Introduction

Hyperpolarized ¹²⁹Xe diffusion-weighted (DW)-MRI provides 3D in-vivo information of lung microstructure with the derived apparent diffusion coefficient (ADC) due to Brownian gas atom diffusion restriction within the acinar airways. Theoretical models of gas diffusion within the lungs, such as the cylinder airway model (CM)¹ and stretched exponential model (SEM)², are used to derive in-vivo acinar airways dimensions in patients with a range of pulmonary diseases³.

Airspace Dimension Assessment with inhaled nanoparticles (AiDA) is a recently proposed alternative non-invasive technique for evaluating distal airspace dimensions with measurements of nanoparticles deposited by Brownian diffusion in the distal airways⁴. AiDA measures the recovery of inhaled nanoparticles after a series of breath-holds of varying duration, and analysis yields an estimated root mean square distal airspace radius (r_AiDA) and the recovery at zero-second breath-hold (R₀ intercept)⁵. In healthy volunteers, r_AiDA significantly correlated with MRI proton lung tissue density⁶, but further benchmarking with established methods of in-vivo acinar airspace assessment is required. The aim of this work was therefore to benchmark AiDA measurements against ¹²⁹Xe DW-MRI derived ADC and acinar airway dimensions in a healthy volunteer cohort.

Methods

Twenty-three healthy volunteers (14M, 9F) with no history of lung disease were recruited for AiDA at Lund University, and hyperpolarized ¹²⁹Xe DW-MRI at University of Sheffield. This study was approved by the Regional Ethical Review Board in Lund, Sweden, and performed in accordance with the Declaration of Helsinki, including obtaining informed written consent from all volunteers.

A schematic illustrating the instrument used for AiDA is shown in Figure 1a⁵. Nanoparticles were generated by aerosolizing polystyrene latex nanospheres using an electrospray, size selected (50 nm) using a differential mobility analyzer and diluted with particle free air. The inhaled and exhaled nanoparticle concentration was continuously sampled using a condensation particle counter for different consecutive breath-hold times of 5, 5, 6, 8, 10, 12, 15, and 15 seconds. The nanoparticle residence time in the lungs was found by adding an individual’s breathing phase to the breath-hold times. An exponential decay curve was fitted to recovery values for each residence time (Figure 1b) to derive r_AiDA from the half-life (t_1/2) of this decay and the diffusion coefficient (D)⁴: $$$\text{r}_{\text{AiDA}}=\sqrt{Dt_{1/2}}$$$. R₀ intercept was subsequently derived from the extrapolation of the exponential decay to a theoretical recovery value at zero-second residence time.

Hyperpolarized ¹²⁹Xe DW-MRI was acquired on a GE HDx 1.5T scanner with a flexible transmit/receive quadrature vest coil using a 3D multiple b-value SPGR sequence with compressed sensing². DW-MRI acquisition parameters were: diffusion time=8.5 ms, b=[0, 12, 20, 30 s/cm²]. ¹²⁹Xe ADC was calculated on a voxel-by-voxel basis using a mono-exponential fit between b=0 and 12 s/cm² interleaves; while for ¹²⁹Xe acinar airway dimensions, the SEM² and CM¹ was fitted to all four b-values to derive: mean diffusive length scale (Lm_D), alpha heterogeneity index, acinar airway radius (R_CM) and mean chord length (Lm) measurements. Correlations between inhaled nanoparticles and global ¹²⁹Xe DW-MRI measurements were assessed using Spearman’s rank correlation tests in GraphPad Prism 8.

Results and Discussion

Table 1 summarizes volunteer demographics and mean global measurements from ¹²⁹Xe DW-MRI and AiDA for this healthy cohort. ¹²⁹Xe ADC and acinar airway dimensions lie between reported values for younger (29±4 years) healthy volunteers and ex-smokers³, demonstrating the prevalence of age-related acinar airway changes in this cohort of older healthy volunteers. This was supported by significant correlations (P<0.05) between volunteer age and all ¹²⁹Xe DW-MRI metrics, except for alpha heterogeneity index. AiDA derived r_AiDA and R₀ intercept measurements in this healthy cohort were comparable to previously reported values in a similarly aged volunteers⁶. A trend towards increased r_AiDA with age was observed; however, this was not statistically significant (P=0.072).

Statistically significant linear correlations were observed between r_AiDA and all ¹²⁹Xe DW-MRI metrics (P=0.001), except for alpha index, indicating that r_AiDA is a measure of acinar airway dimensions (Figure 2). The ¹²⁹Xe acinar airway dimension that showed the best agreement with the r_AiDA measurement appeared to be R_CM. Agreement was confirmed with Bland-Altman analysis, where a mean bias of -15.0 µm (95% agreement limits of -57.6 to 27.6 µm) towards r_AiDA was obtained (Figure 3). This agreement between R_CM and r_AiDA is likely related to the similar underlying cylindrical tube/airway geometry that underpins both the CM and AiDA models, respectively. The remaining bias between the measurements could be attributed to the multiple breath-hold acquisition and longer diffusion times of AiDA, in contrast to the single breath-hold acquisition and millisecond diffusion time of ¹²⁹Xe DW-MRI. The R₀ intercept from AiDA significantly correlated with ¹²⁹Xe alpha heterogeneity index (P=0.019) (Figure 4). This correlation could be representative of heterogeneity in the distal/acinar airways that both metrics are hypothesized to measure^2,4.

Conclusion

This work has benchmarked estimates of root mean square airway radius from inhaled nanoparticles (r_AiDA) against ¹²⁹Xe DW-MRI metrics in a healthy volunteer cohort, and the significant correlations indicate that r_AiDA is a measure of acinar airway microstructure. Further benchmarking in non-symptomatic smokers could be used to evaluate the relative sensitivity of AiDA and ¹²⁹Xe DW-MRI in detecting early emphysematous changes to the acinar microstructure.

Acknowledgements

This work was supported by NIHR grant NIHR-RP-R3-12-027 and MRC grant MR/M008894/1. The views expressed in this work are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.