K, Altes TA, Tustison NJ, et. al.: Rapid acquisition of helium-3 and proton three-dimensional image sets of the human lung in a single breath-hold using compressed sensing. Magn Reson Med 2015; 74: pp. 1110-1115.

  • 30. Rahaghi FN, van Beek EJ, Washko GR: Cardiopulmonary coupling in chronic obstructive pulmonary disease: the role of imaging. J Thorac Imaging 2014; 29: pp. 80-91.

  • 31. Stenmark KR, Fagan KA, Frid MG: Hypoxia-induced pulmonary vascular remodeling: cellular and molecular mechanisms. Circ Res 2006; 99: pp. 675-691.

  • 32. Ruppert K, Qing K, Altes TA, et. al.: Septal wall thickness changes in COPD assessed by CSSR MR spectroscopy. Am J Resp Crit Care Med 2014; 189: pp. A5419. D19 MR and MRS: Imaging Regional Lung Function

  • 33. Cleveland ZI, Cofer GP, Metz G, et. al.: Hyperpolarized Xe MR imaging of alveolar gas uptake in humans. PloS One 2010; 5: pp. e12192.

  • 34. Mugler JP, Driehuys B, Brookeman JR, et. al.: MR imaging and spectroscopy using hyperpolarized 129Xe gas: preliminary human results. Magn Reson Med 1997; 37: pp. 809-815.

Academic Radiology, Volume 26, Issue 3
Journals General Radiology
This post is licensed under CC BY 4.0 by the author.
Recently Updated
Contents