White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging

Abstract

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases but has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared to typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI to those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (1 sample) and in vivo human (3 subjects) and rat brain (4 animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 μm isotropic resolution with whole brain coverage in a one hour acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders.

Recent Developments in Fast Kurtosis Imaging

“…Determining which of these two "branches" yields physically correct parameter estimates has been subject of some debate [38,73,74] and is not yet fully resolved. In Hansen et al [38] affected parameters are reported for both branches.…”

“…Determining which of these two "branches" yields physically correct parameter estimates has been subject of some debate [38,73,74] and is not yet fully resolved. In Hansen et al [38] affected parameters are reported for both branches. The solutions for the two branches are much more obvious than in conventional WMTI, where the sign choice is only known to be stable over diffusion encoding directions for the branch defined by D a ≤ D e,|| [2].…”

“…Similarly, the increase in acquisition speed facilitates high resolution data acquisitions for validation purposes or for in vivo applications. High resolution in vivo WMTI based on the 1-9-9 fast DKI protocol is demonstrated in Figure 6 using one of four rats analyzed in Hansen et al [38]. The advantage of the fast WMTI techniques is evident as the low data requirement allows whole brain coverage at an isotropic resolution of 300 µm to be acquired in 1 h. For ex vivo studies, e.g., for validation studies with subsequent histological analysis, the fast axisymmetric WMTI method enables studies at even higher resolution with high SNR with substantially shorter acquisition times than required for conventional WMTI.…”

“…When evaluated along the radial and axial directions and with averaging over all directions, these general expressions yield directional diffusivities and kurtoses from which expressions for AWF = f , D a , D e,⊥ , and D e,|| can be derived [38]:…”

“…Here we review recent developments enabling fast kurtosis imaging based on small data sets (13 or 19 images) and with near-instant post-processing [37][38][39][40][41][42]. The review is structured such that first the theoretical foundation of DKI and WMTI is recapitulated briefly.…”