| Literature DB >> 31909534 |
Daeun Kim1,2, Jessica L Wisnowski3,4, Christopher T Nguyen5,6,7, Justin P Haldar1,2.
Abstract
Multiexponential modeling of relaxation or diffusion MR signal decays is a popular approach for estimating and spatially mapping different microstructural tissue compartments. While this approach can be quite powerful, it is also limited by the fact that one-dimensional multiexponential modeling is an ill-posed inverse problem with substantial ambiguities. In this article, we present an overview of a recent multidimensional correlation spectroscopic imaging approach to this problem. This approach helps to alleviate ill-posedness by making advantageous use of multidimensional contrast encoding (e.g., 2D diffusion-relaxation encoding or 2D relaxation-relaxation encoding) combined with a regularized spatial-spectral estimation procedure. Theoretical calculations, simulations, and experimental results are used to illustrate the benefits of this approach relative to classical methods. In addition, we demonstrate an initial proof-of-principle application of this kind of approach to in vivo human MRI experiments.Entities:
Keywords: constrained reconstruction; high-dimensional contrast encoding; microstructure; multicomponent modeling; multidimensional relaxometry; regularization; relaxometry and diffusometry; spatial regularization
Year: 2020 PMID: 31909534 PMCID: PMC7338241 DOI: 10.1002/nbm.4244
Source DB: PubMed Journal: NMR Biomed ISSN: 0952-3480 Impact factor: 4.044