Diffusion-weighted hyperpolarized 129Xe MRI in healthy volunteers and subjects with chronic obstructive pulmonary disease

Abstract

Given its greater availability and lower cost, (129) Xe apparent diffusion coefficient (ADC) MRI offers an alternative to (3) He ADC MRI. To demonstrate the feasibility of hyperpolarized (129) Xe ADC MRI, we present results from healthy volunteers (HV), chronic obstructive pulmonary disease (COPD) subjects, and age-matched healthy controls (AMC). The mean parenchymal ADC was 0.036 ± 0.003 cm(2) sec(-1) for HV, 0.043 ± 0.006 cm(2) sec(-1) for AMC, and 0.056 ± 0.008 cm(2) sec(-1) for COPD subjects with emphysema. In healthy individuals, but not the COPD group, ADC decreased significantly in the anterior-posterior direction by ∼ 22% (P = 0.006, AMC; 0.0059, HV), likely because of gravity-induced tissue compression. The COPD group exhibited a significantly larger superior-inferior ADC reduction (∼ 28%) than the healthy groups (∼ 24%) (P = 0.00018, HV; P = 3.45 × 10(-5) , AMC), consistent with smoking-related tissue destruction in the superior lung. Superior-inferior gradients in healthy subjects may result from regional differences in xenon concentration. ADC was significantly correlated with pulmonary function tests (forced expiratory volume in 1 sec, r = -0.77, P = 0.0002; forced expiratory volume in 1 sec/forced vital capacity, r = -0.77, P = 0.0002; diffusing capacity of carbon monoxide in the lung/alveolar volume (V(A) ), r = -0.77, P = 0.0002). In healthy groups, ADC increased with age by 0.0002 cm(2) sec(-1) year(-1) (r = 0.56, P = 0.02). This study shows that (129) Xe ADC MRI is clinically feasible, sufficiently sensitive to distinguish HV from subjects with emphysema, and detects age- and posture-dependent changes.

Copyright © 2010 Wiley-Liss, Inc.

Figures

Figure 1

Erosion and dilation of binary masks. A: Binary mask generated from a representative, non-diffusion weighted image (b = 0) of a COPD subject with emphysema. The mask was generated using a threshold obtained using the mean background intensity mean plus twice its standard deviation. B: Mask from A after erosion using a circular structuring element (radius = 3 pixels), showing that the majority of the background noise has been removed C: Mask from B after dilation with the same structuring element showing the restoration of subtle image features.

Figure 2

Effect of masking on the ADC map generation. Separate masks were generated for a healthy volunteer using only a threshold, a threshold followed by erosion/dilation, and manual segmentation. The top row shows the masks and the bottom row shows the corresponding ADC map obtained after application of the mask. With a threshold mask, the mean ADC of the healthy subject was 0.041±0.026 cm2/s. This mean ADC reduced to 0.037±0.021 cm2/s with a mask that underwent erosion/dilation with a circular structuring element with a radius of 3-pixels. With a manually segmented mask, the mean ADC was the same as that obtained using erosion/dilation.

Figure 3

Representative slices from 129Xe ADC maps and corresponding whole-lung ADC histograms. A: Healthy volunteer (age = 28 years) with a low mean ADC of 0.037±0.021 cm2/s indicating normal alveolar microstructure. The ADC values in the airways are higher (0.083±0.029 cm2/s) and reflect nearly free diffusion. B: Age matched healthy control displaying similarly low parenchymal ADC values (0.042±0.025 cm2/s). C: COPD subject with emphysema shows high ADC values (0.068±0.028 cm2/s) in the parenchyma, indicating alveolar destruction. D: Whole-lung histogram for the healthy volunteer in panel A showing narrow ADC distribution. E: Whole-lung histogram for the age-matched control in panel B, exhibits a similarly homogenous distribution. F: Whole-lung histogram corresponding to the COPD subject with emphysema in panel C, exhibiting a moderately broader distribution.

Figure 4

Mean parenchyma ADC values for each subject group. The mean ADC of the COPD subjects with emphysema (0.056±0.008 cm2/s) was significantly higher than that of the age-matched controls (0.043± 0.006 cm2/s, p = 0.0021), which in turn was significantly higher than that of the healthy volunteers (0.036±0.003 cm2/s, p = 0.0046).

Figure 5

A complete ADC map for a healthy volunteer. The map shows clear ADC gradients in both the superior-inferior and anterior-posterior directions.

Figure 6

ADC gradients. (A) Mean ADC gradients in the superior-inferior direction. This gradient was significantly larger in the COPD subjects with emphysema (0.00074 cm2/s/cm) than in the age matched healthy controls (0.00049 cm2/s/cm, p = 0.024), and was also larger than that of the healthy volunteers (0.00038 cm2/s/cm, p = 0.0017). There was no significant difference between the superior-inferior gradients observed in the two groups of healthy subjects (p = 0.09). (B) Mean ADC gradients in the anterior-posterior direction. The mean ADC gradient from the COPD subjects with emphysema (3.05×10-5 cm2/s/cm) is significantly smaller than that of either the healthy volunteers (0.00072 cm2/s/cm, p = 0.014) or the age matched healthy controls (0.00065 cm2/s/cm, p = 0.0085). The ADC gradients from the two groups of two healthy subjects were not significantly different (p = 0.81) from one another.

Figure 7

Correlation of mean parenchymal ADC with pulmonary function metrics and age. (A) Correlation with percentage of predicted FEV1. r = −0.77, p = 0.0002. (B) Correlation with percentage of predicted FEV1/FVC. r = -0.78, p = 0.0002. (C) Correlation with percentage of predicted DLCO/VA. r = −0.77, p = 0.0002. (D) Correlation with age (healthy subjects only). r = 0.56, p = 0.02.