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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. [ABSTRACT FROM AUTHOR]

In vivo noninvasive imaging of neurometabolites is crucial to improve our understanding of the underlying pathophysiological mechanism in neurodegenerative diseases. Abnormal changes in synaptic organization leading to synaptic degradation and neuronal loss is considered as one of the primary factors driving Alzheimer's disease pathology. Magnetic resonance based molecular imaging techniques such as chemical exchange saturation transfer (CEST) and magnetic resonance spectroscopy (MRS) can provide neurometabolite specific information which may relate to underlying pathological and compensatory mechanisms. In this study, CEST and short echo time single voxel MRS was performed to evaluate the sensitivity of cerebral metabolites to beta-amyloid (Aβ) induced synaptic deficit in the hippocampus of a mouse model of Alzheimer's disease. The CEST based spectra (Z-spectra) were acquired on a 9.4 Tesla small animal MR imaging system with two radiofrequency (RF) saturation amplitudes (1.47 μT and 5.9 μT) to obtain creatine-weighted and glutamate-weighted CEST contrasts, respectively. Multi-pool Lorentzian fitting and quantitative T1 longitudinal relaxation maps were used to obtain metabolic specific apparent exchange-dependent relaxation (AREX) maps. Short echo time (TE = 12 ms) single voxel MRS was acquired to quantify multiple neurometabolites from the right hippocampus region. AREX contrasts and MRS based metabolite concentration levels were examined in the ARTE10 animal model for Alzheimer's disease and their wild type (WT) littermate counterparts (age = 10 months). Using MRS voxel as a region of interest, group-wise analysis showed significant reduction in Glu-AREX and Cr-AREX in ARTE10, compared to WT animals. The MRS based results in the ARTE10 mice showed significant decrease in glutamate (Glu) and glutamate-total creatine (Glu/tCr) ratio, compared to WT animals. The MRS results also showed significant increase in total creatine (tCr), phosphocreatine (PCr) and glutathione (GSH) concentration levels in ARTE10, compared to WT animals. In the same ROI, Glu-AREX and Cr-AREX demonstrated positive associations with Glu/tCr ratio. These results indicate the involvement of neurotransmitter metabolites and energy metabolism in Aβ-mediated synaptic degradation in the hippocampus region. The study also highlights the feasibility of CEST and MRS to identify and track multiple competing and compensatory mechanisms involved in heterogeneous pathophysiology of Alzheimer's disease in vivo. [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]

Background: Diffusion tensor imaging (DTI) measures water diffusion within brain tissue and can provide information regarding white matter, myelin, and axonal degeneration. We analyzed the cingulum bundle of the hippocampus (CBH), chosen for relevance to Alzheimer's Disease (AD) and memory (Wen et al, 2019; Dalboni da Rocha et al, 2020), using fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AxD), and mean diffusivity (MD), as well as their relationship to cognition, measured by DTI data from the initial phase of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE). Methods: Participants from KBASE included cognitively normal older adults (CN, n = 276), mild cognitive impairment (MCI, n = 142), and AD dementia (AD, n = 87) studied with baseline neuroimaging and cognitive testing at Seoul National University and processed at Indiana University School of Medicine. Affine and non‐linear transformations were used to align individual FA maps to the FMRIB58FA template (FSL). Voxel values were extracted from unilateral CBH regions (determined using JHU ICBM‐DTI‐81‐white‐matter‐labels atlas) and averaged. Univariate‐GLM and Bonferroni‐corrected post‐hoc T‐tests controlling for age and sex were used to analyze diagnostic group differences, with lower FA and higher RD, AxD, and MD values expected in MCI and AD groups compared to CN. Bonferroni‐adjusted partial correlations controlling for age, sex, and education were used to test the hypothesis that DTI values would be associated with worsening cognitive scores. Results: As hypothesized, bilateral CBH DTI values in AD and MCI were significantly worse than those in CN (p<0.001) (Fig 1) with moderate effect sizes (η2 = 0.111 – 0.307). Worsening DTI values were significantly associated with worsening Digit Span Backward, Trailmaking A and B, GDS, MMSE‐KC, CDR‐SB, Word List Recall, and Logical Memory scores at the Bonferroni‐adjusted p‐value of 0.003. Bilaterally, higher Digit Span Forward scores were significantly associated with AxD values and lower Total SMCQ scores were associated with RD, AxD, and MD values. Conclusion: Within the KBASE cohort, MCI and AD demonstrated significantly worse DTI, memory, and cognition consistent with the pattern of white matter microstructural damage previously reported in MCI and AD (Wen et al, 2019; LoBuono et al., 2019). [ABSTRACT FROM AUTHOR]

Background: The human brain undergoes considerable morphologic change with age, which is one of the primary risk‐factors for Alzheimer's disease (AD). Age‐related microstructural changes in the brain may be quantified by advanced diffusion MRI (dMRI) with compartment modeling. In this longitudinal study, we aimed to investigate the effects of age on the hippocampal subfields, one of the brain regions vulnerable to the early stages of AD. Method: Thirty‐seven cognitively normal older adults (70.6 ± 6.7 years) were recruited from the Indiana ADRC. Participants received a baseline and a follow‐up MRI scan over 24 ± 11.7 months with a Siemens 3T Prisma scanner using a 64‐channel head coil. We applied grey‐matter‐specific multi‐compartment diffusion model (cortical‐neurite orientation dispersion and density imaging) to derive diffusion microstructural metrics, namely orientation dispersion index (ODI), volume fractions of fast isotropic diffusion (VFISO), and intracellular‐space (VFIC) in the hippocampal‐subfields (CA1‐3, CA4 and dentate gyrus (CA4‐DG), and subiculum) [1]. To study the longitudinal age effects, we investigated the rate of change in the diffusion metrics and the association between the rate of change and age. Linear regression analysis was performed using SPSS software and adjusted for sex, education, APoE e4 status, and subfield volumes (Table 1). Result: All subjects had normal cognition (i.e., MoCA and MMSE, Table 1). The volumes of CA1‐3 and subiculum significantly decreased between the baseline and follow‐up MRI scans, (p<0.05, Table 1). During this period, while significantly increased ODI within subject was observed in CA4‐DG, significantly decreased VFISO in all the subfields and increased VFIC in the subiculum were noted (Figure 1). The decreasing rate of VFISO in CA4‐DG was significantly associated with age (Table 2), suggesting the reduction in VFISO accelerated over age. Conclusion: We demonstrated that diffusion metrics are sensitive to microstructural alterations in the hippocampal subfields of cognitively normal older adults. The cornu ammonis region 4 and dentate gyrus is the most vulnerable region affected by aging with increased tissue dispersion and age‐accelerated reduction in fast isotropic diffusion. Future studies will focus on the effects of the initial microstructural condition to its rate of change with aging. References: 1. Shahid, et al., Brain,2022 [ABSTRACT FROM AUTHOR]

Background: Hypertension is one of the key vascular risk factors of AD and related dementia. Cerebral blood flow (CBF) and white matter (WM) integrity may play an essential role in understanding the vascular contributions to dementia (VCID). We investigated if hypertension is related to WM microstructural and vascular imaging metrics in WM. Method: Four‐hundred‐seven subjects (age: 69.7±8.1 years) enrolled in the Wake Forest Alzheimer's Disease Research Center (ADRC) Clinical Core underwent MRI, including neurite orientation dispersion and density imaging (NODDI) and eight‐phase pseudo‐continuous ASL (PCASL). The subjects included 158 MCI, 111 APOE e4 allele carriers, 224 with hypertension, and 249 with impaired glycemic status which includes type 2 diabetes and prediabetics. Hypertension status was defined as SBP≥130mmHG and DBP≥80mmHG. The microstructural imaging metrics including intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index (ODI) were obtained from NODDI. The vascular imaging metric included CBF. CBF was obtained from PCASL sequence. Voxel‐wise linear regression analyses were performed to examine if CBF, ICVF, ISOVF, or ODI were related to hypertension adjusting for cognitive status, glycemic status, APOE e4 allele, age, sex, and years of education. All images were normalized into standard space. Tract‐based spatial statistics (TBSS) were used to normalize NODDI images. The false positive cluster thresholding was applied. Result: Hypertensive subjects showed impairments in both microstructural and vascular imaging metrics. Based on Figures 1‐(A), 2‐(A) and 3‐(A), there are overlapping brain image voxels between the microstructural and vascular imaging metrics. Additionally, the hypertensive subjects showed significantly lower CBF, higher ISOVF, and higher ODI than normal subjects within the voxel clusters (Figures 1‐(B), 2‐(B), and 3‐(B)). Note that APOE e4 allele, glycemic status, and cognitive status also showed statistical significance in the NODDI parameters, but there was no association in CBF. Conclusion: Hypertension showed the potential association between the microstructural and vascular impairments in the WM. Each risk factor and cognitive status differently affected WM microstructural and vascular dynamic imaging parameters. These findings warrant further investigations of contributions of hypertension to the microstructural and vascular abnormalities in dementia. [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]

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]

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. Index Terms--Diffusion, diffusion spectrum imaging, diffusion tensor imaging, orientation distribution function, q-space.

Background: Tau propagates in a highly stereotyped pattern in both normally aged and cognitively impaired individuals, with the medial temporal lobe (MTL) being first affected. Although substantial progress has been made in revealing its spreading pattern with the aid of network analysis, it remains unclear why tau first seeds in this specific region. We hypothesize that regional white‐matter connections exacerbate MTL's vulnerability to tauopathy. Further, we speculate that tau candidate genes have higher expression levels in MTL. This study tested the two hypotheses in cognitively normal older brains using two independent imaging datasets, i.e., ADNI and Indiana ADRC (IADRC), along with gene expression data derived from the Allen Human Brain Atlas (AHBA). Method: We identified 159 cognitively normal participants (72±7 y/o) in ADNI and 57 (70±7 y/o) in IADRC that have both diffusion MRI and tau‐PET (AV1451) data. We estimated network metrics and tau SUVR in 68 cortical regions of interest (ROIs) for each participant. All participants' data were then averaged (after controlling for age and sex) to produce ROI‐wise measurements. Gene expression data were extracted from the same 68 ROIs. We preselected eight tau risk genes, including MAPT, LRP1, PTK2B, MADD, CASS4, BIN1, EPHA1, and APOE. Spearman correlation was applied to examine their spatial correlations. Result: ADNI and IADRC reveal a similar spatial pattern for structural connectivity and tau deposition, with MTL demonstrating lower connectivity and higher gene expression levels (Figure 1A‐B). This trend is also evident when summarized in Braak stages (Figure 1C‐D), with Braak I ROI (entorhinal) showing the most elevated tau deposition, lowest structural connectivity, and highest gene expression level. Figure 2 summarizes the Spearman's Rho across the 68 ROIs. Consistently, higher tau deposition is associated with lower connectivity and higher the expression levels of BIN1 and APOE. Conclusion: The two independent datasets produced consistent results, supporting our hypotheses that both weaker structural connectivity and higher tau candidate gene expression contribute to the regional vulnerability in the MTL. These preliminary results encourage future studies to systemically examine the interaction between tau, gene expression, and axonal changes in healthy aging and across the AD spectrum. [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]