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Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para-arterial spaces, interstitial spaces, and para-venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion-based imaging, especially when differentiating between tissue- and fluid-related changes or elucidating structural versus functional alterations., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Cerebrospinal fluid (CSF) in the paravascular spaces of the surface arteries (sPVS) is a vital pathway in brain waste clearance. Arterial pulsations may be the driving force of the paravascular flow, but its pulsatile pattern remains poorly characterized, and no clinically practical method for measuring its dynamics in the human brain is available. In this work, we introduce an imaging and quantification framework for in-vivo non-invasive assessment of pulsatile fluid dynamics in the sPVS. It used dynamic Diffusion-Weighted Imaging (dDWI) at a lower b-values of 150s/mm 2 and retrospective gating to detect the slow flow of CSF while suppressing the fast flow of adjacent arterial blood. The waveform of CSF flow over a cardiac cycle was revealed by synchronizing the measurements with the heartbeat. A data-driven approach was developed to identify sPVS and allow automatic quantification of the whole-brain fluid waveforms. We applied dDWI to twenty-five participants aged 18-82 y/o. Results demonstrated that the fluid waveforms across the brain showed an explicit cardiac-cycle dependency, in good agreement with the vascular pumping hypothesis. Furthermore, the shape of the CSF waveforms closely resembled the pressure waveforms of the artery wall, suggesting that CSF dynamics is tightly related to artery wall mechanics. Finally, the CSF waveforms in aging participants revealed a strong age effect, with a significantly wider systolic peak observed in the older relative to younger participants. The peak widening may be associated with compromised vascular compliance and vessel wall stiffening in the older brain. Overall, the results demonstrate the feasibility, reproducibility, and sensitivity of dDWI for detecting sPVS fluid dynamics of the human brain. Our preliminary data suggest age-related alterations of the paravascular pumping. With an acquisition time of under six minutes, dDWI can be readily applied to study fluid dynamics in normal physiological conditions and cerebrovascular/neurodegenerative diseases., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r 2 = 0.92, P = 1.9 × 10 -9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI., (© 2020 John Wiley & Sons, Ltd.)

Purpose: Golden-angle single-shot PROPLLER (GA-SS-PROP) is proposed to accelerate the PROPELLER acquisition for distortion-free diffusion-weighted (DW) imaging. Acceleration is achieved by acquiring one-shot per b-value and several b-values can be acquired along a diffusion direction, where the DW signal follows a bi-exponential decay (i.e. IVIM). Sparse reconstruction is used to reconstruct full resolution DW images. Consequently, apparent diffusion coefficient (ADC) map and IVIM maps (i.e., perfusion fraction (f) and the perfusion-free diffusion coefficient (D)) are obtained simultaneously. The performance of GA-SS-PROP was demonstrated with simulation and human experiments., Methods: A realistic numerical phantom of high-quality diffusion images of the brain was developed. The error of the reconstructed DW images and quantitative maps were compared to the ground truth. The pulse sequence was developed to acquire human brain data. For comparison, fully sampled PROPELLER and conventional single-shot echo planar imaging (SS-EPI) acquisitions were performed., Results: GA-SS-PROP was 5 times faster than conventional PROPELLER acquisition with comparable image quality. The simulation demonstrated that sparse reconstruction is effective in restoring contrast and resolution. The human experiments demonstrated that GA-SS-PROP achieved superior image fidelity compared to SS-EPI for the same acquisition time and same in-plane resolution (1 × 1 mm 2 )., Conclusion: GA-SS-PROP offers fast, high-resolution and distortion-free DW images. The generated quantitative maps (f, D and ADC) can provide valuable information on tissue perfusion and diffusion properties simultaneously, which are desirable in many applications, especially in oncology. As a turbo spin-echo based technique, it can be applied in most challenging regions where SS-EPI is problematic., (Copyright © 2020. Published by Elsevier Inc.)

Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white matter alterations in 19 patients with mTBI and 23 other trauma control patients. Within 15 days (standard deviation = 10) of brain injury, all subjects underwent magnetic resonance HYDI and were assessed with a battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) was used for voxel-wise statistical analyses within the white matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between-group interaction effects. The advanced diffusion imaging techniques, including neurite orientation dispersion and density imaging (NODDI) and q-space analyses, appeared to be more sensitive then classic diffusion tensor imaging. Only NODDI-derived intra-axonal volume fraction (V ic ) demonstrated significant group differences (i.e., 5-9% lower in the injured brain). Within the mTBI group, V ic and a q-space measure, P 0 , correlated with 6 of 10 neuropsychological tests, including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between groups (R 2  > 0.71 and p interation < 0.03). Specifically, in the control group, higher V ic and P 0 were associated with better performances on clinical assessments, whereas in the mTBI group, higher V ic and P 0 were associated with worse performances with correlation coefficients >0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.

Neurite orientation dispersion and density imaging (NODDI), a MRI multi-shell diffusion technique, has offered new insights for the study of microstructural changes in neurodegenerative diseases. Mainly, the present study aimed to determine the connection between NODDI-derived parameters and changes in white matter (WM) abnormalities at early stages of amyotrophic lateral sclerosis (ALS). Spinal cords from ALS mice (G93A-SOD1 mice) were scanned in a Bruker Avance III HD 17.6T magnet. Fluorescent axonal-tagged mice (YFP, G93A-SOD1 mice) were used for quantitative histological analysis. NODDI showed a decrease in intra-cellular volume fraction (-24%) and increases in orientation dispersion index (+35%) and isotropic volume fraction (+33%). In addition, histoathological results demonstrated a reductions in axonal area (-11%) and myelin content (-29%). A histological decrease in WM intra-axonal space (-71%) and an increase in the extra-axonal compartment (+22%) were also detected. Our studies demonstrate that NODDI may be a suitable technique for detecting presymptomatic spinal cord WM microstructural degeneration in ALS.

Purpose: To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments., Methods: A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions., Results: The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm 2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion., Conclusion: RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

3D q-space can be viewed as the surface of a 4D hypersphere. In this paper, we seek to develop a 4D hyperspherical interpretation of q-space by projecting it onto a hypersphere and subsequently modeling the q-space signal via 4D hyperspherical harmonics (HSH). Using this orthonormal basis, we analytically derive several quantitative indices and numerically estimate the diffusion ODF. Importantly, we derive the integral transform describing the relationship between the diffusion signal and propagator on a hypersphere. We also show that the HSH basis expends less fitting parameters than other well-established methods to achieve comparable signal and better ODF reconstructions. All in all, this work provides a new way of looking at q-space.

The ensemble average propagator (EAP) describes the 3D average diffusion process of water molecules, capturing both its radial and angular contents. The EAP can thus provide richer information about complex tissue microstructure properties than the orientation distribution function (ODF), an angular feature of the EAP. Recently, several analytical EAP reconstruction schemes for multiple q-shell acquisitions have been proposed, such as diffusion propagator imaging (DPI) and spherical polar Fourier imaging (SPFI). In this study, a new analytical EAP reconstruction method is proposed, called Bessel Fourier Orientation Reconstruction (BFOR), whose solution is based on heat equation estimation of the diffusion signal for each shell acquisition, and is validated on both synthetic and real datasets. A significant portion of the paper is dedicated to comparing BFOR, SPFI, and DPI using hybrid, non-Cartesian sampling for multiple b-value acquisitions. Ways to mitigate the effects of Gibbs ringing on EAP reconstruction are also explored. In addition to analytical EAP reconstruction, the aforementioned modeling bases can be used to obtain rotationally invariant q-space indices of potential clinical value, an avenue which has not yet been thoroughly explored. Three such measures are computed: zero-displacement probability (Po), mean squared displacement (MSD), and generalized fractional anisotropy (GFA)., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The ensemble average propagator (EAP) describes the 3D average diffusion process of water molecules, capturing both its radial and angular contents, and hence providing rich information about complex tissue microstructure properties. Bessel Fourier orientation reconstruction (BFOR) is one of several analytical, non-Cartesian EAP reconstruction schemes employing multiple shell acquisitions that have recently been proposed. Such modeling bases have not yet been fully exploited in the extraction of rotationally invariant q-space indices that describe the degree of diffusion anisotropy/restrictivity. Such quantitative measures include the zero-displacement probability (P(o)), mean squared displacement (MSD), q-space inverse variance (QIV), and generalized fractional anisotropy (GFA), and all are simply scalar features of the EAP. In this study, a general relationship between MSD and q-space diffusion signal is derived and an EAP-based definition of GFA is introduced. A significant part of the paper is dedicated to utilizing BFOR in a clinical dataset, comprised of 5 multiple sclerosis (MS) patients and 4 healthy controls, to estimate P(o), MSD, QIV, and GFA of corpus callosum, and specifically, to see if such indices can detect changes between normal appearing white matter (NAWM) and healthy white matter (WM). Although the sample size is small, this study is a proof of concept that can be extended to larger sample sizes in the future.

Diffusion tensor imaging has been widely used to study brain diseases, disorders, development, and aging. However, few studies have explored the effects of aging on diffusion imaging measures with higher b values. Further, the water diffusion in biological tissues appears biexponential, although this also has not been explored with aging. In this study, hybrid diffusion imaging (HYDI) was used to study 52 healthy subjects with an age range from 18 to 72 years. The HYDI diffusion-encoding scheme consisted of five concentric q-space shells with b values ranging from 0 to 9375 s/mm(2). Quantitative diffusion measures were investigated as a function of age and gender using both region-of-interest (whole-brain white matter, genu and splenium of corpus callosum, posterior limb of the internal capsule) and whole-brain voxel-based analyses. Diffusion measures included measures of the diffusion probability density function (zero displacement probability and mean-squared displacement), biexponential diffusion (i.e., volume fractions of fast/slow diffusion compartments and fast/slow diffusivities), and DTI measures (fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity). The biexponential volume fraction, the fast diffusivity, and the axial diffusivity measures (f(1), D(1), and D(a)) were found to be more sensitive to normal aging than the restricted, slow and radial diffusion measures (P(0), D(2), and D(r)). The biexponential volume fraction, f(1), showed the most widespread age dependence in the voxel-based analyses, although both FA and mean diffusivity did show changes in frontal white matter regions that may be associated with age-related decline., (Copyright © 2010 Elsevier Inc. All rights reserved.)

The estimation of the ensemble average propagator (EAP) directly from q-space DWI signals is an open problem in diffusion MRI. Diffusion spectrum imaging (DSI) is one common technique to compute the EAP directly from the diffusion signal, but it is burdened by the large sampling required. Recently, several analytical EAP reconstruction schemes for multiple q-shell acquisitions have been proposed. One, in particular, is Diffusion Propagator Imaging (DPI) which is based on the Laplace's equation estimation of diffusion signal for each shell acquisition. Viewed intuitively in terms of the heat equation, the DPI solution is obtained when the heat distribution between temperatuere measurements at each shell is at steady state. We propose a generalized extension of DPI, Bessel Fourier Orientation Reconstruction (BFOR), whose solution is based on heat equation estimation of the diffusion signal for each shell acquisition. That is, the heat distribution between shell measurements is no longer at steady state. In addition to being analytical, the BFOR solution also includes an intrinsic exponential smootheing term. We illustrate the effectiveness of the proposed method by showing results on both synthetic and real MR datasets.

The distribution of water diffusion in biological tissues may be estimated by a 3-D Fourier transform (FT) of diffusion-weighted measurements in q-space. In this study, methods for estimating diffusion spectrum measures (the zero-displacement probability, the mean-squared displacement, and the orientation distribution function) directly from the q-space signals are described. These methods were evaluated using both computer simulations and hybrid diffusion imaging (HYDI) measurements on a human brain. The HYDI method obtains diffusion-weighted measurements on concentric spheres in q-space. Monte Carlo computer simulations were performed to investigate effects of noise, q-space truncation, and sampling interval on the measures. This new direct computation approach reduces HYDI data processing time and image artifacts arising from 3-D FT and regridding interpolation. In addition, it is less sensitive to the noise and q-space truncation effects than conventional approach. Although this study focused on data using the HYDI scheme, this computation approach may be applied to other diffusion sampling schemes including Cartesian diffusion spectrum imaging.

Objective: To calibrate and correct the gradient errors including gradient amplitude scaling errors, background/imaging gradients, and residual gradients in diffusion tensor imaging (DTI)., Methods: A calibration protocol using an isotropic phantom was proposed. Gradient errors were estimated by using linear regression analyses on quadratic functions of diffusion gradients along 3 orthogonal directions. A 6-element total effective scaling vector is generated from the calibration protocol to retrospectively correct gradient errors in DTI experiments., Results: The accuracy of the calibration protocol was within 1% or less in estimating gradient scaling errors. On both the brain study and the computer simulations, the retrospective correction minimized undesirable estimate biases of DTI measurements due to gradient errors., Conclusion: The protocol and retrospective correction are shown to be effective. The method may be used for prospective correction if actual diffusion-gradient waveforms are available. The methodology is expandable to general diffusion imaging schemes.

Diffusion measurements in the human central nervous system are complex to characterize and a broad spectrum of methods have been proposed. In this study, a comprehensive diffusion encoding and analysis approach, hybrid diffusion imaging (HYDI), is described. The HYDI encoding scheme is composed of multiple concentric "shells" of constant diffusion weighting, which may be used to characterize the signal behavior with low, moderate and high diffusion weighting. HYDI facilitates the application of multiple data analyses strategies including diffusion tensor imaging (DTI), multi-exponential diffusion measurements, diffusion spectrum imaging (DSI) and q-ball imaging (QBI). These different analysis strategies may provide complementary information. DTI measures (mean diffusivity and fractional anisotropy) may be estimated from either data in the inner shells or the entire HYDI data. Fast and slow diffusivities were estimated using a nonlinear least squares bi-exponential fit on geometric means of the HYDI shells. DSI measurements from the entire HYDI data yield empirical model-independent diffusion information and are well-suited for characterizing tissue regions with complex diffusion behavior. DSI measurements were characterized using the zero displacement probability and the mean-squared displacement. The outermost HYDI shell was analyzed using QBI analysis to estimate the orientation distribution function (ODF), which is useful for characterizing the directions of multiple fiber groups within a voxel. In this study, an HYDI encoding scheme with 102 diffusion-weighted measurements was obtained over most of the human cerebrum in under 30 min.

The diffusion properties of biological tissues are independent of magnetic field strength. Field strength, however, does affect the signal-to-noise ratio (SNR) and artifacts of diffusion-weighted (DW) images, which ultimately will influence the quantitative and spatial accuracy of diffusion tensor imaging (DTI). In this article, the effects of field strength on DTI are reviewed. The effects of parallel imaging also are discussed. A small study comparing DTI measurements both as a function of field strength (1.5 T and 3.0 T) and parallel imaging was performed. Overall, the SNR of the DW images roughly doubled going from 1.5 T to 3.0 T, and there was a relatively small decrease in SNR (15% to 30%) when parallel imaging was used. The increased SNR at 3.0 T resulted in smaller variances in the estimated mean diffusivities and fractional anisotropies. As expected, the amount of echo-planar image distortion roughly doubled going from 1.5 T to 3.0 T, but was reduced by 50% when using parallel imaging. In summary, DTI studies at 3.0 T using parallel imaging will provide significantly improved DTI measurements relative to studies at 1.5 T.

Hybrid diffusion imaging (HYDI) is a new diffusion MRI method for characterizing complex diffusion. Diffusion-weighted measurements are obtained on multiple 'shells' of constant diffusion weighting. This diffusion encoding approach is amenable to multiple types of diffusion imaging analysis. The inner shells may be used to estimate the diffusion tensor and generate maps of the diffusion anisotropy and mean diffusivity. The outer shell, which has high angular resolution, may be used to estimate the distribution of white matter fiber tracts in a voxel. Finally, all of the data may be used to estimate the diffusion displacement spectrum for characterizing the full diffusion behavior in a voxel. HYDI experiments were performed on the brains of healthy volunteers and the results are presented. Overall, HYDI is an efficient and promising method for characterizing complex diffusion in the human brain and potentially other tissues.

The ability of diffusion tensor imaging (DTI) to probe the ultrastructural properties of biological tissues presents new possibilities for DTI-based tissue characterization, with the potential for greater pathologic specificity than conventional imaging methods. This is urgently needed in the diagnosis and treatment of cerebral neoplasms, where clinical decisions depend on the ability to discriminate tumor-involved from uninvolved tissue, a major shortcoming of conventional imaging. Several investigators have attempted to make this determination on the basis of the apparent diffusion coefficient (ADC) or the fractional anisotropy (FA), with mixed results. The directionally encoded color map, with hues reflecting tensor orientation and intensity weighted by FA, provides an aesthetic and informative summary of DTI features throughout the brain in an easily interpreted format. The use of these maps is becoming increasingly common in both basic and clinical research, as well as in purely clinical settings. These examples serve to demonstrate our approach to the quantitation of regional diffusion tensor distributions using directional statistical methods.

Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing., ((c) 2004 Wiley-Liss, Inc.)

Purpose: To categorize the varied appearances of tumor-altered white matter (WM) tracts on diffusion tensor eigenvector directional color maps., Materials and Methods: Diffusion tensor imaging (DTI) was obtained preoperatively in 13 patients with brain tumors ranging from benign to high-grade malignant, including primary and metastatic lesions, and maps of apparent diffusion coefficient (ADC), fractional anisotropy (FA), and major eigenvector direction were generated. Regions of interest (ROIs) were drawn within identifiable WM tracts affected by tumor, avoiding grossly cystic and necrotic regions, known fiber crossings, and gray matter. Patterns of WM tract alteration were categorized on the basis of qualitative analysis of directional color maps and correlation analysis of ADC and FA., Results: Four basic patterns of WM alteration were identified: 1) normal or nearly normal FA and ADC, with abnormal tract location or tensor directions attributable to bulk mass displacement, 2) moderately decreased FA and increased ADC with normal tract locations and tensor directions, 3) moderately decreased FA and increased ADC with abnormal tensor directions, and 4) near isotropy. FA and ADC were inversely correlated for Patterns 1-3 but did not discriminate edema from infiltrating tumor. However, in the absence of mass displacement, infiltrating tumor was found to produce tensor directional changes that were not observed with vasogenic edema, suggesting the possibility of discrimination on the basis of directional statistics., Conclusion: Tumor alteration of WM tracts tends to produce one of four patterns on FA and directional color maps. Clinical application of these patterns must await further study., (Copyright 2004 Wiley-Liss, Inc.)

Background: Cardiac pulsation propels blood through the cerebrovascular network to maintain cerebral homeostasis. The cerebrovascular network is uniquely surrounded by paravascular cerebrospinal fluid (pCSF), which plays a crucial role in waste removal, and its flow is suspected to be driven by arterial pulsations. Despite its importance, the relationship between vascular and paravascular fluid dynamics throughout the cardiac cycle remains poorly understood in humans. Methods: In this study, we developed a non-invasive neuroimaging approach to investigate the coupling between pulsatile vascular and pCSF dynamics within the subarachnoid space of the human brain. Resting-state functional MRI (fMRI) and dynamic diffusion-weighted imaging (dynDWI) were retrospectively cardiac-aligned to represent cerebral hemodynamics and pCSF motion, respectively. We measured the time between peaks (∆TTP) in d d ϕ f M R I and dynDWI waveforms and measured their coupling by calculating the waveforms correlation after peak alignment (correlation at aligned peaks). We compared the ∆TTP and correlation at aligned peaks between younger [mean age: 27.9 (3.3) years, n = 9] and older adults [mean age: 70.5 (6.6) years, n = 20], and assessed their reproducibility within subjects and across different imaging protocols. Results: Hemodynamic changes consistently precede pCSF motion. ∆TTP was significantly shorter in younger adults compared to older adults (−0.015 vs. −0.069, p < 0.05). The correlation at aligned peaks were high and did not differ between younger and older adults (0.833 vs. 0.776, p = 0.153). The ∆TTP and correlation at aligned peaks were robust across fMRI protocols (∆TTP: −0.15 vs. −0.053, p = 0.239; correlation at aligned peaks: 0.813 vs. 0.812, p = 0.985) and demonstrated good to excellent within-subject reproducibility (∆TTP: intraclass correlation coefficient = 0.36; correlation at aligned peaks: intraclass correlation coefficient = 0.89). Conclusion: This study proposes a non-invasive technique to evaluate vascular and paravascular fluid dynamics. Our findings reveal a consistent and robust cardiac pulsation-driven coupling between cerebral hemodynamics and pCSF dynamics in both younger and older adults. [ABSTRACT FROM AUTHOR]

Paravascular cerebrospinal fluid (pCSF) surrounding the cerebral arteries within the glymphatic system is pulsatile and moves in synchrony with the pressure waves of the vessel wall. Whether such pulsatile pCSF can infer pulse wave propagation—a property tightly related to arterial stiffness—is unknown and has never been explored. Our recently developed imaging technique, dynamic diffusion‐weighted imaging (dynDWI), captures the pulsatile pCSF dynamics in vivo and can explore this question. In this work, we evaluated the time shifts between pCSF waves and finger pulse waves, where pCSF waves were measured by dynDWI and finger pulse waves were measured by the scanner's built‐in finger pulse oximeter. We hypothesized that the time shifts reflect brain‐finger pulse wave travel time and are sensitive to arterial stiffness. We applied the framework to 36 participants aged 18–82 years to study the age effect of travel time, as well as its associations with cognitive function within the older participants (N = 15, age > 60 years). Our results revealed a strong and consistent correlation between pCSF pulse and finger pulse (mean CorrCoeff = 0.66), supporting arterial pulsation as a major driver for pCSF dynamics. The time delay between pCSF and finger pulses (TimeDelay) was significantly lower (i.e., faster pulse propagation) with advanced age (Pearson's r = −0.44, p = 0.007). Shorter TimeDelay was further associated with worse cognitive function in the older participants. Overall, our study demonstrated pCSF as a viable pathway for measuring intracranial pulses and encouraged future studies to investigate its relevance with cerebrovascular functions. A novel framework was proposed to measure the brain‐finger pulse wave propagation through imaging the paravascular fluid dynamics. The brain‐finger TimeDelay was found to be significantly associated with age and neurocognition. Our results suggest that paravascular fluid is a viable pathway for measuring intracranial pulse waves and inferring arterial stiffness. [ABSTRACT FROM AUTHOR]

Methadone-based treatment for pregnant women with opioid use disorder is quite prevalent in the clinical environment. A number of clinical and animal model-based studies have reported cognitive deficits in infants prenatally exposed to methadone-based opioid treatments. However, the long-term impact of prenatal opioid exposure (POE) on pathophysiological mechanisms that govern neurodevelopmental impairment is not well understood. Using a translationally relevant mouse model of prenatal methadone exposure (PME), the aim of this study is to investigate the role of cerebral biochemistry and its possible association with regional microstructural organization in PME offspring. To understand these effects, 8-week-old male offspring with PME (n = 7) and prenatal saline exposure (PSE) (n = 7) were scanned in vivo on 9.4 Tesla small animal scanner. Single voxel proton magnetic resonance spectroscopy (1H-MRS) was performed in the right dorsal striatum (RDS) region using a short echo time (TE) Stimulated Echo Acquisition Method (STEAM) sequence. Neurometabolite spectra from the RDS was first corrected for tissue T1 relaxation and then absolute quantification was performed using the unsuppressed water spectra. High-resolution in vivo diffusion MRI (dMRI) for region of interest (ROI) based microstructural quantification was also performed using a multi-shell dMRI sequence. Cerebral microstructure was characterized using diffusion tensor imaging (DTI) and Bingham-neurite orientation dispersion and density imaging (Bingham-NODDI). MRS results in the RDS showed significant decrease in N-acetyl aspartate (NAA), taurine (tau), glutathione (GSH), total creatine (tCr) and glutamate (Glu) concentration levels in PME, compared to PSE group. In the same RDS region, mean orientation dispersion index (ODI) and intracellular volume fraction (VFIC) demonstrated positive associations with tCr in PME group. ODI also exhibited significant positive association with Glu levels in PME offspring. Significant reduction in major neurotransmitter metabolites and energy metabolism along with strong association between the neurometabolites and perturbed regional microstructural complexity suggest a possible impaired neuroadaptation trajectory in PME offspring which could be persistent even into late adolescence and early adulthood. [ABSTRACT FROM AUTHOR]

Rationale: Little is known about how acute and chronic alcohol exposure may alter the in vivo membrane properties of neurons. Objectives: We employed neurite orientation dispersion and density imaging (NODDI) to examine acute and chronic effects of alcohol exposure on neurite density. Methods: Twenty-one healthy social drinkers (CON) and thirteen nontreatment-seeking individuals with alcohol use disorder (AUD) underwent a baseline multi-shell diffusion magnetic resonance imaging (dMRI) scan. A subset (10 CON, 5 AUD) received dMRI during intravenous infusions of saline and alcohol during dMRI. NODDI parametric images included orientation dispersion (OD), isotropic volume fraction (ISOVF), and corrected intracellular volume fraction (cICVF). Diffusion tensor imaging metrics of fractional anisotropy and mean, axial, and radial diffusivity (FA, MD, AD, RD) were also computed. Average parameter values were extracted from white matter (WM) tracts defined by the Johns Hopkins University atlas. Results: There were group differences in FA, RD, MD, OD, and cICVF, primarily in the corpus callosum. Both saline and alcohol had effects on AD and cICVF in WM tracts proximal to the striatum, cingulate, and thalamus. This is the first work to indicate that acute fluid infusions may alter WM properties, which are conventionally believed to be insensitive to acute pharmacological challenges. It also suggests that the NODDI approach may be sensitive to transient changes in WM. The next steps should include determining if the effect on neurite density differs with solute or osmolality, or both, and translational studies to assess how alcohol and osmolality affect the efficiency of neurotransmission. [ABSTRACT FROM AUTHOR]

Growing opioid use among pregnant women is fueling a crisis of infants born with prenatal opioid exposure. A large body of research has been devoted to studying the management of opioid withdrawal during the neonatal period in these infants, but less substantive work has explored the long-term impact of prenatal opioid exposure on neurodevelopment. Using a translationally relevant mouse model of prenatal methadone exposure (PME), the aim of the study is to investigate the cerebral microstructural differences between the mice with PME and prenatal saline exposure (PSE). The brains of eight-week-old male offspring with either PME (n = 15) or PSE (n = 15) were imaged using high resolution in-vivo diffusion magnetic resonance imaging on a 9.4 Tesla small animal scanner. Brain microstructure was characterized using diffusion tensor imaging (DTI) and Bingham neurite orientation dispersion and density imaging (Bingham-NODDI). Voxel-based analysis (VBA) was performed using the calculated microstructural parametric maps. The VBA showed significant (p < 0.05) bilateral alterations in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI) and dispersion anisotropy index (DAI) across several cortical and subcortical regions, compared to PSE. Particularly, in PME offspring, FA, MD and AD were significantly higher in the hippocampus, dorsal amygdala, thalamus, septal nuclei, dorsal striatum and nucleus accumbens. These DTI-based results suggest widespread bilateral microstructural alterations across cortical and subcortical regions in PME offspring. Consistent with the observations in DTI, Bingham-NODDI derived ODI exhibited significant reduction in PME offspring within the hippocampus, dorsal striatum and cortex. NODDI-based results further suggest reduction in dendritic arborization in PME offspring across multiple cortical and subcortical regions. To our best knowledge, this is the first study of prenatal opioid exposure to examine microstructural organization in vivo. Our findings demonstrate perturbed microstructural complexity in cortical and subcortical regions persisting into early adulthood which could interfere with critical neurodevelopmental processes in individuals with prenatal opioid exposure. [ABSTRACT FROM AUTHOR]

Hippocampal subfields exhibit differential vulnerabilities to Alzheimer's disease-associated pathology including abnormal accumulation of amyloid-β deposition and neurofibrillary tangles. These pathological processes extensively impact on the structural and functional interconnectivities of the subfields and may explain the association between hippocampal dysfunction and cognitive deficits. In this study, we investigated the degree of alterations in the microstructure of hippocampal subfields across the clinical continuum of Alzheimer's disease. We applied a grey matter-specific multi-compartment diffusion model (Cortical-Neurite orientation dispersion and density imaging) to understand the differential effects of Alzheimer's disease pathology on the hippocampal subfield microstructure. A total of 119 participants were included in this cross-sectional study. Participants were stratified into three categories, cognitively normal (n = 47), mild cognitive impairment (n = 52), and Alzheimer's disease (n = 19). Diffusion MRI, plasma biomarkers and neuropsychological test scores were used to determine the association between the microstructural integrity and Alzheimer's disease-associated molecular indicators and cognition. For Alzheimer's disease-related plasma biomarkers, we studied amyloid-β, total tau and neurofilament light; for Alzheimer's disease-related neuropsychological tests, we included the Trail Making Test, Rey Auditory Verbal Learning Test, Digit Span and Montreal Cognitive Assessment. Comparisons between cognitively normal subjects and those with mild cognitive impairment showed significant microstructural alterations in the hippocampal cornu ammonis (CA) 4 and dentate gyrus region, whereas CA 1-3 was the most sensitive region for the later stages in the Alzheimer's disease clinical continuum. Among imaging metrics for microstructures, the volume fraction of isotropic diffusion for interstitial free water demonstrated the largest effect size in between-group comparisons. Regarding the plasma biomarkers, neurofilament light appeared to be the most sensitive biomarker for associations with microstructural imaging findings in CA4-dentate gyrus. CA 1-3 was the subfield which had stronger correlations between cognitive performance and microstructural metrics. Particularly, poor performance on the Rey Auditory Verbal Learning Test and Montreal Cognitive Assessment was associated with decreased intracellular volume fraction. Overall, our findings support the value of tissue-specific microstructural imaging for providing pathologically relevant information manifesting in the plasma biomarkers and neuropsychological outcomes across various stages of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM) for diffusion and perfusion estimation by characterizing the objective function using simplicial homology tools. We provide a robust solution via topological optimization of this model so that the estimates are more reliable and accurate. Estimating the tissue microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem. Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model we perform the optimization using simplicial homology based global optimization to better understand the topology of objective function surface. We theoretically show how the proposed methodology can recover the model parameters more accurately and consistently by casting it in a reduced subspace given by VarPro. Additionally we demonstrate that the IVIM model parameters cannot be accurately reconstructed using conventional numerical optimization methods due to the presence of infinite solutions in subspaces. The proposed method helps uncover multiple global minima by analyzing the local geometry of the model enabling the generation of reliable estimates of model parameters. [ABSTRACT FROM AUTHOR]

Sport-related concussion (SRC) is an important public health issue. White-matter alterations after SRC are widely studied by neuroimaging approaches, such as diffusion magnetic resonance imaging (MRI). Although the exact anatomical location of the alterations may differ, significant white-matter alterations are commonly observed in long fiber tracts, but are never proven. In the present study, we performed streamline tractography to characterize the association between tract length and white-matter microstructural alterations after SRC. Sixty-eight collegiate athletes diagnosed with acute concussion (24–48 h post-injury) and 64 matched contact-sport controls were included in this study. The athletes underwent diffusion tensor imaging (DTI) in 3.0 T MRI scanners across three study sites. DTI metrics were used for tract-based spatial statistics to map white-matter regions-of-interest (ROIs) with significant group differences. Whole-brain white-mater streamline tractography was performed to extract "affected" white-matter streamlines (i.e., streamlines passing through the identified ROIs). In the concussed athletes, streamline counts and DTI metrics of the affected white-matter fiber tracts were summarized and compared with unaffected white-matter tracts across tract length in the same participant. The affected white-matter tracts had a high streamline count at length of 80–100 mm and high length-adjusted affected ratio for streamline length longer than 80 mm. DTI mean diffusivity was higher in the affected streamlines longer than 100 mm with significant associations with the Brief Symptom Inventory score. Our findings suggest that long fibers in the brains of collegiate athletes are more vulnerable to acute SRC with higher mean diffusivity and a higher affected ratio compared with the whole distribution. [ABSTRACT FROM AUTHOR]

• Tau deposition is associated with white-matter (WM) degeneration along connecting tracts. • Tau-related WM degeneration demonstrates distinct spatial pattern, similar to Braak staging. • WM degeneration is characterized by increased mean diffusivity and decreased axon density. • WM plays an important role in the deposition of tau pathology. Progressive accumulation of tau neurofibrillary tangles in the brain is a defining pathologic feature of Alzheimer's disease (AD). Tau pathology exhibits a predictable spatiotemporal spreading pattern, but the underlying mechanisms of this spread are poorly understood. Although AD is conventionally considered a disease of the gray matter, it is also associated with pronounced and progressive deterioration of the white matter (WM). A link between abnormal tau and WM degeneration is suggested by findings from both animal and postmortem studies, but few studies demonstrated their interplay in vivo. Recent advances in diffusion magnetic resonance imaging and the availability of tau positron emission tomography (PET) have made it possible to evaluate the association of tau and WM degeneration (tau-WM) in vivo. In this study, we explored the spatial pattern of tau-WM associations across the whole brain to evaluate the hypothesis that tau deposition is associated with WM microstructural alterations not only in isolated tracts, but in continuous structural connections in a stereotypic pattern. Sixty-two participants, including 22 cognitively normal subjects, 22 individuals with subjective cognitive decline, and 18 with mild cognitive impairment were included in the study. WM characteristics were inferred by classic diffusion tensor imaging (DTI) and a complementary diffusion compartment model – neurite orientation dispersion and density imaging (NODDI) that provides a proxy for axonal density. A data-driven iterative searching (DDIS) approach, coupled with whole-brain graph theory analyses, was developed to continuously track tau-WM association patterns. Without applying prior knowledge of the tau spread, we observed a distinct spatial pattern that resembled the typical propagation of tau pathology in AD. Such association pattern was not observed between diffusion and amyloid-β PET signal. Tau-related WM degeneration is characterized by an increase in the mean diffusivity (with a dominant change in the radial direction) and a decrease in the intra-axonal volume fraction. These findings suggest that cortical tau deposition (as measured in tau PET) is associated with a lower axonal packing density and greater diffusion freedom. In conclusion, our in vivo findings using a data-driven method on cross-sectional data underline the important role of WM alterations in the AD pathological cascade with an association pattern similar to the postmortem Braak staging of AD. Future studies will focus on longitudinal analyses to provide in vivo evidence of tau pathology spreads along neuroanatomically connected brain areas. [ABSTRACT FROM AUTHOR]