FICK , Rutger

This thesis is dedicated to furthering neuroscientific understanding of the human brain using diffusion-sensitized Magnetic Resonance Imaging (dMRI). Within dMRI, we focus on the estimation and interpretation of microstructure-related markers, often referred to as ``Microstructure Imaging''. This thesis is organized in three parts. Part I...

Non-invasive estimation of brain microstructure features using diffusion MRI (dMRI)—known as Microstructure Imaging—has become an increasingly diverse and complicated field over the last decades. Multi-compartment (MC)-models, representing the measured diffusion signal as a linear combination of signal models of distinct tissue types, have been...

International audience

Bolus dispersion affects the residue function computed via deconvolution of DSC-MRI data. The obtained effective residue function can be expressed as the convolution of the true one with a Vascular Transport Function (VTF) that characterizes dispersion. The state-of-the-art technique CPI+VTF allows to estimate the actual residue function by...

The non-Gaussian noise distribution in magnitude Diffusion-Weighted Images (DWIs) can severely affect the estimation and reconstruction of the true diffusion signal. As a consequence, also the estimated diffusion metrics can be biased. We study the effect of phase correction, a procedure that re-establishes the Gaussianity of the noise...

We propose a novel framework to simultaneously represent the diffusion-weighted MRI (dMRI) signal over diffusion times, gradient strengths and gradient directions. Current frameworks such as the 3D Simple Harmonic Oscillator Reconstruction and Estimation basis (3D-SHORE) only represent the signal over the spatial domain, leaving the temporal...

The recovery of microstructure-related features of the brain's white matter is a current challenge in diffusion MRI.To robustly estimate these important features from multi-shell diffusion MRI data, we propose to analytically regularize the coefficient estimation of the Mean Apparent Propagator (MAP)-MRI method using the norm of the Laplacian...

Dispersion effects in perfusion MRI data have a relevant influence on the residue function computed from deconvolution of the measured arterial and tissular concentration time-curves. Their characterization allows reliable estimation of hemody-namic parameters and can reveal pathological tissue conditions. However, the time-delay between the...

Non-invasive estimation of brain white matter microstructure features using diffusion MRI - otherwise known as Microstructure Imaging - has become an increasingly diverse and complicated field over the last decade. Multi-compartment-based models have been a popular approach to estimate these features. In this work, we present Diffusion...

The micro-architecture of brain tissue obstructs the movement of diffusing water molecules, causing tissue-dependent, often anisotropic diffusion profiles. In diffusion MRI (dMRI), the relation between brain tissue structure and diffusion anisotropy is studied using oriented diffusion gradients, resulting in tissue-and orientation-dependent...

In DSC-MRI the presence of dispersion affects the estimation, via deconvolution, of the residue function that characterizes the perfusion in each voxel. Dispersion is descibed by a Vascular Transport Function (VTF) which knolewdge is essential to recover a dispersion-free residue function. State-of-the-art techniques aim at characterizing the...

In diffusion MRI, the accurate description of the entire diffusion signal from sparse measurements is essential to enable the recovery of microstructural information of the white matter. The recent Mean Apparent Propagator (MAP)-MRI basis is especially well suited for this task, but the basis fitting becomes unreliable in the presence of noise....

Axon diameter estimation has been a focus of the diffusion MRI community for the past decade. The main argument has been that while diffusion models always overestimate the true axon diameter, their estimation still correlates with changes in true value. Until now, this remains more as a discussion point. The aim of this paper is to clarify...

Three dimensional Polarized Light Imaging (3D-PLI) is a contrast-enhancing technique that measures the spatial fiber architecture in the human postmortem brain or heart at a submillimeter resolution. In a voxel, the 3D fiber orientation is defined by the direction angle and the inclination angle whose sign is unknown. To have an accurate...

We propose a novel method to simultaneously trace brain white matter (WM) fascicles and estimate WM microstructure character- istics. Recent advancements in diffusion-weighted imaging (DWI) allow multi-shell acquisitions with b-values of up to 10,000 s/mm2 in human subjects, enabling the measurement of the ensemble average propagator (EAP) at...

Current theories hold that brain function is highly related with long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcella-tion based on extrinsic connectivity remains challenging. Current par-cellation methods are computationally expensive; need tuning of several...

Diffusion MRI (dMRI) has been widely used to estimate brain tissue microstructure in-vivo.Two of the most widely used microstructural indices are the white matter (WM) andintra-cellular (IC) volume fractions (VF) [2012z,2019f]. In estimating these fractions, acommon assumption of dMRI-based signal modeling is to assume that the T2-relaxation...

This paper highlights a systematic bias in white matter tissue microstructure modelling via diffusion MRI that is due to the common, yet inaccurate, assumption that all brain tissues have a similar T2 response. We show that the concept of "signal fraction" is more appropriate to describe what have always been referred to as "volume fraction"....

State-of-the-art multi-compartment microstructural models of diffusion MRI (dMRI) in the human brain have limited capability to model multiple tissues at the same time. In particular, the available techniques that allow this multi-tissue modelling are based on multi-TE acquisitions. In this work we propose a novel multi-tissue formulation of...

In Diffusion MRI, q-space indices are scalar quantities that describe properties of the ensemble average propagator (EAP). Their values are often linked to the axonal diameter – assuming that the diffusion signal originates from inside an ensemble of parallel cylinders. However, histological studies show that these assumptions are incorrect,...

For clinical applications the number of diffusion MRI (dMRI) samples that can be obtained is often limited by scanner time and patient comfort. For this reason one often uses short scanning protocols that acquire just 32 or 64 gradient directions using a single b-value to obtain diffusion measures such as the fractional anisotropy from...

Diffusion MRI (dMRI) is used to characterize the directional-ity and microstructural properties of brain white matter (WM) by measuring the diffusivity of water molecules. In clinical practice the number of dMRI samples that can be obtained is limited, and one often uses short scanning protocols that acquire just 32 to 64 different gradient...

We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both methods are based on the same PDE framework, defined in the coupled space of positions and orientations, associated with a stochastic process describing the enhancement of elongated structures...

Effective representation of the diffusion signal's dependence on diffusion time is a sought-after, yet still unsolved challenge in diffusion MRI (dMRI). We propose a functional basis approach that is specifically designed to represent the dMRI signal in this four-dimensional space – varying over gradient strength, direction and diffusion time –...

We assess the test-retest reproducibility of time-dependent q-space indices (qτ-indices) in three C57Bl6 wild-type mice. To estimate qτ-indices from the four-dimensional qτ diffusion signal - varying over 3D q-space and diffusion time - we use our recent Multi-Spherical Diffusion MRI (MS-dMRI) method. Using MS-dMRI we could reliably estimate...