-
NeuroImage Nov 2023Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells.... (Review)
Review
Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.
Topics: Humans; Brain; Magnetic Resonance Imaging; Gray Matter; Diffusion Magnetic Resonance Imaging; White Matter; Anisotropy
PubMed: 37598814
DOI: 10.1016/j.neuroimage.2023.120338 -
NeuroImage May 2023Neural tissue microstructure plays an important role in developmental, physiological and pathophysiological processes. Diffusion tensor distribution (DTD) MRI helps...
Neural tissue microstructure plays an important role in developmental, physiological and pathophysiological processes. Diffusion tensor distribution (DTD) MRI helps probe subvoxel heterogeneity by describing water diffusion within a voxel using an ensemble of non-exchanging compartments characterized by a probability density function of diffusion tensors. In this study, we provide a new framework for acquiring multiple diffusion encoding (MDE) images and estimating DTD from them in the human brain in vivo. We interfused pulsed field gradients (iPFG) in a single spin echo to generate arbitrary b-tensors of rank one, two, or three without introducing concomitant gradient artifacts. Employing well-defined diffusion encoding parameters we show that iPFG retains salient features of a traditional multiple-PFG (mPFG/MDE) sequence while reducing the echo time and coherence pathway artifacts thereby extending its applications beyond DTD MRI. Our DTD is a maximum entropy tensor-variate normal distribution whose tensor random variables are constrained to be positive definite to ensure their physicality. In each voxel, the second-order mean and fourth-order covariance tensors of the DTD are estimated using a Monte Carlo method that synthesizes micro-diffusion tensors with corresponding size, shape, and orientation distributions to best fit the measured MDE images. From these tensors we obtain the spectrum of diffusion tensor ellipsoid sizes and shapes, and the microscopic orientation distribution function (μODF) and microscopic fractional anisotropy (μFA) that disentangle the underlying heterogeneity within a voxel. Using the DTD-derived μODF, we introduce a new method to perform fiber tractography capable of resolving complex fiber configurations. The results revealed microscopic anisotropy in various gray and white matter regions and skewed MD distributions in cerebellar gray matter not observed previously. DTD MRI tractography captured complex white matter fiber organization consistent with known anatomy. DTD MRI also resolved some degeneracies associated with diffusion tensor imaging (DTI) and elucidated the source of diffusion heterogeneity which may help improve the diagnosis of various neurological diseases and disorders.
Topics: Humans; Diffusion Tensor Imaging; Diffusion Magnetic Resonance Imaging; Brain; White Matter; Magnetic Resonance Imaging; Anisotropy
PubMed: 36907281
DOI: 10.1016/j.neuroimage.2023.120003 -
Brain : a Journal of Neurology Feb 2021Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains...
Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provides a quantitative measure of axonal injury in vivo, with fractional anisotropy often used as a proxy for white matter damage. Diffusion imaging has been widely used in TBI but is not routinely applied clinically. This is in part because robust analysis methods to diagnose axonal injury at the individual level have not yet been developed. Here, we present a pipeline for diffusion imaging analysis designed to accurately assess the presence of axonal injury in large white matter tracts in individuals. Average fractional anisotropy is calculated from tracts selected on the basis of high test-retest reliability, good anatomical coverage and their association to cognitive and clinical impairments after TBI. We test our pipeline for common methodological issues such as the impact of varying control sample sizes, focal lesions and age-related changes to demonstrate high specificity, sensitivity and test-retest reliability. We assess 92 patients with moderate-severe TBI in the chronic phase (≥6 months post-injury), 25 patients in the subacute phase (10 days to 6 weeks post-injury) with 6-month follow-up and a large control cohort (n = 103). Evidence of axonal injury is identified in 52% of chronic and 28% of subacute patients. Those classified with axonal injury had significantly poorer cognitive and functional outcomes than those without, a difference not seen for focal lesions or microbleeds. Almost a third of patients with unremarkable standard MRIs had evidence of axonal injury, whilst 40% of patients with visible microbleeds had no diffusion evidence of axonal injury. More diffusion abnormality was seen with greater time since injury, across individuals at various chronic injury times and within individuals between subacute and 6-month scans. We provide evidence that this pipeline can be used to diagnose axonal injury in individual patients at subacute and chronic time points, and that diffusion MRI provides a sensitive and complementary measure when compared to susceptibility weighted imaging, which measures diffuse vascular injury. Guidelines for the implementation of this pipeline in a clinical setting are discussed.
Topics: Adult; Anisotropy; Axons; Brain Injuries, Traumatic; Diffusion Magnetic Resonance Imaging; Female; Humans; Image Processing, Computer-Assisted; Male; Middle Aged; Reproducibility of Results; White Matter
PubMed: 33257929
DOI: 10.1093/brain/awaa372 -
Human Brain Mapping Nov 2022Diffusion tensor imaging (DTI) has provided great insights into the microstructural features of the developing brain. However, DTI images are prone to several artifacts...
Diffusion tensor imaging (DTI) has provided great insights into the microstructural features of the developing brain. However, DTI images are prone to several artifacts and the reliability of DTI scalars is of paramount importance for interpreting and generalizing the findings of DTI studies, especially in the younger population. In this study, we investigated the intrascan test-retest repeatability of four DTI scalars: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in 5-year-old children (N = 67) with two different data preprocessing approaches: a volume censoring pipeline and an outlier replacement pipeline. We applied a region of interest (ROI) and a voxelwise analysis after careful quality control, tensor fitting and tract-based spatial statistics. The data had three subsets and each subset included 31, 32, or 33 directions thus a total of 96 unique uniformly distributed diffusion encoding directions per subject. The repeatability of DTI scalars was evaluated with intraclass correlation coefficient (ICC(3,1)) and the variability between test and retest subsets. The results of both pipelines yielded good to excellent (ICC(3,1) > 0.75) reliability for most of the ROIs and an overall low variability (<10%). In the voxelwise analysis, FA and RD had higher ICC(3,1) values compared to AD and MD and the variability remained low (<12%) across all scalars. Our results suggest high intrascan repeatability in pediatric DTI and lend confidence to the use of the data in future cross-sectional and longitudinal studies.
Topics: Humans; Child; Child, Preschool; Diffusion Tensor Imaging; Reproducibility of Results; Cross-Sectional Studies; Anisotropy; Brain
PubMed: 36098477
DOI: 10.1002/hbm.26064 -
Alzheimer's Research & Therapy Feb 2023Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and...
BACKGROUND
Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD.
METHODS
One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation.
RESULTS
Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups.
CONCLUSIONS
There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.
Topics: Humans; Alzheimer Disease; Cognition; Anisotropy; Gyrus Cinguli; Mutation
PubMed: 36850008
DOI: 10.1186/s13195-023-01192-y -
NMR in Biomedicine May 2021Metabolite diffusion measurable in humans in vivo with diffusion-weighted spectroscopy (DW-MRS) provides a window into the intracellular morphology and state of specific...
Metabolite diffusion measurable in humans in vivo with diffusion-weighted spectroscopy (DW-MRS) provides a window into the intracellular morphology and state of specific cell types. Anisotropic diffusion in white matter is governed by the microscopic properties of the individual cell types and their structural units (axons, soma, dendrites). However, anisotropy is also markedly affected by the macroscopic orientational distribution over the imaging voxel, particularly in DW-MRS, where the dimensions of the volume of interest (VOI) are much larger than those typically used in diffusion-weighted imaging. One way to address the confound of macroscopic structural features is to average the measurements acquired with uniformly distributed gradient directions to mimic a situation where fibers present in the VOI are orientationally uniformly distributed. This situation allows the extraction of relevant microstructural features such as transverse and longitudinal diffusivities within axons and the related microscopic fractional anisotropy. We present human DW-MRS data acquired at 7 T in two different white matter regions, processed and analyzed as described above, and find that intra-axonal diffusion of the neuronal metabolite N-acetyl aspartate is in good correspondence to simple model interpretations, such as multi-Gaussian diffusion from disperse fibers where the transverse diffusivity can be neglected. We also discuss the implications of our approach for current and future applications of DW-MRS for cell-specific measurements.
Topics: Adult; Anisotropy; Aspartic Acid; Computer Simulation; Corpus Callosum; Cytosol; Diffusion Magnetic Resonance Imaging; Female; Humans; Male; Monte Carlo Method; White Matter
PubMed: 32232909
DOI: 10.1002/nbm.4304 -
Molecular Psychiatry Oct 2023Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies.... (Meta-Analysis)
Meta-Analysis
Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.
Topics: Adult; Humans; Child; White Matter; Attention Deficit Disorder with Hyperactivity; Diffusion Tensor Imaging; Brain; Corpus Callosum; Anisotropy
PubMed: 37479785
DOI: 10.1038/s41380-023-02173-1 -
Journal of Veterinary Internal Medicine Sep 2021Degenerative myelopathy (DM) in dogs shares similarities with superoxide dismutase 1-associated human amyotrophic lateral sclerosis (ALS). Brain microstructural lesions...
BACKGROUND
Degenerative myelopathy (DM) in dogs shares similarities with superoxide dismutase 1-associated human amyotrophic lateral sclerosis (ALS). Brain microstructural lesions are quantified using diffusion tensor imaging (DTI) in ALS patients.
OBJECTIVE
Characterize brain neurodegenerative changes in DM-affected dogs using DTI.
ANIMALS
Sixteen DM-affected and 8 control dogs.
METHODS
Prospective observational study. Brain DTI was performed at baseline and every 3 months on DM-affected dogs and compared to controls. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated on specified regions of interest. Gait scores (0, normal to 14, tetraplegia) were assigned at each scan. Diffusion tensor imaging values in DM-affected dogs were compared to controls, gait scores, and evaluated over time.
RESULTS
Mean age was 5.7 years (SD 3.2) in controls and 9.7 years (SD 1.4) in DM-affected dogs. In DM-affected dogs, mean baseline gait score was 4 (SD 1), and mean score change from baseline to last scan was 4.82 (SD 2.67). Nine dogs had ≤3 scans; 7 had >3 scans. Accounting for age, no differences in DTI indices were identified for any brain or proximal spinal cord regions between DM-affected dogs and controls (P > .05). Diffusion tensor imaging values poorly correlated with gait scores (R < .2). No significant changes were identified in diffusion indices over time (P > .05).
CONCLUSIONS AND CLINICAL IMPORTANCE
Diffusion tensor imaging indices did not differentiate DM-affected from control dogs, detect longitudinal changes, or differentiate disease severity. Findings do not yet support brain DTI as an imaging biomarker.
Topics: Animals; Dogs; Amyotrophic Lateral Sclerosis; Anisotropy; Biomarkers; Brain; Diffusion Tensor Imaging; Dog Diseases
PubMed: 34410026
DOI: 10.1111/jvim.16248 -
Magnetic Resonance in Medicine Jan 2023To assess the ability of MRI-DTI to evaluate growth plate morphology and activity compared with that of histomorphometry and micro-CT in rabbits.
PURPOSE
To assess the ability of MRI-DTI to evaluate growth plate morphology and activity compared with that of histomorphometry and micro-CT in rabbits.
METHODS
The hind limbs of female rabbits aged 16, 20, and 24 wk (n = 4 per age group) were studied using a 9.4T MRI scanner with a multi-gradient echo 3D sequence and DTI in 14 directions (b-value = 984 s/mm ). After MRI, the right and left hind limb were processed for histological analysis and micro-CT, respectively. The Wilcoxon signed-rank test was used to evaluate the height and volume of the growth plate. Intraclass correlation and Pearson correlation coefficient were used to evaluate the association between DTI metrics and age.
RESULTS
The growth plate height and volume were similar for all modalities at each time point and age. Age was correlated with all tractography and DTI metrics in both the femur and tibia. A correlation was also observed between all the metrics at both sites. Tract number and volume declined with age; however, tract length did not show any changes. The fractional anisotropy color map showed lateral diffusion centrally in the growth plate and perpendicular diffusion in the hypertrophic zone, as verified by histology and micro-CT.
CONCLUSION
MRI-DTI may be useful for evaluating the growth plates.
Topics: Animals; Rabbits; Female; Diffusion Tensor Imaging; Growth Plate; Anisotropy; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Diffusion Magnetic Resonance Imaging
PubMed: 36110062
DOI: 10.1002/mrm.29432 -
Cartilage Dec 2021To investigate the influences of the diffusion gradient directions (angular resolution) and the strength of the diffusion gradient ( value) on diffusion tensor imaging...
OBJECTIVE
To investigate the influences of the diffusion gradient directions (angular resolution) and the strength of the diffusion gradient ( value) on diffusion tensor imaging (DTI) metrics and tractography of various connective tissues in knee joint.
DESIGN
Two rat knee joints were scanned on a preclinical 9.4-T system using a 3-dimensional diffusion-weighted spin echo pulse sequence. One protocol with value of 500, 1500, and 2500 s/mm were acquired separately using 43 diffusion gradient directions. The other protocol with value of 1000 s/mm was performed using 147 diffusion gradient directions. The in-plane resolution was 45 µm isotropic. Fractional anisotropy (FA) and mean diffusivity (MD) were compared at different angular resolution. Tractography was quantitatively evaluated at different values and angular resolutions in cartilage, ligament, meniscus, and growth plate.
RESULTS
The ligament showed higher FA value compared with growth plate and cartilage. The FA values were largely overestimated at the angular resolution of 6. Compared with FA, MD showed less sensitivity to the angular resolution. The fiber tracking was failed at low angular resolution (6 diffusion gradient directions) or high value (2500 s/mm). The quantitative measurements of tract length and track volume were strongly dependent on angular resolution and value.
CONCLUSIONS
To obtain consistent DTI outputs and tractography in knee joint, the scan may require a proper value (ranging from 500 to 1500 s/mm) and sufficient angular resolution (>14) with signal-to-noise ratio >10.
Topics: Animals; Anisotropy; Diffusion Tensor Imaging; Image Processing, Computer-Assisted; Knee Joint; Rats; Signal-To-Noise Ratio
PubMed: 33843284
DOI: 10.1177/19476035211007909