Purpose To present a novel MR pulse sequence and modeling algorithm to quantify the water exchange rate (kw) across the blood–brain barrier (BBB) without contrast, and to evaluate its clinical utility in a cohort of elderly subjects at risk of cerebral small vessel disease (SVD). Methods A diffusion preparation module with spoiling of non–Carr‐Purcell‐Meiboom‐Gill signals was integrated with pseudo‐continuous arterial spin labeling (pCASL) and 3D gradient and spin echo (GRASE) readout. The tissue/capillary fraction of the arterial spin labeling (ASL) signal was separated by appropriate diffusion weighting (b = 50 s/mm2). kw was quantified using a single‐pass approximation (SPA) model with total generalized variation (TGV) regularization. Nineteen elderly subjects were recruited and underwent 2 MRIs to evaluate the reproducibility of the proposed technique. Correlation analysis was performed between kw and vascular risk factors, Clinical Dementia Rating (CDR) scale, neurocognitive assessments, and white matter hyperintensity (WMH). Results The capillary/tissue fraction of ASL signal can be reliably differentiated with the diffusion weighting of b = 50 s/mm2, given ~100‐fold difference between the (pseudo‐)diffusion coefficients of the 2 compartments. Good reproducibility of kw measurements (intraclass correlation coefficient = 0.75) was achieved. Average kw was 105.0 ± 20.6, 109.6 ± 18.9, and 94.1 ± 19.6 min–1 for whole brain, gray and white matter. kw was increased by 28.2%/19.5% in subjects with diabetes/hypercholesterolemia. Significant correlations between kw and vascular risk factors, CDR, executive/memory function, and the Fazekas scale of WMH were observed. Conclusion A diffusion prepared 3D GRASE pCASL sequence with TGV regularized SPA modeling was proposed to measure BBB water permeability noninvasively with good reproducibility. kw may serve as an imaging marker of cerebral SVD and associated cognitive impairment.

Brain arteriolosclerosis (B-ASC), characterized by pathologic arteriolar wall thickening, is a common finding at autopsy in aged persons and is associated with cognitive impairment. Hypertension and diabetes are widely recognized as risk factors for B-ASC. Recent research indicates other and more complex risk factors and pathogenetic mechanisms. Here we describe aspects of the unique architecture of brain arterioles, histomorphologic features of B-ASC, relevant neuroimaging findings, epidemiology and association with aging, established genetic risk factors, and the co-occurrence of B-ASC with other neuropathologic conditions such as A a a b c-predominant age-related TDP-43 encephalopathy (LATE).There may also be complex physiologic interactions between metabolic syndrome (e.g. hypertension and inflammation) and brain arteriolar pathology. Although there is no universally applied diagnostic methodology, several classification schemes and neuroimaging techniques are used to diagnose and categorize cerebral small vessel disease pathologies that include B-ASC, microinfarcts, microbleeds, lacunar infarcts, and cerebral amyloid angiopathy (CAA). In clinical-pathologic studies that include consideration of comorbid diseases, B-ASC is independently associated with impairments in global cognition, episodic memory, working memory, and perceptual speed, and has been linked to autonomic dysfunction and motor symptoms including parkinsonism. We conclude by discussing critical knowledge gaps related to B-ASC and suggest that there are probably subcategories of B-ASC that differ in pathogenesis. Observed in over 80% of autopsied individuals beyond 80 years of age, B-ASC is a complex and under-studied contributor to neurologic disability.

Background: Dynamic contrast-enhanced (DCE) MRI using intravenous injection of gadolinium-based contrast agents (GBCAs) is commonly used for imaging blood-brain barrier (BBB) permeability. Water is an alternative endogenous tracer with limited exchange rate across the BBB. A direct comparison between BBB water exchange rate and BBB permeability to GBCA is missing. The purpose of this study was to directly compare BBB permeability to GBCA (Ktrans and kGad = Ktrans/Vp) and water exchange rate (kw) in a cohort of elderly subjects at risk of cerebral small vessel disease (cSVD).Methods: Ktrans/kGad and kw were measured by DCE-MRI and diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL), respectively, at 3 Tesla in 16 elderly subjects (3 male, age = 67.9 ± 3.0 yrs) at risk of cSVD. The test-retest reproducibility of kw measurements was evaluated with repeated scans ~6 weeks apart. Mixed effects linear regression was performed in the whole brain, gray matter (GM), white matter (WM), and 6 subcortical brain regions to investigate associations between Ktrans/kGad and test-retest kw. In addition, kw and Ktrans/kGad were compared in normal appearing white matter (NAWM), white matter hyperintensity (WMH) lesions and penumbra.Results: Significant correlation was found between kw and Ktrans only in WM (β = 6.7 × 104, P = 0.036), caudate (β = 8.6 × 104, P = 0.029), and middle cerebral artery (MCA) perforator territory (β = 6.9 × 104, P = 0.009), but not in the whole brain, GM or rest 5 brain regions. Significant correlation was found between kw and kGad in MCA perforator territory (β = 1.5 × 103, P = 0.049), medial-temporal lobe (β = 3.5 × 103, P = 0.032), and hippocampus (β = 3.4 × 103, P = 0.038), but not in the rest brain regions. Good reproducibility of kw measurements (ICC=0.75) was achieved. Ktrans was significantly lower inside WMH than WMH penumbra (16.2%, P = 0.026), and kGad was significantly lower in NAWM than in the WMH penumbra (20.8%, P < 0.001).Conclusion: kw provides a measure of water exchange rate across the BBB with good test-retest reproducibility. The BBB mechanism underlying kw and Ktrans/kGad is likely to be different, as manifested by correlations in only three brain regions for each pair of comparison between kw and Ktrans or kGad.

Cerebral small vessel disease (cSVD) affects arterioles, capillaries, and venules and can lead to cognitive impairments and clinical symptomatology of vascular cognitive impairment and dementia (VCID). VCID symptoms are similar to Alzheimer’s disease (AD) but the neurophysiologic alterations are less well studied, resulting in no established biomarkers. The purpose of this study was to evaluate cerebral blood flow (CBF) measured by 3D pseudo-continuous arterial spin labeling (pCASL) as a potential biomarker of VCID in a cohort of elderly Latinx subjects at risk of cSVD. Forty-five elderly Latinx subjects (12 males, 69 ± 7 years) underwent repeated MRI scans ∼6 weeks apart. CBF was measured using 3D pCASL in the whole brain, white matter and 4 main vascular territories (leptomeningeal anterior, middle, and posterior cerebral artery (leptoACA, leptoMCA, leptoPCA), as well as MCA perforator). The test-retest repeatability of CBF was assessed by intra-class correlation coefficient (ICC) and within-subject coefficient of variation (wsCV). Absolute and relative CBF was correlated with gross cognitive measures and domain specific assessment of executive and memory function, vascular risks, and Fazekas scores and volumes of white matter hyperintensity (WMH). Neurocognitive evaluations were performed using Montreal Cognitive Assessment (MoCA) and neuropsychological test battery in the Uniform Data Set v3 (UDS3). Good to excellent test-retest repeatability was achieved (ICC = 0.77–0.85, wsCV 3–9%) for CBF measurements in the whole brain, white matter, and 4 vascular territories. Relative CBF normalized by global mean CBF in the leptoMCA territory was positively correlated with the executive function composite score, while relative CBF in the leptoMCA and MCA perforator territory was positively correlated with MoCA scores, controlling for age, gender, years of education, and testing language. Relative CBF in WM was negatively correlated with WMH volume and MoCA scores, while relative leptoMCA CBF was positively correlated with WMH volume. Reliable 3D pCASL CBF measurements were achieved in the cohort of elderly Latinx subjects. Relative CBF in the leptomeningeal and perforator MCA territories were the most likely candidate biomarker of VCID. These findings need to be replicated in larger cohorts with greater variability of stages of cSVD.

The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.