dMRI Techniques Research Articles

Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging.

Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear. This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI). Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment. In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline.

Temporal Diffusion Ratio (TDR) for imaging restricted diffusion: Optimisation and pre-clinical demonstration

Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (Dell'Acqua et al., proc. ISMRM 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for informing on pore sizes, in particular the presence of large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion gradient waveforms. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time introduces and optimises the TDR method in simulation for a range of different tissues and scanner constraints and validates it in a pre-clinical demonstration. We consider both substrates containing cylinders and spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration, short diffusion time and high gradient strength with an acquisition with long gradient duration, long diffusion time and low gradient strength, maximises the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for informing on pore sizes and restricted diffusion in general.

Soma and Neurite Density MRI (SANDI) of the in-vivo mouse brain and comparison with the Allen Brain Atlas

Diffusion MRI (dMRI) provides unique insights into the neural tissue milieu by probing interactions between diffusing molecules and tissue microstructure. Most dMRI techniques focus on white matter (WM) tissues, nevertheless, interest in gray matter characterizations is growing. The Soma and Neurite Density MRI (SANDI) methodology harnesses a model incorporating water diffusion in spherical objects (assumed to be associated with cell bodies) and in impermeable “sticks” (assumed to represent neurites), which potentially enables the characterization of cellular and neurite densities. Recognising the importance of rodents in animal models of development, aging, plasticity, and disease, we here employ SANDI for in-vivo preclinical imaging and provide a first validation of the methodology by comparing SANDI metrics with cellular density reflected by the Allen mouse brain atlas. SANDI was implemented on a 9.4T scanner equipped with a cryogenic coil, and in-vivo experiments were carried out on N = 6 mice. Pixelwise, ROI-based, and atlas comparisons were performed, magnitude vs. real-valued analyses were compared, and shorter acquisitions with reduced the number of b-value shells were investigated. Our findings reveal good reproducibility of the SANDI parameters, including the sphere and stick fractions, as well as sphere size (CoV < 7%, 12% and 3%, respectively). Additionally, we find a very good rank correlation between SANDI-driven sphere fraction and Allen mouse brain atlas contrast that represents cellular density. We conclude that SANDI is a viable preclinical MRI technique that can greatly contribute to research on brain tissue microstructure.

Advanced Diffusion MRI of the Visual System in Glaucoma: From Experimental Animal Models to Humans.

Simple SummaryThis review summarizes current applications of advanced diffusion magnetic resonance imaging (MRI) throughout the glaucomatous visual system, focusing on the eye, optic nerve, optic tract, subcortical visual brain nuclei, optic radiations, and visual cortex. Glaucoma continues to be the leading cause of irreversible blindness worldwide and often remains undetected until later disease stages. The development of non-invasive methods for early detection of visual pathway integrity could pave the way for timely intervention and targeted treatment strategies. Principles of diffusion have been integrated with MRI protocols to produce a diffusion-weighted imaging modality for studying changes to tissue microstructures by quantifying the movement of water molecules in vivo. The development and applications of diffusion MRI in ophthalmology have allowed a better understanding of neural pathway changes in glaucoma. The feasibility of translating diffusion MRI techniques to assess both humans and experimental animal models of glaucoma and other optic neuropathies or neurodegenerative diseases is discussed. Recent research focuses on overcoming limitations in imaging quality, acquisition times, and biological interpretation suggest that diffusion MRI can provide an important tool for the non-invasive evaluation of glaucomatous changes in the visual system.Glaucoma is a group of ophthalmologic conditions characterized by progressive retinal ganglion cell death, optic nerve degeneration, and irreversible vision loss. While intraocular pressure is the only clinically modifiable risk factor, glaucoma may continue to progress at controlled intraocular pressure, indicating other major factors in contributing to the disease mechanisms. Recent studies demonstrated the feasibility of advanced diffusion magnetic resonance imaging (dMRI) in visualizing the microstructural integrity of the visual system, opening new possibilities for non-invasive characterization of glaucomatous brain changes for guiding earlier and targeted intervention besides intraocular pressure lowering. In this review, we discuss dMRI methods currently used in visual system investigations, focusing on the eye, optic nerve, optic tract, subcortical visual brain nuclei, optic radiations, and visual cortex. We evaluate how conventional diffusion tensor imaging, higher-order diffusion kurtosis imaging, and other extended dMRI techniques can assess the neuronal and glial integrity of the visual system in both humans and experimental animal models of glaucoma, among other optic neuropathies or neurodegenerative diseases. We also compare the pros and cons of these methods against other imaging modalities. A growing body of dMRI research indicates that this modality holds promise in characterizing early glaucomatous changes in the visual system, determining the disease severity, and identifying potential neurotherapeutic targets, offering more options to slow glaucoma progression and to reduce the prevalence of this world’s leading cause of irreversible but preventable blindness.

The structural connectome in ADHD.

Attention-deficit/hyperactivity disorder (ADHD) has been conceptualized as a brain dysconnectivity disorder. In the past decade, noninvasive diffusion magnetic resonance imaging (dMRI) studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome, and that these alterations are associated with core symptoms and cognitive deficits in patients. This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-, tractography-, and network-based perspectives. Voxel- and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts, the corpus callosum, the corticospinal tracts, and the cingulum bundle in patients with ADHD. Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes. The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification. These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation. However, given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations, these ADHD-related white matter alterations are still far from informing clinical practice. Future studies with larger and more homogeneous samples are needed to validate the consistency of current results; advanced dMRI techniques can help to generate much more precise estimation of white matter pathways and assure specific fiber configurations; and finally, dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.

The Mathematics of Quasi-Diffusion Magnetic Resonance Imaging

Quasi-diffusion imaging (QDI) is a novel quantitative diffusion magnetic resonance imaging (dMRI) technique that enables high quality tissue microstructural imaging in a clinically feasible acquisition time. QDI is derived from a special case of the continuous time random walk (CTRW) model of diffusion dynamics and assumes water diffusion is locally Gaussian within tissue microstructure. By assuming a Gaussian scaling relationship between temporal (α) and spatial (β) fractional exponents, the dMRI signal attenuation is expressed according to a diffusion coefficient, D (in mm2 s−1), and a fractional exponent, α. Here we investigate the mathematical properties of the QDI signal and its interpretation within the quasi-diffusion model. Firstly, the QDI equation is derived and its power law behaviour described. Secondly, we derive a probability distribution of underlying Fickian diffusion coefficients via the inverse Laplace transform. We then describe the functional form of the quasi-diffusion propagator, and apply this to dMRI of the human brain to perform mean apparent propagator imaging. QDI is currently unique in tissue microstructural imaging as it provides a simple form for the inverse Laplace transform and diffusion propagator directly from its representation of the dMRI signal. This study shows the potential of QDI as a promising new model-based dMRI technique with significant scope for further development.

Diffusion MR Imaging with T2-based Water Suppression (T2wsup-dMRI).

Purpose: This study proposes and assesses a new diffusion MRI (dMRI) technique to solve problems related to the quantification of parameter maps (apparent diffusion coefficient [ADC] or mean diffusivity [MD], fractional anisotropy [FA]) and misdrawing of fiber tractography (FT) due to cerebrospinal fluid (CSF)-partial volume effects (PVEs) for brain tissues by combining with the T2-based water suppression (T2wsup) technique.Methods: T2wsup–diffusion-weighted imaging (DWI) images were obtained by subtracting those images from the acquired multi-b value (b) DWI images after correcting the signal intensities of multiecho time (TE) images using long TE water signal-dominant images. Quantitative parameter maps and FT were obtained from minimum data points and were compared with those using the standard (without wsup) DWI method, and partly compared with those obtained using other alternative DWI methods of applying fluid attenuation inversion recovery (FLAIR), non-b-zero (NBZ) by theoretical or noise-added simulation and MR images.Results: In the T2wsup-dMRI method, the hyperintense artifacts due to CSF-PVEs in MRI data were dramatically suppressed even at lower b (≲ 500 s/mm2) while keeping the tissue SNR. The quantitative parameter map values became precisely close to the pure tissue values precisely even in water (CSF) PVE voxels in healthy brain tissues (T2 ≲ 100 ms). Furthermore, the fiber tracts were correctly connected, particularly at the fornix in closest contact to the CSF.Conclusion: Solving the problem of CSF-PVE in the current dMRI technique using our proposed T2wsup-dMRI technique is easy, with higher SNR than those obtained with FLAIR or NBZ methods when applying to healthy brain tissues. The proposed T2wsup–dMRI could be useful in clinical settings, although further optimization of the pulse sequence and processing techniques and clinical assessments are required, particularly for long T2 lesions.

Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project.

Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project—a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.

Diffusion MRI detects basal forebrain cholinergic abnormalities in the 3xTg-AD mouse model of Alzheimer's disease

Degeneration of the basal forebrain (BF) is detected early in the course of Alzheimer's disease (AD). Reduction in the number of BF cholinergic (ChAT) neurons associated with age-related hippocampal cholinergic neuritic dystrophy is described in the 3xTg-AD mouse model; however, no prior diffusion MRI (dMRI) study has explored the presence of BF alterations in this model. Here we investigated the ability of diffusion MRI (dMRI) to detect abnormalities in BF microstructure for the 3xTg-AD mouse model, along with related pathology in the hippocampus (HP) and white matter (WM) tracks comprising the septo-hippocampal pathway. 3xTg-AD and normal control (NC) mice were imaged in vivo using the specific dMRI technique known as diffusional kurtosis imaging (DKI) at 2, 8, and 15 months of age, and 8 dMRI parameters were measured at each time point. Our results revealed significant lower dMRI values in the BF of 2 months-old 3xTg-AD mice compared with NC mice, most likely related to the increased number of ChAT neurons seen in this AD mouse model at this age. They also showed significant age-related dMRI changes in the BF of both groups between 2 and 8 months of age, mainly a decrease in fractional anisotropy and axial diffusivity, and an increase in radial kurtosis. These dMRI changes in the BF may be reflecting the complex aging and pathological microstructural changes described in this region. Group differences and age-related changes were also observed in the HP, fimbria (Fi) and fornix (Fx). In the HP, diffusivity values were significantly higher in the 2 months-old 3xTg-AD mice, and the HP of NC mice showed a significant increase in axial kurtosis after 8 months, reflecting a normal pattern of increased fiber density complexity, which was not seen in the 3xTg-AD mice. In the Fi, mean and radial diffusivity values were significantly higher, and fractional anisotropy, radial kurtosis and kurtosis fractional anisotropy were significantly lower in the 2 months-old 3xTg-AD mice. The age trajectories for both NC and TG mice in the Fi and Fx were similar between 2 and 8 months, but after 8 months there was a significant decrease in diffusivity metrics associated with an increase in kurtosis metrics in the 3xTg-AD mice. These later HP, Fi and Fx dMRI changes probably reflect the growing number of dystrophic neurites and AD pathology progression in the HP, accompanied by WM disruption in the septo-hippocampal pathway. Our results demonstrate that dMRI can detect early cytoarchitectural abnormalities in the BF, as well as related aging and neurodegenerative changes in the HP, Fi and Fx of the 3xTg-AD mice. Since DKI is widely available on clinical scanners, these results also support the potential of the considered dMRI parameters as in vivo biomarkers for AD disease progression.

White matter variability in auditory callosal pathways contributes to variation in the cultural transmission of auditory symbolic systems.

The cultural transmission of spoken language and music relies on human capacities for encoding and recalling auditory patterns. In this experiment, we show that interindividual differences in this ability are associated with variation in the organization of cross-callosal white matter pathways. First, high-angular resolution diffusion MRI (dMRI) data were analyzed in a large participant sample (N = 51). Subsequently, these participants underwent a behavioral test that models in the laboratory the cultural transmission of auditory symbolic systems: the signaling game. Cross-callosal and intrahemispheric (arcuate fasciculus) pathways were reconstructed and analyzed using conventional diffusion tensor imaging (DTI) as well as a more advanced dMRI technique: fixel-based analysis (FBA). The DTI metric of fractional anisotropy (FA) in auditory callosal pathways predicted-weeks after scanning-the fidelity of transmission of an artificial tone system. The ability to coherently transmit auditory signals in one signaling game, irrespective of the signals learned during the previous game, was predicted by morphological properties of the fiber bundles in the most anterior portions of the corpus callosum. The current study is the first application of dMRI in the field of cultural transmission, and the first to connect individual characteristics of callosal pathways to core behaviors in the transmission of auditory symbolic systems.

In vivo human whole-brain Connectom diffusion MRI dataset at 760\u2009\xb5m isotropic resolution

We present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

Ultra-high resolution and multi-shell diffusion MRI of intact ex vivo human brains using kT-dSTEAM at 9.4T

Diffusion MRI (dMRI) in ex vivo human brain specimens is an important research tool for neuroanatomical investigations and the validation of dMRI techniques. Many ex vivo dMRI applications have benefited from very high dMRI resolutions achievable on small-bore preclinical or animal MRI scanners for small tissue samples. However, the investigation of entire human brains post mortem provides the important context of entire white matter (WM) network systems and entire gray matter (GM) areas connected through these systems. The investigation of intact ex vivo human brains in large bore systems creates challenges due to the limited gradient performance and transmit radio-frequency (B1+) inhomogeneities, specially at ultra-high field (UHF, 7T and higher). To overcome these issues, it is necessary to tailor ex vivo diffusion-weighted sequences specifically for high resolution and high diffusion-weighting. Here, we present kT-dSTEAM, which achieves B1+ homogenization across whole human brain specimens using parallel transmit (pTx) on a 9.4T MR system. We use kT-dSTEAM to obtain multi-shell high b-value and high resolution diffusion-weighted data in ex vivo whole human brains. Isotropic whole brain data can be acquired at high b-value (6000–8000 s/mm2) at high resolution (1000 μm) and at moderate b-value (3000 s/mm2) at ultra-high isotropic resolution (400 μm). As an illustration of the advantages of the ultra-high resolution, tractography across the WM/GM border shows less of the unwanted gyral crown bias, and more high-curvature paths connecting the sulcal wall than at lower resolution. The kT-dSTEAM also allows for acquisition of T1 and T2 weighted images suitable for estimating quantitative T1 and T2 maps. Finally, multi-shell analysis of kT-dSTEAM data at variable mixing time (TM) is shown as an approach for ex vivo data analysis which is adapted to the strengths of STEAM diffusion-weighting. Here, we use this gain for multi-orientation modelling and crossing-fiber tractography. We show that multi-shell data allows superior multiple orientation tractography of known crossing fiber structures in the brain stem.

Microstructural characterization of corticospinal tract in subacute and chronic stroke patients with distal lesions by means of advanced diffusion MRI

PurposeThe aim of the paper is to evaluate if advanced dMRI techniques, including diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI), could provide novel insights into the subtle microarchitectural modifications occurring in the corticospinal tract (CST) of stroke patients in subacute and chronic phases.MethodsSeventeen subjects (age 68 ± 11 years) in the subacute phase (14 ± 3 days post-stroke), 10 of whom rescanned in the chronic phase (231 ± 36 days post-stroke), were enrolled. Images were acquired using a 3-T MRI scanner with a two-shell EPI protocol (20 gradient directions, b = 700 s/mm2, 3 b = 0; 64 gradient directions, b = 2000 s/mm2, 9 b = 0). DTI-, DKI-, and NODDI-derived parameters were calculated in the posterior limb of the internal capsule (PLIC) and in the cerebral peduncle (CP).ResultsIn the subacute phase, a reduction of FA, AD, and KA values was correlated with an increase of ODI, RD, and AK parameters, in both the ipsilesional PLIC and CP, suggesting that increased fiber dispersion can be the main structural factor. In the chronic phase, a reduction of FA and an increase of ODI persisted in the ipsilesional areas. This was associated with reduced Fic and increased MD, with a concomitant reduction of MK and increase of RD, suggesting that fiber reduction, possibly due to nerve degeneration, could play an important role.ConclusionsThis study shows that advanced dMRI approaches can help elucidate the underpinning architectural modifications occurring in the CST after stroke. Further follow-up studies on bigger cohorts are needed to evaluate if DKI- and NODDI-derived parameters might be proposed as complementary biomarkers of brain microstructural alterations.

The use of diffusional kurtosis imaging and neurite orientation dispersion and density imaging of the brain in bipolar disorder

BackgroundDiffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) are new diffusional magnetic resonance imaging (dMRI) techniques to clarify the characterization of neural tissues in the human brain. In this study, we evaluated the structural changes of the cerebrum in patients with bipolar disorder (BD) by these dMRI techniques. MethodsThirty-one Japanese patients with BD (male/female: 14/17; 29 out of 31 patients were right-handed; mean age: 39.5 ± 9.3) and 28 healthy, right-handed Japanese subjects underwent 3-Tesla dMRI. We compared the dMRI metrics between the 2 groups and examined the relationships among the metrics. LimitationThe majority of the participants in this study were medicated with antidepressants and antipsychotics. Further studies with drug-free participants will be needed before any conclusions can be drawn regarding microstructural changes in BD. ResultsThe BD patients showed significantly reduced mean kurtosis in right inferior front-occipital fasciculus and right posterior cingulate cortex (PCC), and neurite density indices in the right -PCC, compared with the controls. As for the orientation dispersion index, we detected significant decrease in the left hippocampal region of BD patients. ConclusionsUsing the new dMRI techniques, we observed disease-related alterations in the inferior front-occipital fasciculus, PCC, and hippocampal regions which play important roles in BD. These results may indicate that NODDI and DKI are useful to detect changes in the microstructural tissue organization in BD. It is anticipated that these techniques will be adopted as the mainstream methods for neuroimaging study.

Multiple Approaches to Diffusion Magnetic Resonance Imaging in Hereditary Cerebral Amyloid Angiopathy Mutation Carriers.

BackgroundCerebral amyloid angiopathy (CAA) is a major cause of lobar intracerebral hemorrhage in elderly adults; however, presymptomatic diagnosis of CAA is difficult. Hereditary cerebral hemorrhage with amyloidosis–Dutch type (HCHWA‐D) is a rare autosomal‐dominant disease that leads to pathology similar to sporadic CAA. Presymptomatic HCHWA‐D mutation carriers provide a unique opportunity to study CAA‐related changes before any symptoms have occurred. In this study we investigated early CAA‐related alterations in the white matter.Methods and ResultsWe investigated diffusion magnetic resonance imaging (dMRI) data for 15 symptomatic and 11 presymptomatic HCHWA‐D mutation carriers and 30 noncarrier control participants using 4 different approaches. We looked at (1) the relation between age and global dMRI measures for mutation carriers versus controls, (2) voxel‐wise dMRI, (3) independent component‐clustered dMRI measures, and (4) structural connectomics between presymptomatic or symptomatic carriers and controls. Fractional anisotropy decreased, and mean diffusivity and peak width of the skeletonized mean diffusivity increased significantly over age for mutation carriers compared with controls. In addition, voxel‐wise and independent component‐wise fractional anisotropy, and mean diffusivity, and structural connectomics were significantly different between HCHWA‐D patients and control participants, mainly in the periventricular frontal and occipital regions and in the occipital lobe. We found no significant differences between presymptomatic carriers and control participants.ConclusionsThe dMRI technique is sensitive in detecting alterations in symptomatic HCHWA‐d carriers but did not show alterations in presymptomatic carriers. This result indicates that dMRI may be less suitable for identifying early white matter changes in CAA.

Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances.

This review discusses ex vivo diffusion magnetic resonance imaging (dMRI) as an important research tool for neuroanatomical investigations and the validation of in vivo dMRI techniques, with a focus on the human brain. We review the challenges posed by the properties of post‐mortem tissue, and discuss state‐of‐the‐art tissue preparation methods and recent advances in pulse sequences and acquisition techniques to tackle these. We then review recent ex vivo dMRI studies of the human brain, highlighting the validation of white matter orientation estimates and the atlasing and mapping of large subcortical structures. We also give particular emphasis to the delineation of layered gray matter structure with ex vivo dMRI, as this application illustrates the strength of its mesoscale resolution over large fields of view. We end with a discussion and outlook on future and potential directions of the field.

The use of diffusional kurtosis imaging and neurite orientation dispersion and density imaging of the brain in major depressive disorder

Diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) are new diffusional magnetic resonance imaging (dMRI) techniques for the characterization of neural tissues in human brain. In this study, we used these dMRI techniques to evaluate the whole-brain microstructural changes in patients with major depressive disorder (MDD). Twenty-three patients with MDD and 26 healthy subjects underwent dMRI. We compared the dMRI metrics between the 2 groups and examined the relationships between the metrics and the clinical symptoms of MDD. The MDD patients showed significant fractional anisotropy reduction in the bilateral parietal, right parieto-occipital, and right superior temporal corti, compared with the controls. Mean kurtosis values were significantly reduced in MDD patients in the right superior temporal cortex and bilateral posterior thalamic radiation. Neurite density index reductions were found in the right superior temporal cortex, bilateral insulae, right inferior frontal cortex, left parahippocampal region, left middle cerebellar peduncle, and right cerebellum. Regarding the orientation dispersion index (ODI), we detected significant decreases in the left thalamus and left occipital cortex, and significant increases in the bilateral superior longitudinal fasciculi and left posterior thalamic radiation tract. Further, there were significant positive correlations between the total Hamilton Depression Rating scale-21 scores and the ODI values in the right frontal gyri. These results suggest that the DKI and NODDI methods may provide more information about microstructural abnormalities in patients with MDD than the DTI method. It is thus expected that these techniques will be adopted as the informative methods for neuroimaging study.

Quantifying musculoskeletal motion using dynamic MRI techniques: A systematic review of validity and perspectives for musculoskeletal disorder evaluation

This systematic review reports the evidence of validity and reliability of dynamic MRI (dMRI) techniques in quantifying in vivo skeletal joint movement (kinematics) or muscle tracking and to propose recommendations of use for the assessment of normal and impaired musculoskeletal function. A systematic search was conducted on six bibliographic databases (Web of science, PubMed, Scopus, Academic search Premier, Pascal, and Cochrane Library) for articles published between 1990 and January 2017. Prospective studies that reported the concurrent validity and/or reliability of determining in vivo skeletal joint or muscle motion using dMRI techniques were included after assessment by two independent reviewers for inclusion and exclusion criteria. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Concurrent validity and reliability measurement results were categorized as poor, moderate, or excellent for this review. Bibliographic search identified 20 articles that met the inclusion and exclusion criteria. The mean quality assessment score for all the selected articles was 66% (±10.4). Concurrent validity and/or reliability of eight dMRI techniques evaluating the musculoskeletal motion were reported. Selected studies spanned various joints and muscles with knee joint being the most evaluated joint (seven studies), followed by ankle and temporomandibular joint (two studies each). Moderate to excellent concurrent validity and reliability were reported for most of the dMRI techniques. Based on the current level of metrological evidence Cine Phase-Contrast and Real-time MRI techniques stand out for determining skeletal joint motion whereas Spin tag MRI technique stands out for determining muscle motion. dMRI techniques can be effectively applied to understand in vivo skeletal joint and muscle movement mechanics for both healthy and pathological populations. However, caution must be exercised as the evidence of validity and reliability of using these techniques in all the skeletal joints and muscles have not been systematically evaluated. Furthermore, clinical utility of the techniques in impaired population is not addressed yet in terms of concurrent validity and reliability measures setting up a good research direction for future studies. Examples of the best available techniques and outcomes for rehabilitation application will be provided during the presentation.

Diffusion MRI and the detection of alterations following traumatic brain injury.

This article provides a review of brain tissue alterations that may be detectable using diffusion magnetic resonance imaging MRI (dMRI) approaches and an overview and perspective on the modern dMRI toolkits for characterizing alterations that follow traumatic brain injury (TBI). Noninvasive imaging is a cornerstone of clinical treatment of TBI and has become increasingly used for preclinical and basic research studies. In particular, quantitative MRI methods have the potential to distinguish and evaluate the complex collection of neurobiological responses to TBI arising from pathology, neuroprotection, and recovery. dMRI provides unique information about the physical environment in tissue and can be used to probe physiological, architectural, and microstructural features. Although well‐established approaches such as diffusion tensor imaging are known to be highly sensitive to changes in the tissue environment, more advanced dMRI techniques have been developed that may offer increased specificity or new information for describing abnormalities. These tools are promising, but incompletely understood in the context of TBI. Furthermore, model dependencies and relative limitations may impact the implementation of these approaches and the interpretation of abnormalities in their metrics. The objective of this paper is to present a basic review and comparison across dMRI methods as they pertain to the detection of the most commonly observed tissue and cellular alterations following TBI.

APPLICATION OF A NOVEL QUANTITATIVE TRACTOGRAPHY-BASED ANALYSIS OF DIFFUSION TENSOR IMAGING TO EXAMINE FIBER BUNDLE LENGTH IN HUMAN CEREBRAL WHITE MATTER.

This paper reviews basic methods and recent applications of length-based fiber bundle analysis of cerebral white matter using diffusion magnetic resonance imaging (dMRI). Diffusion weighted imaging (DWI) is a dMRI technique that uses the random motion of water to probe tissue microstructure in the brain. Diffusion tensor imaging (DTI) is an extension of DWI that measures the magnitude and direction of water diffusion in cerebral white matter, using either voxel-based scalar metrics or tractography-based analyses. More recently, quantitative tractography based on diffusion tensor imaging (qtDTI) technology has been developed to help quantify aggregate structural anatomical properties of white matter fiber bundles, including both scalar metrics of bundle diffusion and more complex morphometric properties, such as fiber bundle length (FBL). Unlike traditional scalar diffusion metrics, FBL reflects the direction and curvature of white matter pathways coursing through the brain and is sensitive to changes within the entire tractography model. In this paper, we discuss applications of this approach to date that have provided new insights into brain organization and function. We also discuss opportunities for improving the methodology through more complex anatomical models and potential areas of new application for qtDTI.