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Using Hyperpolarized Xenon-129 MRI to Quantify Early-Stage Lung Disease in Smokers

Posted Feb 28, 2019 Updated Apr 10, 2023
By Kai Ruppert PhD , Kun Qing PhD , James T. Patrie MS , Talissa A. Altes MD , John P. Mugler PhD
17 min read

Rationale and Objectives

Hyperpolarized xenon-129 magnetic resonance (MR) provides sensitive tools that may detect early stages of lung disease in smokers before it has progressed to chronic obstructive pulmonary disease (COPD) apparent to conventional spirometric measures. We hypothesized that the functional alveolar wall thickness as assessed by hyperpolarized xenon-129 MR spectroscopy would be elevated in clinically healthy smokers before xenon MR diffusion measurements would indicate emphysematous tissue destruction.

Materials and Methods

Using hyperpolarized xenon-129 MR we measured the functional septal wall thickness and apparent diffusion coefficient of the gas phase in 16 subjects with smoking-related COPD, 9 clinically healthy current or former smokers, and 10 healthy never smokers. All subjects were age-matched and characterized by conventional pulmonary function tests. A total of 11 data sets from younger healthy never smokers were added to determine the age dependence of the septal wall thickness measurements.

Results

In healthy never smokers the septal wall thickness increased by 0.04 μm per year of age. The healthy smoker cohort exhibited normal pulmonary function test measures that did not significantly differ from the never-smoker cohort. The age-corrected septal wall thickness correlated well with diffusion capacity for carbon monoxide (R 2 = 0.56) and showed a highly significant difference between healthy subjects and COPD patients (8.8 μm vs 12.3 μm; p < 0.001), but was the only measure that actually discriminated healthy subjects from healthy smokers (8.8 μm vs 10.6 μm; p < 0.006).

Conclusion

Functional alveolar wall thickness assessed by hyperpolarized xenon-129 MR allows discrimination between healthy subjects and healthy smokers and could become a powerful new measure of early-stage lung disease.

INTRODUCTION

Despite preserved pulmonary function, many former and current smokers experience physical function impairments, reduced respiratory-specific quality of life, and an increased number of exacerbation events ( ). Studies based on computed tomography (CT), thin-section CT, and high-resolution CT, have demonstrated radiologically-detectable pulmonary abnormalities including ground-glass opacities, parenchymal micronodules, abnormal bronchial wall thickening, and emphysematous changes in a large fraction of nonsymptomatic current or former smokers in statistically significant excess to the levels found in healthy never-smokers ( ). Further, using magnetic resonance imaging (MRI) Alamidi et al ( ) showed a negative correlation between pack years and the relaxation time of the lung parenchyma possibly due to pathological decreases in microvascular blood flow in mild chronic obstructive pulmonary disease (COPD) ( ). Nevertheless, the clinical relevance of these findings has not been established and it remains infeasible to identify those individuals who will develop progressive COPD ( ).

Hyperpolarized gas MRI has provided additional insights in the ventilation, microstructure, and function of the lungs that are difficult to obtain with existing conventional lung imaging modalities. By filling the pulmonary airspaces with hyperpolarized helium-3 gas several groups have been able to identify statistically significant differences in ventilation patterns ( ), fractional ventilation ( ), lung morphology ( ), and pulmonary oxygen tension ( ) between normal control subjects, healthy smokers, and COPD patients. However, hyperpolarized helium-3 MRI provides only indirect measures of lung function due to its very low tissue solubility.

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MATERIALS AND METHODS

Subjects

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Physiologic Measurements

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Gas Polarization and Administration

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HXe MRI Data Acquisition

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Data Analysis

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Statistical Analysis

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Descriptive Data Summaries

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Analysis of Lung Function

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First Order Derivation of Age-Corrected Septal Wall Thickness

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Analysis of HXe MRI-Derived Lung Function Measurements

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Analysis of DLCO Dsb and Septal Wall Thickness

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Lung Function-based Separation of AMN and HS Individuals

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RESULTS

Demographics and Conventional Lung Function Measurements

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Figure 1, Empirical distributions of conventional lung function measures. If any of the letters above the boxplots match between groups they did not differ at the p < 0.05 level after Bonferroni correction. For subjects to be included in the study, all spirometric functions (FEF 25%–75%, FRC, RV, TLC, FVC, FEV1 %pred, and FEV1/FVC %pred) for the AMN and HS study groups had to be in the normal range. No statistically significant differences in DLCO and 6MWT were observed between the AMN and HS groups, either. Statistically significant differences for FEF 25%–75%, FEV1 %pred, FEV1/FVC %pred, and DLCO in the COPD cohort relative to those values in the AMN and HS groups were observed.

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Age Dependence of Septal Wall Thickness

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Figure 2, Function alveolar septal wall thickness as assessed by CSSR spectroscopy in healthy never smokers plotted as a function of age. The septal wall thickness shows a good linear correlation with the age of subject and increases by approximately 0.04 μm per year of age.

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HXe MRI Lung Function Measurements

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Figure 3, Empirical distribution of global measures of septal wall thickness, age-corrected septal wall thickness and apparent gas-phase diffusion coefficient for the three study cohorts. Correcting the measured septal wall thickness for the age of the subjects reduces the variability in the AMN cohort and further increases the statistical significance of the difference between the AMN and HS cohorts. The COPD cohort is characterized by a large increase in gas-phase diffusion relative to the AMN and HS cohorts, most likely due to emphysematous lung tissue destruction. If any of the letters above the boxplots match between groups they did not differ at the p < 0.05 level after Bonferroni correction.

Table 1

Between Study Group Comparisons of Septal Wall Thickness, AC-63 Septal Wall Thickness and Apparent Diffusion Coefficient (ADC)

HXe MRI-Derived Parameter AMNMean [95% CI] HSMean [95% CI] COPDMean [95% CI]p ValueHo: All Means Equal Septal Wall Thickness [μm] 8.7 [8.0, 9.4] a (a) 10.5 [9.4, 11.6] b (b) 12.4 [11.2, 13.7] c (b) <0.001 AC-63 Septal Wall Thickness [μm] 8.8 [8.3, 9.3] a (a) 10.6 [9.5, 11.7] b (b) 12.3 [11.1, 13.6] c (b) <0.001 Apparent Diffusing Coefficient (cm 2 /s) 0.04 [0.04, 0.05] a (a) 0.04 [0.04, 0.05] a (a) 0.06 [0.05, 0.07] b (b) <0.001

For the analysis of variances (ANOVA) in which the null hypothesis that all study group means are equal is rejected at the 0.05 significance level, pairwise tests were conducted. Study group means with same superscript outside of parenthesis signify the means did not differ at the two-sided p ≤ 0.05 significant level, while study group means with the same superscript inside of parenthesis signify that the mean did not differ at the Bonferroni multiple comparison corrected two-sided p ≤0.05 significant level.

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Figure 4, Plot of the apparent gas-phase diffusion constant as a function of the measured (A) and age-corrected (B) septal wall thickness. By subdividing the graph at a diffusion coefficient of 0.046 cm 2s and a septal wall thickness of 9.5 μm the three study cohorts appear clustered in the lower left (AMN), lower right (HS), and upper right (COPD) quadrants. The fourth quadrant (upper left) is empty. (Color version of figure is available online.)

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Comparison of Septal Wall Thickness and DLCO

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Figure 5, Plot of DLCO Dsb as a function of the measured (A) and age-corrected (B) septal wall thickness. Although there appears to exist a reasonable strong negative correlation between the septal wall thickness and DLCO (R 2 = 0.56) this correlation is mainly driven by the COPD subjects. If only the HS and AMN cohorts are considered the correlation disappears and the septal wall thickness alone is discriminative for the two cohorts. (Color version of figure is available online.)

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Lung Function-Based Separation of AMN and HS Individuals

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Table 2

Logistic Regression Odds Ratios and Receiver Operator Characteristics (ROC) for Predicting † AMN and HS Individuals Based on Lung Function Characteristics

Logistic Regression Odds Ratio Summary Receiver Operator Characteristics (ROC) Predictor Predictor Ratiothird quartile: first Odds Ratio[95% CI]p Value ROC AUC[95% CI] PredictorThreshold Sensitivity[95% CI] Specificity[95% CI] PPV[95% CI] NPV[95% CI] VC [L] 4.2: 3.2 0.29

[0.07, 1.25] 0.097 0.76

[0.52, 1.00] 3.85 88.9

[55.6, 100] 70.0

[40.0, 100] 72.7

[58.3, 100] 87.5

[66.7, 100] FRC [L] 3.8: 2.6 0.78

[0.22, 2.87] 0.725 0.58

[0.50, 0.87] 2.95 66.7

[22.2, 100] 70.0

[40.0, 100] 66.7

[50.0, 100] 70.0

[55.6, 100] RV [L] 2.4: 1.7 1.49

[0.60, 2.69] 0.384 0.52

[0.50, 0.81] 1.99 66.7

[11.1, 100] 60.0

[40.0, 100] 60.0

[50.0, 100] 66.7

[55.6, 88.9] TLC [L] 6.9: 5.0 0.60

[0.14, 2.51] 0.481 0.63

[0.50, 0.92] 6.12 77.8

[33.3, 100] 60.0

[40.0, 100] 63.6

[53.9, 100] 75.0

[58.3, 100] FVC [L] 3.9: 3.0 0.36

[0.09, 1.38] 0.137 0.74

[0.50, 0.99] 3.19 77.8

[55.6, 100] 80.0

[40.0, 100] 77.8

[57.1, 100] 80.0

[66.7, 100] FEV1 pred [%] 2.9: 2.2 0.42

[0.12, 1.46] 0.172 0.71

[0.50, 0.96 2.66 77.8

[33.3, 100] 60.0

[30.0, 100] 63.6

[53.9, 100] 75.0

[60.0, 100] FEV1/FVC pred [%] 96: 91 0.99

[0.36, 2.69] 0.978 0.57

[0.50, 0.84] 97.00 33.3

[11.1, 100] 90.0

[30.0, 100] 75.0

[50.0, 100] 60.0

[55.6, 100] DLCO Dsb [ml/min/mmHg] 24.3: 18.5 0.75

[0.25, 2.25] 0.607 0.56

[0.50, 0.83] 21.19 77.7

[22.2, 100] 50.0

[20.0, 100] 58.3

[50.0, 100] 71.5

[55.6, 100] 6MWT [steps] 486: 400 1.13

[0.32, 4.04] 0.084 0.77

[0.55, 0.99] 486 100

[33.3, 100] 50.0

[40.0, 100] 64.3

[60.0, 100] 100

[62.5, 100] Septal Wall Thickness [μm] 10.4: 8.5 15.38

[1.35, 174.24] 0.027 0.86

[0.69, 1.00] 9.25 88.9

[55.6, 88.9] 80.0

[50.0, 80.0] 80.0

[64.3, 81.8] 88.9

[71.4, 90.9] AC-63 Septal Wall Thickness [μm] 10.2: 8.6 30.34

[1.47, 629.33] 0.027 0.90

[0.75, 1.00] 9.53 88.9

[55.6, 88.9] 80.0

[69.7, 90.0] 80.0

[69.2, 90.0] 88.9

[71.4, 90.0] ADC [cm 2 /s] 0.045:0.039 1.13

[0.32, 4.04] 0.848 0.59

[0.50, 0.87] 0.04 77.8

[22.2, 100] 50.0

[30.0, 100] 58.3

[50.0, 100] 71.4

[55.6, 100]

† The predictor variable threshold for classifying individuals as AMD (predictor variable ≤threshold) or HS (predictor variable >cut point) was determined by identifying the threshold value that minimized the false classification error rate.

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DISCUSSION

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Acknowledgments

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Academic Radiology, Volume 26, Issue 3
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