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. 2014 Feb;71(2):486-505.
doi: 10.1002/mrm.24729.

Probing lung microstructure with hyperpolarized noble gas diffusion MRI: theoretical models and experimental results

Affiliations

Probing lung microstructure with hyperpolarized noble gas diffusion MRI: theoretical models and experimental results

Dmitriy A Yablonskiy et al. Magn Reson Med. 2014 Feb.

Abstract

The introduction of hyperpolarized gases ((3)He and (129)Xe) has opened the door to applications for which gaseous agents are uniquely suited-lung MRI. One of the pulmonary applications, diffusion MRI, relies on measuring Brownian motion of inhaled hyperpolarized gas atoms diffusing in lung airspaces. In this article we provide an overview of the theoretical ideas behind hyperpolarized gas diffusion MRI and the results obtained over the decade-long research. We describe a simple technique based on measuring gas apparent diffusion coefficient (ADC) and an advanced technique, in vivo lung morphometry, that quantifies lung microstructure both in terms of Weibel parameters (acinar airways radii and alveolar depth) and standard metrics (mean linear intercept, surface-to-volume ratio, and alveolar density) that are widely used by lung researchers but were previously available only from invasive lung biopsy. This technique has the ability to provide unique three-dimensional tomographic information on lung microstructure from a less than 15 s MRI scan with results that are in good agreement with direct histological measurements. These safe and sensitive diffusion measurements improve our understanding of lung structure and functioning in health and disease, providing a platform for monitoring the efficacy of therapeutic interventions in clinical trials.

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Figures

FIG. 1.
FIG. 1.
Diffusion sensitizing pulse gradient waveform employed in diffusion MRI with hyperpolarized gases at short diffusion times. In this diagram Gm is the gradient lobe amplitude, Δ is the spacing between the leading edges of the positive and negative lobes (the diffusion time), δ is the full duration of each lobe, and τ is a ramp-up and ramp-down time.
FIG. 2.
FIG. 2.
Images of normal and emphysematous human lungs. Left to right–proton MRI, 3He ventilation maps, 3He gas ADC maps and histological slices (the latter adapted from Ref. 122); first row–normal lungs, second row–lung with emphysema. ADC in a normal lung is rather homogeneous except for large airways (trachea and its first branches) and is about 0.17 cm2/s. In the emphysema lung 3He gas penetrates only into ventilated regions (lower portion of the lung in this case) and has an ADC about three times bigger (0.55 cm2/s) than the ADC in the normal lung.
FIG. 3.
FIG. 3.
Correlation between ADC and (a) mean alveolar internal area (AIA) in rats with elastase induced emphysema (adapted from Ref. 90); (b) mean chord length (MCL) in elastase-induced emphysematous rabbit lungs (adapted from Ref. 102); (c) mean linear intercept Lm in healthy and emphysematous human lungs with data obtained at different diffusion times (in ms, shown by number by the lines) (■) −1.6 ms; (•) −5 ms; (▴) −10 ms) (adapted from Ref. 123); (d) mean linear intercept Lm in healthy human lungs and lungs with severe emphysema (adapted from Ref. 124).
FIG. 4.
FIG. 4.
ADC dependence on age: (a) (adapted from Ref. 98), (b) (adapted from Ref. 125); and lung inflation (c) (adapted from Ref. 125).
FIG. 5.
FIG. 5.
Scatter plots depict the relationship between the ADC parameters and spirometric indexes obtained from 16 healthy volunteers and 11 patients with emphysema (adapted from Ref. 83). The 95 % CIs for the regressions are shown as dotted lines. For all subjects, the mean ADCs correlated with the percentage of predicted FEV1 (r =−0.797, P < 0.001) (left) and FEV1/FVC (r = −0.930, P < 0.001) (right).
FIG. 6.
FIG. 6.
a: Distal portion of airways as seen with SEM. Terminal bronchiole (tb), respiratory bronchiole (rb), alveolar duct (ad), alveolar sacs (as), and alveoli (a) are seen in continuity as the airway branches to the pleura (p) (adapted from Ref. 163). b: Schematic drawing of acinar airway cross section representing eight alveoli surrounding the lumen (L) (adapted from Ref. 164). c: Schematic structure of two levels of acinar airways. Open spheres represent alveoli forming an alveolar sleeve around the lumen of each cylindrical airway. d: Cross-section of the acinar airway model (146) with two main parameters: external radius R and internal radius r (lumen radius) The other parameters, the depth of alveolar sleeve, h, and the alveolar length, L, are: h = Rr, L = 2R sin(π/8) = 0.765 R (8-alveolar model—see discussion below).
FIG. 7.
FIG. 7.
3He diffusion MRI signal intensity measured from a rat lung for nine b-values in a region of interest (right lung in the inset) (adapted from Ref. 127). The solid line is a fit to the model in Eq. [6], the dashed line is a fit to the kurtosis model, and the dotted line is a fit of the first four data points to a mono-exponential ADC model, imitating the acquisition of only a few low b-values.
FIG. 8.
FIG. 8.
Upper row: examples of the Lm (in mm) maps obtained from normal human lung (left) and lungs with different stages of emphysema (mild–middle and severe–right) (adapted from Ref. 146). Lower row: examples of histological slices obtained from the same lungs as above. Right panel: plot of mean linear intercept obtained by means of lung morphometry with hyperpolarized 3He diffusion MRI versus direct measurement. Each point represents one lung. Lm (3He) is median calculated across entire lung; Lm (histology) is median calculated across all lung specimens corresponding to this lung.
FIG. 9.
FIG. 9.
Summary of data obtained for six human lung specimens. a: DL0, DT0, and ADC (in cm2/s); b: R and h (in mm); c: S/V (in cm−1); d: Nv (in mm−3) (adapted from Ref. 146). Markers (•) represent two control healthy lungs, markers (▴)–two lungs with mild emphysema, markers (▾)−two lungs with severe emphysema. Each data point is a median calculated across all imaging voxels for a given lung specimen. Horizontal axis is the mean Lm obtained from direct histological measurements on the same lungs.
FIG. 10.
FIG. 10.
Examples of the maps of acinar airways geometric parameters obtained with 3He lung morphometry and CT images for a GOLD 0 former smoker (left, FEV1 = 93 % predicted, FEV1/FVC = 80 %), a GOLD 0 smoker (middle, FEV1 = 94 % predicted, FEV1/FVC = 71 %), and a GOLD 2 former smoker (right, FEV1 = 62 % predicted, FEV1/FVC = 56 %) (adapted from Ref. 104). These images illustrate the heterogeneity of disease across the lungs and the significant increases in R and Lm, and decreases in h and Nv with COPD. Red pixels on the CT images indicate regions of emphysema (attenuation less than −950 HU). Charts on the right summarize results obtained from 30 current and former smokers; they show the increase in (a) mean chord length, (b) %EI−950, and (c) acinar duct radius, and decrease in (d) alveolar depth h with decreasing prebronchodilator FEV1/FVC by PFT. The FEV1/FVC <70 % group is statistically significant against all other groups for all measurements shown (*P < 0.05). The FEV1/FVC 70 to 80 % group is also statistically significant against all other groups on the 3He lung morphometry measurements (*P < 0.05), but not on the CT-based %EI−950. Error bars are standard deviations.
FIG. 11.
FIG. 11.
Histograms of the lung geometrical parameters and CT images in HU for the subjects in Figure 10.
FIG. 12.
FIG. 12.
Examples of axial maps of alveolar sleeve depth h (left panel) mean linear intercept Lm (middle panel), and acinar-duct radii R (right panel) obtained with 129Xe lung morphometry in a healthy human volunteer at 3 T (adapted from Ref. 169).
FIG. 13.
FIG. 13.
Two types of basic airway configurations contributed to MRI signal (adapted from Ref. 145). The internal alveolar structure of the airways is not shown and the aspect ratio is changed for better view of the structures. The first configuration with two nodes (a) corresponds to an alveolar duct of generation Z (shaded airway), surrounded by a “parent” duct of generation (Z − 1), a “sister” airway of generation Z, and two “daughter” airways of generation (Z + 1). Symmetrical branching with half-angle α = 40° is assumed. The second configuration with one node (b) corresponds to an alveolar sac of terminal generation Z (shaded airway), surrounded by a “parent” duct of generation (Z − 1) and a “sister” airway of generation Z.
FIG. 14.
FIG. 14.
ADC versus Lm found for 30 subjects from study (104) (adapted from Ref. 189). a: The average (over each subject) values of the parameters ADC and Lm. b: ADC and Lm calculated on a pixel-by-pixel basis (grey symbols). The lines represent the dependence of ADC as a function of Lm, theoretically calculated at fixed values of the ratio h/R (given by numbers near the lines). Importantly, each value of Lm can be associated with numerous values of ADC, and vice versa.
FIG. 15.
FIG. 15.
Time sequence of tagged images in dog with emphysema in the right lung only (right side of each image) (adapted from Ref. 116). The images have a tagging wavelength of 3 cm and were acquired 0 to 4.1 s after tagging, in equal increments of 1.36 s. The images presented are all from the same slice, out of a total of 10 slices. The LRADC map at lower right is calculated from the decay rate of the fractional modulation on a pixel-by-pixel basis, and shows a substantial difference in LRADC between the two lungs. The fast diffusion is evident from the rapid disappearance of the modulation in the right lung. An ADC map of short-range diffusion is also shown for comparison; note the different scales for LRADC and ADC.

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References

    1. 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 Respir Crit Care Med 2007;176:532–555. - PubMed
    1. Mead J, Turner JM, Macklem PT, Little JB. Significance of the relationship between lung recoil and maximum expiratory flow. J Appl Physiol 1967;22:95–108. - PubMed
    1. Hogg JC, Macklem PT, Thurlbeck WM. Site and nature of airway obstruction in chronic obstructive lung disease. New Engl J Med 1968;278:1355–1360. - PubMed
    1. Van Brabandt H, Cauberghs M, Verbeken E, Moerman P, Lauweryns JM, Van de Woestijne KP. Partitioning of pulmonary impedance in excised human and canine lungs. J Appl Physiol 1983;55:1733–1742. - PubMed
    1. Yanai M, Sekizawa K, Ohrui T, Sasaki H, Takishima T. Site of airway obstruction in pulmonary disease: direct measurement of intrabronchial pressure. J Appl Physiol 1992;72:1016–1023. - PubMed

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