6018 Quantification of lung microstructure in asthma using a 3 He fractional diffusion approach

Target audience: Lung imaging, Diffusion MRI, hyperpolarized agents Purpose: To quantify lung microstructure in asthma patients using a stretched-exponential model of He MRI diffusion measurements. Introduction MR diffusion experiments using hyperpolarized gases are sensitive to acinar airway dimensions. The fractional diffusion stretched-exponential model has been shown to provide a robust quantitative measure of changes in lung microstructure due to emphysema [1]. In this work, this approach is further developed to allow for in-vivo estimation of the distributions of the microscopic length scales of acinar airways from He diffusion MRI data. This new technique is used to assess the acinar microstructure in asthma patients and the results are compared with CT densitometry and macroscopic He ventilation distributions. Methods Thirty-three patients (moderate-severe uncontrolled asthmatics GINA 2-5) were scanned at 1.5T using hyperpolarised He with local ethics approval. A 2D spoiled gradient echo imaging sequence (64x48 matrix, TE: 4.8 ms, TR: 9.0 ms, FOV:38.4 cm) with bipolar diffusion gradients (diffusion time Δ= 1.6ms) was used and five slices were acquired consecutively (thickness 15mm and 10mm spacing). Four interleaved acquisitions were obtained for each slice, corresponding to equally spaced diffusion b values: 0, 2.4, 4.8 and 7.2 s/cm. The decay of the diffusion signal S(b) in the images can be described using the stretched exponential function [1]: S(b)/S0= exp[-(b.DDC))]; where DDC is the diffusivity and α is the heterogeneity index. Unlike existing geometrical models this model addresses the non-mono exponential nature of the diffusion MRI signal without any underlying assumptions of airway geometry. Taking into account that the macroscopic voxel signal originates from the superposition of signals from multiple microscopic compartment with different apparent diffusivities D, i.e. S(b)/S0 = ∫p(D) exp(-b.D) dD, the probability density function p(D) for each voxel can then be estimated [2] from the stretched exponential parameters. The distribution of length scales LD (i.e. root mean squared displacements) associated with the D values can then be calculated using the diffusion equation: LD= (2DΔ) for each voxel. The p(LD) distributions are hence a measure of the distribution of microscopic dimensions of the airways contained within a given voxel. A mean length value LmD, was calculated for each patient’s diffusion imaging data (average over all voxels) and compared with their corresponding CT attenuation values (full expiration), percentage ventilation volumes (Vv%) from the He ventilation images [4] and pulmonary function test (PFT) results. Results and Discussion Experimental results showed a significant variation in the values of the DDC and α parameters among the asthma patients, which were classified into two clusters using a k-means algorithm (Fig.1). Patients in cluster 1 showed values near those found in normal lungs in a previous study [1], while patients in cluster 2 had values of DDC (higher) and α (lower) that deviated from the normal range. This deviation is however lower than that reported in COPD patients [1]. The distributions of airway length scales p(LD) (Fig. 2) in patients in Cluster 2 were broader and shifted toward higher airway length scales LD than distributions from patients in Cluster 1. The shape of these distributions are very similar to the distributions of intercept length (Lx) obtained in histological studies [3]. The LmD values showed significant correlation with FRC (% predicted): ρ= 0.75, p<0.001 and CT density: ρ= 0.79, p<0.001 (Fig. 3). Unlike average CT density, the LmD values are obtained from He ventilated regions only (i.e. does not include trapped air). Higher correlation may be achieved if unventilated regions are excluded from the CT average density calculation and we extend to a regional comparison using image registration. Although