| 1. |
- Ahmadi, Khazar, et al.
(författare)
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Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer’s Disease
- 2024
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Ingår i: Journal of Neuroscience. - 0270-6474. ; 44:18
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Tidskriftsartikel (refereegranskat)abstract
- Several studies have shown white matter (WM) abnormalities in Alzheimer’s disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aβ-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aβ-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.
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| 2. |
- Bergamino, Maurizio, et al.
(författare)
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Applying a free-water correction to diffusion imaging data uncovers stress-related neural pathology in depression
- 2016
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Ingår i: NeuroImage. - : Elsevier. - 2213-1582. ; 10, s. 336-342
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Tidskriftsartikel (refereegranskat)abstract
- Diffusion tensor imaging (DTI) holds promise for developing our understanding of white-matter pathology in major depressive disorder (MDD). Variable findings in DTI-based investigations ofMDD, however, have thwarted development of this literature. Effects of extra-cellular free-water on the sensitivity of DTI metrics could account for some of this inconsistency. Here we investigated whether applying a free-water correction algorithm to DTI data could improve the sensitivity to detect clinical effects using DTI metrics. Only after applying this correction, we found: a) significantly decreased fractional anisotropy and axial diffusivity (AD) in the left inferior frontooccipital fasciculus (IFOF) in MDD; and b) increased self-reported stress that significantly correlated with decreased IFOF AD in depression. We estimated and confirmed the robustness of differences observed between free-water corrected and uncorrected approaches using bootstrapping. We conclude that applying a free-water correction to DTI data increases the sensitivity of DTI-based metrics to detect clinical effects in MDD. (C) 2015 The Authors. Published by Elsevier Inc.
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| 3. |
- Rydhög, Anna, et al.
(författare)
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Estimation of diffusion, perfusion and fractional volumes using a multi-compartment relaxation-compensated intravoxel incoherent motion (IVIM) signal model
- 2019
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Ingår i: European Journal of Radiology Open. - : Elsevier BV. - 2352-0477. ; 6, s. 198-205
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Scherman Rydhög, Anna, et al.
(författare)
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Separating Blood and Water: Perfusion and Free Water Elimination from Diffusion MRI in the Human Brain.
- 2017
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Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119. ; 156, s. 423-434
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 5. |
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| 6. |
- Westin, Carl-Fredrik, et al.
(författare)
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Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding
- 2014
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Ingår i: Lecture Notes in Computer Science. - Cham : Springer International Publishing. - 1611-3349. ; 17:Pt 3, s. 16-209, s. 209-216
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Tidskriftsartikel (refereegranskat)abstract
- In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).
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| 7. |
- Westin, Carl-Fredrik, et al.
(författare)
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Q-space trajectory imaging for multidimensional diffusion MRI of the human brain
- 2016
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Ingår i: NeuroImage. - : Elsevier. - 1053-8119 .- 1095-9572. ; 135, s. 345-362
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Tidskriftsartikel (refereegranskat)abstract
- This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.
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| 8. |
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