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Abstract #3465

Time-Dependent Standard Model of diffusion in human brain white matter evaluated in vivo on the high gradient performance Connectome 2.0 scanner

Kwok-Shing Chan1,2, Yixin Ma1,2, Hansol Lee1,2, Santiago Coelho3,4, Els Fieremans3,4, Dmitry S. Novikov3,4, Susie Huang1,2, and Hong-Hsi Lee1,2
1Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States, 3Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States, 4Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States

Synopsis

Keywords: Microstructure, Microstructure

Motivation: While most biophysical models in brain white matter estimate Gaussian compartment parameters, characteristic length scales of tissue microstructure can only be obtained from non-Gaussian features.

Goal(s): To introduce time dependence into the Standard Model of diffusion; to in vivo evaluate non-Gaussian signatures of diffusion in intra- and extra-neurite spaces, irrespective of neurite orientation dispersion.

Approach: We perform diffusion measurements on the Connectome 2.0 scanner in healthy volunteers at short times (13-30 ms) and estimate time-dependent diffusion parameters using GPU-accelerated fitting.

Results: Time-dependent diffusion signals up to 2nd-order in spherical harmonics provide sensitivity potentially related to axonal beadings and packing correlation length.

Impact: We demonstrated the feasibility of mapping time-dependent diffusion in human white matter in vivo using the Connectome 2.0 scanner. This potentially provides novel biomarkers sensitive to axon beadings and packing length scales for investigation of neurological disorders.

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Keywords