MRI free water mediates the association between water exchange rate across the blood brain barrier and executive function among older adults.

Vascular risk factors contribute to cognitive aging, with one such risk factor being dysfunction of the blood brain barrier (BBB). Studies using non-invasive magnetic resonance imaging (MRI) techniques, such as diffusion prepared arterial spin labeling (DP-ASL), can estimate BBB function by measuring water exchange rate (kw). DP-ASL kw has been associated with cognition, but the directionality and strength of the relationship is still under investigation. An additional variable that measures water in extracellular space and impacts cognition, MRI free water (FW), may help explain prior findings. A total of 94 older adults without dementia (Mean age = 74.17 years, 59.6% female) underwent MRI (DP-ASL, diffusion weighted imaging (DWI)) and cognitive assessment. Mean kw was computed across the whole brain (WB), and mean white matter FW was computed across all white matter. The relationship between kw and three cognitive domains (executive function, processing speed, memory) was tested using multiple linear regression. FW was tested as a mediator of the kw-cognitive relationship using the PROCESS macro. A positive association was found between WB kw and executive function [F(4,85) = 7.81, p < .001, R2= 0.269; ß = .245, p = .014]. Further, this effect was qualified by subsequent results showing that FW was a mediator of the WB kw-executive function relationship (indirect effect results: standardized effect = .060, bootstrap confidence interval = .0006 to .1411). Results suggest that lower water exchange rate (kw) may contribute to greater total white matter (WM) FW which, in turn, may disrupt executive function. Taken together, proper fluid clearance at the BBB contributes to higher-order cognitive abilities.

Cerebrovascular reactivity MRI as a biomarker for cerebral small vessel disease-related cognitive decline: Multi-site validation in the MarkVCID Consortium.

INTRODUCTION: Vascular contributions to cognitive impairment and dementia (VCID) represent a major factor in cognitive decline in older adults. The present study examined the relationship between cerebrovascular reactivity (CVR) measured by magnetic resonance imaging (MRI) and cognitive function in a multi-site study, using a predefined hypothesis. METHODS: We conducted the study in a total of three analysis sites and 263 subjects. Each site performed an identical CVR MRI procedure using 5% carbon dioxide inhalation. A global cognitive measure of Montreal Cognitive Assessment (MoCA) and an executive function measure of item response theory (IRT) score were used as outcomes. RESULTS: CVR and MoCA were positively associated, and this relationship was reproduced at all analysis sites. CVR was found to be positively associated with executive function. DISCUSSION: The predefined hypothesis on the association between CVR and a global cognitive score was validated in three independent analysis sites, providing support for CVR as a biomarker in VCID. HIGHLIGHTS: This study measured a novel functional index of small arteries referred to as cerebrovascular reactivity (CVR). CVR was positively associated with global cognition in older adults. This finding was observed in three independent cohorts at three sites. Our statistical analysis plan was predefined before beginning data collection.

Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study.

BACKGROUND AND PURPOSE: Considering recent iodinated contrast shortages and a focus on reducing waste, developing protocols with lower contrast dosing while maintaining image quality through artificial intelligence is needed. This study compared reduced iodinated contrast media and standard dose CTP acquisitions, and the impact of deep learning denoising on CTP image quality in preclinical and clinical studies. The effect of reduced X-ray mAs dose was also investigated in preclinical studies. MATERIALS AND METHODS: Twelve swine underwent 9 CTP examinations each, performed at combinations of 3 different x-ray (37, 67, and 127 mAs) and iodinated contrast media doses (10, 15, and 20 mL). Clinical CTP acquisitions performed before and during the iodinated contrast media shortage and protocol change (from 40 to 30 mL) were retrospectively included. Eleven patients with reduced iodinated contrast media dosages and 11 propensity-score-matched controls with the standard iodinated contrast media dosages were included. A residual encoder-decoder convolutional neural network (RED-CNN) was trained for CTP denoising using k-space-weighted image average filtered CTP images as the target. The standard, RED-CNN-denoised, and k-space-weighted image average noise-filtered images for animal and human studies were compared for quantitative SNR and qualitative image evaluation. RESULTS: The SNR of animal CTP images decreased with reductions in iodinated contrast media and milliampere-second doses. Contrast dose reduction had a greater effect on SNR than milliampere-second reduction. Noise-filtering by k-space-weighted image average and RED-CNN denoising progressively improved the SNR of CTP maps, with RED-CNN resulting in the highest SNR. The SNR of clinical CTP images was generally lower with a reduced iodinated contrast media dose, which was improved by the k-space-weighted image average and RED-CNN denoising (P < .05). Qualitative readings consistently rated RED-CNN denoised CTP as the best quality, followed by k-space-weighted image average and then standard CTP images. CONCLUSIONS: Deep learning-denoising can improve image quality for low iodinated contrast media CTP protocols, and could approximate standard iodinated contrast media dose CTP, in addition to potentially improving image quality for low milliampere-second acquisitions.

Heterogeneous blood-brain barrier dysfunction in cerebral small vessel diseases.

INTRODUCTION: We explored how blood-brain barrier (BBB) leakage rate of gadolinium chelates (Ktrans) and BBB water exchange rate (kw) varied in cerebral small vessel disease (cSVD) subtypes. METHODS: Thirty sporadic cSVD, 40 cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), and 13 high-temperature requirement factor A serine peptidase 1 (HTRA) -related cSVD subjects were investigated parallel to 40 healthy individuals. Subjects underwent clinical, cognitive, and MRI assessment. RESULTS: In CADASIL, no difference in Ktrans, but lower kw was observed in multiple brain regions. In sporadic cSVD, no difference in kw, but higher Ktrans was found in the whole brain and normal-appearing white matter. In HTRA1-related cSVD, both higher Ktrans in the whole brain and lower kw in multiple brain regions were observed. In each patient group, the altered BBB measures were correlated with lesion burden or clinical severity. DISCUSSION: In cSVD subtypes, distinct alterations of kw and Ktrans were observed. The combination of Ktrans and kw can depict the heterogeneous BBB dysfunction. HIGHLIGHTS: We measured BBB leakage to gadolinium-based contrast agent (Ktrans) and water exchange rate (kw) across BBB in three subtypes of cSVD. CADASIL is characterized by lower kw, HTRA1-related cSVD exhibits both higher Ktrans and lower kw, while sporadic cSVD is distinguished by higher Ktrans. There are distinct alterations in kw and Ktrans among subtypes of cSVD, indicating the heterogeneous nature of BBB dysfunction.

Older adults with reduced cerebrovascular reactivity exhibit high white matter hyperintensity burden.

Cerebrovascular reactivity (CVR) deficits may contribute to small vessel disease, such as white matter hyperintensities (WMH). Moreover, apolipoprotein-e4 (APOE4) carriers at genetic risk for Alzheimer's disease exhibit cerebrovascular dysfunction relative to non-carriers. We examined whether older adults, and APOE4 carriers specifically, with diminished CVR would exhibit higher WMH burden. Independently living older adults (N = 125, mean age = 69.2 years; SD = 7.6; 31.2% male) free of dementia or clinical stroke underwent brain MRI to quantify cerebral perfusion during CVR to hypercapnia and hypocapnia and determine WMH volume. Adjusting for age, sex and intracranial volume, hierarchical regression analysis revealed a significant association between whole brain CVR to hypercapnia and WMH overall [B = -.02, 95% CI (-.04, -.008), p =.003] and in APOE4 carriers [B = -.03, 95% CI (-.06, -.009), p =.009]. Findings suggest deficits in cerebral vasodilatory capacity are associated with WMH burden in older adults and future studies are warranted to further delineate the effect of APOE4 on precipitating WMH.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Functional connectivity and complexity analyses of resting-state fMRI in pre-adolescents demonstrating the behavioral symptoms of ADHD.

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.

Vessel density mapping of small cerebral vessels on 3D high resolution black blood MRI.

Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling.

PURPOSE: To present a Swin Transformer-based deep learning (DL) model (SwinIR) for denoising single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) and other Transformer-based methods. METHODS: SwinIR and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 66 subjects (119 scans) and tested on 39 subjects (44 scans) from three different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL, respectively. The performance was evaluated using similarity metrics, spatial SNR and quantification accuracy of cerebral blood flow (CBF), and arterial transit time (ATT). RESULTS: SwinIR outperformed CNN and other Transformer-based networks, whereas pseudo-3D models performed better than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models and further improved when using M0 as input, but introduced greater biases for CBF quantification. Pseudo-3D models with three slices achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay ASL, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps. CONCLUSIONS: SwinIR provided better performance than CNN and other Transformer-based methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.