David Romascano^{1,2}, Erick J. Canales-Rodriguez^{3}, Jonathan Rafael-Patino^{1}, Marco Pizzolato^{1}, Gaëtan Rensonnet^{1,4}, Muhamed Barakovic^{1}, Gabriel Girard^{1,5}, Alessandro Daducci^{6}, Tim B. Dyrby^{2,7}, and Jean-Philippe Thiran^{1,5}

We present HOTmix, a new model to describe the diffusion MRI signal for molecules undergoing hindered diffusion. HOTmix is based on a mixture of generalized higher order tensors, explicitly incorporating the diffusion sequence’s time-dependent parameters. The method was evaluated on simulated diffusion MRI signals obtained through Monte Carlo simulations, using intermediate diffusion times, mimicking both ex-vivo and in-vivo conditions. HOTmix provided better reconstructions compared to the standard diffusion tensor, the kurtosis tensor, and a single generalized higher order tensor. In future work, we will explore whether modelling the hindered compartment using HOTmix improves microstructural features estimated using dMRI.

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Table 1: ex-vivo and in-vivo diffusion protocols

Figure 1: Illustration of the pipeline used to generate EA dMRI signals for 2 different substrates (IA volume fractions of 0.7). (a) Cylinder diameter distributions; (b) cylinder positions (100x100um^{2} section is shown for visibility); (c) generated dMRI signals. Left: 489’691 small radii from $$$\Gamma$$$(8.5,3.7E-8). Right: 16’589 large radii from $$$\Gamma$$$(3.2,4.9E-7).

Figure 2: Reconstructed ex-vivo signals (dotted lines) overlapped with the corresponding ground-truth (full lines) when using DT, DK, HOT and HOTmix. For each model, the signals for the substrate with smallest and highest mean cylinder size are shown.

Figure 3: RMAE over all substrates for the different models when
reconstructing the signal using parameters estimated from the noiseless
ex-vivo signal, the noiseless in-vivo signal, the noisy ex-vivo signal
and the noisy in-vivo signal.