Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values

Associations of increased interstitial fluid with vascular and neurodegenerative abnormalities in a memory clinic sample

The vascular and neurodegenerative processes related to clinical dementia cause cell loss which induces, amongst others, an increase in interstitial fluid (ISF). We assessed microvascular, parenchymal integrity, and a proxy of ISF volume alterations with intravoxel incoherent motion imaging in 21 healthy controls and 53 memory clinic patients - mainly affected by neurodegeneration (mild cognitive impairment, Alzheimer's disease dementia), vascular pathology (vascular cognitive impairment), and presumed to be without significant pathology (subjective cognitive decline). The microstructural components were quantified with spectral analysis using a non-negative least squares method. Linear regression was employed to investigate associations of these components with hippocampal and white matter hyperintensity (WMH) volumes. In the normal appearing white matter, a large f_int (a proxy of ISF volume) was associated with a large WMH volume and low hippocampal volume. Likewise, a large f_int value was associated with a lower hippocampal volume in the hippocampi. Large ISF volume (f_int) was shown to be a prominent factor associated with both WMHs and neurodegenerative abnormalities in memory clinic patients and is argued to play a potential role in impaired glymphatic functioning.

Estimation of diffusion, perfusion and fractional volumes using a multi-compartment relaxation-compensated intravoxel incoherent motion (IVIM) signal model

Compartmental diffusion MRI models that account for intravoxel incoherent motion (IVIM) of blood perfusion allow for estimation of the fractional volume of the microvascular compartment. Conventional IVIM models are known to be biased by not accounting for partial volume effects caused by free water and cerebrospinal fluid (CSF), or for tissue-dependent relaxation effects. In this work, a three-compartment model (tissue, free water and blood) that includes relaxation terms is introduced. To estimate the model parameters, in vivo human data were collected with multiple echo times (TE), inversion times (TI) and b-values, which allowed a direct relaxation estimate alongside estimation of perfusion, diffusion and fractional volume parameters. Compared to conventional two-compartment models (with and without relaxation compensation), the three-compartment model showed less effects of CSF contamination. The proposed model yielded significantly different volume fractions of blood and tissue compared to the non-relaxation-compensated model, as well as to the conventional two-compartment model, suggesting that previously reported parameter ranges, using models that do not account for relaxation, should be reconsidered.

Separating blood and water: Perfusion and free water elimination from diffusion MRI in the human brain

The assessment of the free water fraction in the brain provides important information about extracellular processes such as atrophy and neuroinflammation in various clinical conditions as well as in normal development and aging. Free water estimates from diffusion MRI are assumed to account for freely diffusing water molecules in the extracellular space, but may be biased by other pools of molecules in rapid random motion, such as the intravoxel incoherent motion (IVIM) of blood, where water molecules perfuse in the randomly oriented capillary network. The goal of this work was to separate the signal contribution of the perfusing blood from that of free-water and of other brain diffusivities. The influence of the vascular compartment on the estimation of the free water fraction and other diffusivities was investigated by simulating perfusion in diffusion MRI data. The perfusion effect in the simulations was significant, especially for the estimation of the free water fraction, and was maintained as long as low b-value data were included in the analysis. Two approaches to reduce the perfusion effect were explored in this study: (i) increasing the minimal b-value used in the fitting, and (ii) using a three-compartment model that explicitly accounts for water molecules in the capillary blood. Estimation of the model parameters while excluding low b-values reduced the perfusion effect but was highly sensitive to noise. The three-compartment model fit was more stable and additionally, provided an estimation of the volume fraction of the capillary blood compartment. The three-compartment model thus disentangles the effects of free water diffusion and perfusion, which is of major clinical importance since changes in these components in the brain may indicate different pathologies, i.e., those originating from the extracellular space, such as neuroinflammation and atrophy, and those related to the vascular space, such as vasodilation, vasoconstriction and capillary density. Diffusion MRI data acquired from a healthy volunteer, using multiple b-shells, demonstrated an expected non-zero contribution from the blood fraction, and indicated that not accounting for the perfusion effect may explain the overestimation of the free water fraction evinced in previous studies. Finally, the applicability of the method was demonstrated with a dataset acquired using a clinically feasible protocol with shorter acquisition time and fewer b-shells.

Comparison of BOLD, diffusion-weighted fMRI and ADC-fMRI for stimulation of the primary visual system with a block paradigm

The blood oxygen level-dependent (BOLD) effect is extensively used for functional MRI (fMRI) but presents some limitations. Diffusion-weighted fMRI (DfMRI) has been proposed as a method more tightly linked to neuronal activity. This work proposes a protocol of DfMRI acquired for several b-values and diffusion directions that is compared to gradient-echo BOLD (GE-BOLD) and to repeated spin-echo BOLD (SE-BOLD, acquisitions performed with b=0s/mm²), which was also used to ensure the reproducibility of the response. A block stimulation paradigm of the primary visual system (V1) was performed in 12 healthy subjects with checkerboard alternations (2Hz frequency). DfMRI was performed at 3T with 5 b-values (b=1500, 1000, 500, 250, 0s/mm²) with TR/TE=1004/93ms, Δ/δ=45.4ms/30ms, and 6 spatial directions for diffusion measures. GE-BOLD was performed with a similar block stimulation design timing. Apparent Diffusion Coefficient (ADC)-fMRI was computed with all b-values used. An identical Z-score level was used for all fMRI modalities for the comparison of volumes of activation. ADC-fMRI and SE-BOLD fMRI activation locations were compared in a voxel-based analysis to a cytoarchitectural probability map of V1. SE-BOLD activation volumes represented only 55% of the GE-BOLD activation volumes (P<0.0001). DfMRI activation volumes averaged for all b-values acquired represented only 12% of GE-BOLD (P<0.0001) and only 22% of SE-BOLD activation volumes (P<0.005). Compared to SE-BOLD-fMRI, ADC-fMRI activations showed fewer pixels outside of V1 and a higher average probability of belonging to V1. DfMRI and ADC-fMRI acquisition at 3T could be easily post-processed with common neuro-imaging software. DfMRI and ADC-fMRI activation volumes were significantly smaller than those obtained with SE-BOLD. ADC-fMRI activations were more precisely localized in V1 than those of SE-BOLD-fMRI. This validated the increased capability of ADC-fMRI compared to BOLD to enhance the precision of localizing an fMRI activation in the cyto-architectural zone V1, thereby justifying the use of ADC-fMRI for neuro-scientific studies.