Abstract #0732

Towards unconstrained compartment modeling in white matter using diffusion-relaxation MRI with tensor-valued diffusion encoding

Björn Lampinen¹, Filip Szczepankiewicz^2,3, Johan Mårtensson⁴, Danielle van Westen², Oskar Hansson⁵, Carl-Fredrik Westin³, and Markus Nilsson²

¹Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, ²Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, ³Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, ⁴Clinical Sciences Lund, Department of Logopedics, Phoniatrics and Audiology, Lund University, Lund, Sweden, ⁵Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden

Microstructure imaging aims to estimate specific quantities such as the axonal density through modeling of diffusion MRI (dMRI) data. However, the low information content of conventional dMRI necessitates assumptions limiting the estimates’ accuracy. Here, we show how to replace model assumptions with independent information from tensor-valued diffusion encoding and diffusion-relaxation experiments. We present sampling protocols optimized using Cramér-Rao lower bounds allowing precise whole-brain estimation of compartment-specific fractions, diffusivities and T₂ values in 15 minutes and show results from subjects of different ages. The approach greatly expands the set of parameters measurable with dMRI and provides parameter relations informing model constraints.

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