Multidimensional correlation MRI

Abstract

Multidimensional correlation spectroscopy is emerging as a novel MRI modality that is well suited for microstructure and microdynamic imaging studies, especially of biological specimens. Conventional MRI methods only provide voxel‐averaged and mostly macroscopically averaged information; these methods cannot disentangle intra‐voxel heterogeneity on the basis of both water mobility and local chemical interactions. By correlating multiple MR contrast mechanisms and processing the data in an integrated manner, correlation spectroscopy is able to resolve the distribution of water populations according to their chemical and physical interactions with the environment. The use of a non‐parametric, phenomenological representation of the multidimensional MR signal makes no assumptions about tissue structure, thereby allowing the study of microscopic structure and composition of complex heterogeneous biological systems. However, until recently, vast data requirements have confined these types of measurement to non‐localized NMR applications and prevented them from being widely and successfully used in conjunction with imaging. Recent groundbreaking advancements have allowed this powerful NMR methodology to be migrated to MRI, initiating its emergence as a promising imaging approach. This review is not intended to cover the entire field of multidimensional MR; instead, it focuses on pioneering imaging applications and the challenges involved. In addition, the background and motivation that have led to multidimensional correlation MR development are discussed, along with the basic underlying mathematical concepts. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed and their potential benefits, and to provide guidance to help refine future applications of this technology.

Multidimensional MRI for characterization of subtle axonal injury accelerated using an adaptive nonlocal multispectral filter

“…Visual inspection of the different injury biomarker maps shown in Figs. 4 and S1 revealed that filtering of the data does not result in loss of the spectral information of interest, and furthermore, the filtered images appear qualitatively of higher quality. Importantly, the data reduction in the case of the filtered data did not significantly affect the resulting injury biomarker maps (Fig.…”

Efficient whole‐brain tract‐specific T1 mapping at 3T with slice‐shuffled inversion‐recovery diffusion‐weighted imaging

“…By combining both contrast encoding mechanisms into the same sequence, a multi-dimensional characterization of the voxel's microstructural compartments can be performed. [17][18][19][20][21][22] These diffusion-relaxometry experiments typically include multiple echo times (TE) and/or repetition times (TR) to vary the T 2 -and T 1 -weighting, respectively.…”

Low-field and variable-field NMR relaxation studies of H2O and D2O molecular dynamics in articular cartilage

“…While such approaches certainly date back to the 1980s, the actual 2D representation of such datasets has benefitted from the developments of related 2D versions of the ILT algorithm [ 21 ]. T 1 -T 2 correlation maps [ 22 , 23 ] have been instrumental in improving the understanding of discrete or distributed components of spin sets in complex systems such as crude oil [ 24 , 25 ] and food materials [ 26 ], or porous media such as rocks [ 22 , 27 ] and cement paste [ 28 , 29 ] and even biological applications [ 30 ]. However, T 1 -T 2 studies of biological matter are scarce, and the authors are aware of only one recent work where cartilage has been investigated as part of a larger study [ 31 ].…”