Diffusion-relaxation correlation spectroscopic imaging: A multidimensional approach for probing microstructure.
OBJECTIVE
To propose and evaluate a novel multidimensional approach for imaging subvoxel tissue compartments called Diffusion-Relaxation Correlation Spectroscopic Imaging.


METHODS
Multiexponential modeling of MR diffusion or relaxation data is commonly used to infer the many different microscopic tissue compartments that contribute signal to macroscopic MR imaging voxels. However, multiexponential estimation is known to be difficult and ill-posed. Observing that this ill-posedness is theoretically reduced in higher dimensions, diffusion-relaxation correlation spectroscopic imaging uses a novel multidimensional imaging experiment that jointly encodes diffusion and relaxation information, and then uses a novel constrained reconstruction technique to generate a multidimensional diffusion-relaxation correlation spectrum for every voxel. The peaks of the multidimensional spectrum are expected to correspond to the distinct tissue microenvironments that are present within each macroscopic imaging voxel.


RESULTS
Using numerical simulations, experiment data from a custom-built phantom, and experiment data from a mouse model of traumatic spinal cord injury, diffusion-relaxation correlation spectroscopic imaging is demonstrated to provide substantially better multicompartment resolving power compared to conventional diffusion- and relaxation-based methods.


CONCLUSIONS
The diffusion-relaxation correlation spectroscopic imaging approach provides powerful new capabilities for resolving the different components of multicompartment tissue models, and can be leveraged to significantly expand the insights provided by MRI in studies of tissue microstructure. Magn Reson Med 78:2236-2249, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
Department of Electrical Engineering, University of Southern California, Los Angeles, California, USA.
Daeun
D
Kim
Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.|Department of Cardiology, Children's Hospital Los Angeles, Los Angeles, California, USA.
Eamon K
http://orcid.org/0000-0002-8652-6518
EK
Doyle
Department of Radiology, Children's Hospital Los Angeles, Los Angeles, California, USA.
Jessica L
JL
Wisnowski
Department of Neurology and Radiology, Washington University, St. Louis, Missouri, USA.
Joong Hee
JH
Kim
Department of Electrical Engineering, University of Southern California, Los Angeles, California, USA.|Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.
Justin P
JP
Haldar
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D003287:Contrast Media; D038524:Diffusion Magnetic Resonance Imaging; D006801:Humans; D051379:Mice; D015233:Models, Statistical; D016011:Normal Distribution; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio; D013116:Spinal Cord / Q000000981:diagnostic imaging; D013119:Spinal Cord Injuries / Q000000981:diagnostic imaging*; D014947:Wounds and Injuries / Q000000981:diagnostic imaging
D003287:Contrast Media
compartment modeling; constrained reconstruction; correlation spectroscopy; diffusion; relaxation