Recent Developments in Fast Kurtosis Imaging

Brian Hansen,Sune N Jespersen

doi:10.3389/fphy.2017.00040

Abstract

Diffusion kurtosis imaging (DKI) is an extension of the popular diffusion tensor imaging (DTI) technique. DKI takes into account leading deviations from Gaussian diffusion stemming from a number of effects related to the microarchitecture and compartmentalization in biological tissues. DKI therefore offers increased sensitivity to subtle microstructural alterations over conventional diffusion imaging such as DTI, as has been demonstrated in numerous reports. For this reason, interest in routine clinical application of DKI is growing rapidly. In an effort to facilitate more widespread use of DKI, recent work by our group has focused on developing experimentally fast and robust estimates of DKI metrics. A significant increase in speed is made possible by a reduction in data demand achieved through rigorous analysis of the relation between the DKI signal and the kurtosis tensor based metrics. The fast DKI methods therefore need only 13 or 19 images for DKI parameter estimation compared to more than 60 for the most modest DKI protocols applied today. Closed form solutions also ensure rapid calculation of most DKI metrics. Some parameters can even be reconstructed in real time, which may be valuable in the clinic. The fast techniques are based on conventional diffusion sequences and are therefore easily implemented on almost any clinical system, in contrast to a range of other recently proposed advanced diffusion techniques. In addition to its general applicability, this also ensures that any acceleration achieved in conventional DKI through sequence or hardware optimization will also translate directly to fast DKI acquisitions. In this review, we recapitulate the theoretical basis for the fast kurtosis techniques and their relation to conventional DKI. We then discuss the currently available variants of the fast DKI methods, their strengths and weaknesses, as well as their respective realms of application. These range from whole body applications to methods mostly suited for spinal cord or peripheral nerve, and analysis specific to brain white matter. Having covered these technical aspects, we proceed to review the fast kurtosis literature including validation studies, organ specific optimization studies and results from clinical applications.

Highlights

Microstructural sensitivity in MRI is most often obtained by sensitizing the signal to the diffusion of water
The fast kurtosis methods are already used for imaging of experimental stroke [63, 64] and with the developments in Hansen et al [38, 42], axial and radial kurtosis can be investigated from fast diffusion kurtosis imaging (DKI) data along with WMTI parameters, e.g., for detection of axonal beading [96]
Fast kurtosis imaging is convenient for studies of the diffusion time dependence of DKI and WMTI parameters. Such experiments are expected to provide a deeper understanding of the WMTI branch ambiguity explored in Hansen et al [38] by making use of the theoretically expected diffusion time dependence [73]

Summary

Introduction

Microstructural sensitivity in MRI is most often obtained by sensitizing the signal to the diffusion of water. The fast DKI methods are convenient to ensure reasonable scan time for high resolution data acquisitions. The fast kurtosis methods are already used for imaging of experimental stroke [63, 64] and with the developments in Hansen et al [38, 42], axial and radial kurtosis can be investigated from fast DKI data along with WMTI parameters, e.g., for detection of axonal beading [96].

Results

Conclusion