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Background Cerebrovascular reserve, the potential capacity of brain tissue to receive more blood flow when needed, is a desirable marker in evaluating ischemic risk. However, current measurement methods require acetazolamide injection or hypercapnia challenge, prompting a clinical need for resting-state (RS) blood oxygen level-dependent (BOLD) functional MRI data to measure cerebrovascular reactivity (CVR). Purpose To optimize and evaluate an RS CVR MRI technique and demonstrate its relationship to neurosurgical treatment. Materials and Methods In this HIPAA-compliant study, RS BOLD functional MRI data collected in 170 healthy controls between December 2008 and September 2010 were retrospectively evaluated to identify the optimal frequency range of temporal filtering on the basis of spatial correlation with the reference standard CVR map obtained with CO 2 inhalation. Next, the optimized RS method was applied in a new, prospective cohort of 50 participants with Moyamoya disease who underwent imaging between June 2014 and August 2019. Finally, CVR values were compared between brain hemispheres with and brain hemispheres without revascularization surgery by using Mann-Whitney U test. Results A total of 170 healthy controls (mean age ± standard deviation, 51 years ± 20; 105 women) and 100 brain hemispheres of 50 participants with Moyamoya disease (mean age, 41 years ± 12; 43 women) were evaluated. RS CVR maps based on a temporal filtering frequency of [0, 0.1164 Hz] yielded the highest spatial correlation ( r = 0.74) with the CO 2 inhalation CVR results. In patients with Moyamoya disease, 77 middle cerebral arteries (MCAs) had stenosis. RS CVR in the MCA territory was lower in the group that did not undergo surgery ( n = 30) than in the group that underwent surgery ( n = 47) (mean, 0.407 relative units [ru] ± 0.208 vs 0.532 ru ± 0.182, respectively; P = .006), which is corroborated with the CO 2 inhalation CVR data (mean, 0.242 ru ± 0.273 vs 0.437 ru ± 0.200; P = .003). Conclusion Cerebrovascular reactivity mapping performed by using resting-state blood oxygen level-dependent functional MRI provided a task-free method to measure cerebrovascular reserve and depicted treatment effect of revascularization surgery in patients with Moyamoya disease comparable to that with the reference standard of CO 2 inhalation MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wolf and Ware in this issue.

Cerebrovascular reactivity (CVR), an index of brain vessel's dilatory capacity, is typically measured using hypercapnic gas inhalation or breath-holding as a vasoactive challenge. However, these methods require considerable subject cooperation and could be challenging in clinical studies. More recently, there have been attempts to use resting-state BOLD data to map CVR by utilizing spontaneous changes in breathing pattern. However, in subjects who have small fluctuations in their spontaneous breathing pattern, the CVR results could be noisy and unreliable. In this study, we aim to develop a new method for CVR mapping that does not require gas-inhalation yet provides substantially higher sensitivity than resting-state CVR mapping. This new method is largely based on resting-state scan, but introduces intermittent modulation of breathing pattern in the subject to enhance fluctuations in their end-tidal CO2 (EtCO2) level. Here we examined the comfort level, sensitivity, and accuracy of this method in two studies. First, in 8 healthy young subjects, we developed the intermittent breath-modulation method using two different modulation frequencies, 6 ​s per breath and 12 ​s per breath, respectively, and compared the results to three existing CVR methods, specifically hypercapnic gas inhalation, breath-holding, and resting-state. Our results showed that the comfort level of the 6-s breath-modulation method was significantly higher than breath-holding (p ​= ​0.007) and CO2-inhalation (p ​= ​0.015) methods, while not different from the resting-state, i.e. free breathing method (p ​= ​0.52). When comparing the sensitivity of CVR methods, the breath-modulation methods revealed higher Z-statistics compared to the resting-state scan (p ​< ​0.008) and was comparable to breath-holding results. Next, we tested the feasibility of breath-modulation CVR mapping (6 ​s per breath) in 21 cognitively normal elderly participants and compared quantitative CVR values to that obtained with the CO2-inhalation method. Whole-brain CVR was found to be 0.150 ​± ​0.055 and 0.154 ​± ​0.032 %ΔBOLD/mmHg for the breath-modulation and CO2-inhalation method, respectively, with a significant correlation between them (y ​= ​0.97x, p ​= ​0.007). CVR mapping with intermittent breath modulation may be a useful method that combines the advantages of resting-state and CO2-inhalation based approaches., Competing Interests: Declaration of competing interest The authors have no conflicts of interest or financial disclosures to report., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: With the disappointing outcomes of clinical trials on patients with Alzheimer's disease or mild cognitive impairment (MCI), there is increasing attention to understanding cognitive decline in normal elderly individuals, with the goal of identifying subjects who are most susceptible to imminent cognitive impairment., Purpose/hypothesis: To evaluate the potential of cerebral blood flow (CBF) as a biomarker by investigating the relationship between CBF at baseline and cognition at follow-up., Study Type: Prospective longitudinal study with a 4-year time interval., Population: 309 healthy subjects aged 20-89 years old., Field Strength/sequence: 3T pseudo-continuous-arterial-spin-labeling MRI., Assessment: CBF at baseline and cognitive assessment at both baseline and follow-up., Statistical Tests: Linear regression analyses with age, systolic blood pressure, physical activity, and baseline cognition as covariates., Results: Linear regression analyses revealed that whole-brain CBF at baseline was predictive of general fluid cognition at follow-up. This effect was observed in the older group (age ≥54 years, β = 0.221, P = 0.004), but not in younger or entire sample (β = 0.018, P = 0.867 and β = 0.089, P = 0.098, respectively). Among major brain lobes, frontal CBF had the highest sensitivity in predicting future cognition, with a significant effect observed for fluid cognition (β = 0.244 P = 0.001), episodic memory (β = 0.294, P = 0.001), and reasoning (β = 0.186, P = 0.027). These associations remained significant after accounting for baseline cognition. Voxelwise analysis revealed that medial frontal cortex and anterior cingulate cortex, part of the default mode network (DMN), are among the most important regions in predicting fluid cognition., Data Conclusion: In a healthy aging cohort, CBF can predict general cognitive ability as well as specific domains of cognitive function., Level of Evidence: 1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:449-458., (© 2018 International Society for Magnetic Resonance in Medicine.)

Purpose: To investigate the venous oxygenation and flow in the brain, and determine how they might change under challenged states., Materials and Methods: Eight healthy human subjects (24-37 years) were studied. T 2 -relaxation under spin tagging (TRUST) magnetic resonance imaging (MRI) and phase-contrast MRI were performed to measure venous oxygenation and venous blood flow, respectively, in the superior sagittal sinus (SSS), the straight sinus (SS), and the internal jugular veins (IJVs). Venous oxygenation was assessed at room air (0.03%CO 2 , 21%O 2 ) and under hyperoxia (O%CO 2 , 95%O 2 , and 5%N 2 ) conditions. Venous blood flow was assessed at room air and under hypercapnia (5%CO 2 , 21%O 2 , and 74%N 2 ) conditions. Whole-brain blood flow was also measured at the four feeding arteries of the brain using phase-contrast MRI. The changes in venous oxygenation and blood flow from room air to hyperoxia or hypercapnia conditions were tested using paired t-tests., Results: Venous oxygenation in the SSS, the SS, and the IJVs was 61 ± 4%, 64 ± 4%, and 62 ± 4%, respectively, at room air, and increased to 70 ± 3% (P < 0.01 compared to room air), 71 ± 5% (P = 0.59), and 68 ± 5% (P < 0.05) under hyperoxic condition. The SSS, SS, and IJV drained 46 ± 9%, 16 ± 4%, and 79 ± 1% of whole-brain blood flow, respectively, and this flow distribution did not change under hypercapnic condition (P > 0.5)., Conclusion: The results found in this study provide insight into the venous oxygenation and venous flow distribution and its heterogeneity among different venous structures., Level of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1091-1098., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: Cerebral venous oxygenation (Y v ) is an important biomarker for brain diseases. This study aims to develop an R2*-based MR oximetry that can measure cerebral Y v in 3D., Methods: This technique separates blood signal from tissue by velocity-encoding phase contrast and measures the R2* of pure blood by multi-gradient-echo acquisition. The blood R2* was converted to Y v using an R2*-versus-oxygenation (Y) calibration curve, which was obtained by in vitro bovine blood experiments. Reproducibility, sensitivity, validity, and resolution dependence of the technique were evaluated., Results: In vitro R2*-Y calibration plot revealed a strong dependence of blood R2* on oxygenation, with additional dependence on hematocrit. In vivo results demonstrated that the technique can provide a 3D venous oxygenation map that depicts both large sinuses and smaller cortical veins, with venous oxygenation ranging from 57 to 72%. Intrasession coefficient of variation of the measurement was 3.0%. The technique detected an average Y v increase of 10.8% as a result of hyperoxia, which was validated by global oxygenation measurement from T 2 -Relaxation-Under-Spin-Tagging (TRUST) MRI. Two spatial resolutions, one with an isotropic voxel dimension and the other with a nonisotropic dimension, were tested for full brain coverage., Conclusions: This study demonstrated the feasibility of 3D brain oxygenation mapping without using contrast agent. Magn Reson Med 79:1304-1313, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O 2 and CO 2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03%/mmHg and 0.0056±0.0006%/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06%/mmHg vs. 0.21±0.05%/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO 2 and O 2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Cerebrovascular reactivity (CVR), the ability of cerebral vessels to dilate or constrict, has been shown to provide valuable information in the diagnosis and treatment evaluation of patients with various cerebrovascular conditions. CVR mapping is typically performed using hypercapnic gas inhalation as a vasoactive challenge while collecting BOLD images, but the inherent need of gas inhalation and the associated apparatus setup present a practical obstacle in applying it in routine clinical use. Therefore, we aimed to develop a new method to map CVR using resting-state BOLD data without the need of gas inhalation. This approach exploits the natural variation in respiration and measures its influence on BOLD MRI signal. In this work, we first identified a surrogate of the arterial CO 2 fluctuation during spontaneous breathing from the global BOLD signal. Second, we tested the feasibility and reproducibility of the proposed approach to use the above-mentioned surrogate as a regressor to estimate voxel-wise CVR. Third, we validated the "resting-state CVR map" with a conventional CVR map obtained with hypercapnic gas inhalation in healthy volunteers. Finally, we tested the utility of this new approach in detecting abnormal CVR in a group of patients with Moyamoya disease, and again validated the results using the conventional gas inhalation method. Our results showed that global BOLD signal fluctuation in the frequency range of 0.02-0.04Hz contains the most prominent contribution from natural variation in arterial CO 2 . The CVR map calculated using this signal as a regressor is reproducible across runs (ICC=0.91±0.06), and manifests a strong spatial correlation with results measured with a conventional hypercapnia-based method in healthy subjects (r=0.88, p<0.001). We also found that resting-state CVR was able to identify vasodilatory deficit in patients with steno-occlusive disease, the spatial pattern of which matches that obtained using the conventional gas method (r=0.71±0.18). These results suggest that CVR obtained with resting-state BOLD may be a useful alternative in detecting vascular deficits in clinical applications when gas challenge is not feasible., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The brain is a spatially heterogeneous and temporally dynamic organ, with different regions requiring different amount of blood supply at different time. Therefore, the ability of the blood vessels to dilate or constrict, known as Cerebral-Vascular-Reactivity (CVR), represents an important domain of vascular function. An imaging marker representing this dynamic property will provide new information of cerebral vessels under normal and diseased conditions such as stroke, dementia, atherosclerosis, small vessel diseases, brain tumor, traumatic brain injury, and multiple sclerosis. In order to perform this type of measurement in humans, it is necessary to deliver a vasoactive stimulus such as CO2 and/or O2 gas mixture while quantitative brain magnetic resonance images (MRI) are being collected. In this work, we presented a MR compatible gas-delivery system and the associated protocol that allow the delivery of special gas mixtures (e.g., O2, CO2, N2, and their combinations) while the subject is lying inside the MRI scanner. This system is relatively simple, economical, and easy to use, and the experimental protocol allows accurate mapping of CVR in both healthy volunteers and patients with neurological disorders. This approach has the potential to be used in broad clinical applications and in better understanding of brain vascular pathophysiology. In the video, we demonstrate how to set up the system inside an MRI suite and how to perform a complete experiment on a human participant.

BOLD fMRI has provided a wealth of information about the aging brain. A common finding is that posterior regions of the brain manifest an age-related decrease in activation while the anterior regions show an age-related increase. Several neurocognitive models have been proposed to interpret these findings. However, one issue that has not been sufficiently considered to date is that the BOLD signal is based on vascular responses secondary to neural activity. Thus the above findings could be in part due to a vascular change, especially in view of the expected decline of vascular health with age. In the present study, we aim to examine age-related differences in memory-encoding fMRI response in the context of vascular aging. One hundred and thirty healthy subjects ranging from 20 to 89 years old underwent a scene-viewing fMRI task and, in the same session, cerebrovascular reactivity (CVR) was measured in each subject using a CO2-inhalation task. Without accounting for the influence of vascular changes, the task-activated fMRI signal showed the typical age-related decrease in visual cortex and medial temporal lobe (MTL), but manifested an increase in the right inferior frontal gyrus (IFG). In the same individuals, an age-related CVR reduction was observed in all of these regions. We then used a previously proposed normalization approach to calculate a CVR-corrected fMRI signal, which was defined as the uncorrected signal divided by CVR. Based on the CVR-corrected fMRI signal, an age-related increase is now seen in both the left and right sides of IFG; and no brain regions showed a signal decrease with age. We additionally used a model-based approach to examine the fMRI data in the context of CVR, which again suggested an age-related change in the two frontal regions, but not in the visual and MTL regions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

One of the main obstacles in quantitative interpretation of functional magnetic resonance imaging (fMRI) signal is that this signal is influenced by non-neural factors such as vascular properties of the brain, which effectively increases signal variability. One approach to account for non-neural components is to identify and measure these confounding factors and to include them as covariates in data analysis or interpretation. Previously, several research groups have independently identified four potential physiologic modulators of fMRI signals, including baseline venous oxygenation (Yv ), cerebrovascular reactivity (CVR), resting state BOLD fluctuation amplitude (RSFA), and baseline cerebral blood flow (CBF). This study sought to directly compare the modulation effects of these indices in the same fMRI session. The physiologic parameters were measured with techniques comparable with those used in the previous studies except for CBF, which was determined globally with a velocity-based phase-contrast MRI (instead of arterial-spin-labeling MRI). Using an event-related, scene-categorization fMRI task, we showed that the fMRI signal amplitude was positively correlated with CVR (P < 0.0001) and RSFA (P = 0.002), while negatively correlated with baseline Yv (P < 0.0001). The fMRI-CBF correlation did not reach significance, although the (negative) sign of the correlation was consistent with the earlier study. Furthermore, among the physiologic modulators themselves, significant correlations were observed between baseline Yv and baseline CBF (P = 0.01), and between CVR and RSFA (P = 0.05), suggesting that some of the modulators may partly be of similar physiologic origins. These observations as well as findings in recent literature suggest that additional measurement of physiologic modulator(s) in an fMRI session may provide a practical approach to control for inter-subject variations and to improve the ability of fMRI in detecting disease or medication related differences. Hum Brain Mapp 34:2078-2088, 2013. © 2011 Wiley Periodicals, Inc., (Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.)

BackgroundWith the disappointing outcomes of clinical trials on patients with Alzheimer's disease or mild cognitive impairment (MCI), there is increasing attention to understanding cognitive decline in normal elderly individuals, with the goal of identifying subjects who are most susceptible to imminent cognitive impairment.Purpose/hypothesisTo evaluate the potential of cerebral blood flow (CBF) as a biomarker by investigating the relationship between CBF at baseline and cognition at follow-up.Study typeProspective longitudinal study with a 4-year time interval.Population309 healthy subjects aged 20-89 years old.Field strength/sequence3T pseudo-continuous-arterial-spin-labeling MRI.AssessmentCBF at baseline and cognitive assessment at both baseline and follow-up.Statistical testsLinear regression analyses with age, systolic blood pressure, physical activity, and baseline cognition as covariates.ResultsLinear regression analyses revealed that whole-brain CBF at baseline was predictive of general fluid cognition at follow-up. This effect was observed in the older group (age ≥54 years, β = 0.221, P = 0.004), but not in younger or entire sample (β = 0.018, P = 0.867 and β = 0.089, P = 0.098, respectively). Among major brain lobes, frontal CBF had the highest sensitivity in predicting future cognition, with a significant effect observed for fluid cognition (β = 0.244 P = 0.001), episodic memory (β = 0.294, P = 0.001), and reasoning (β = 0.186, P = 0.027). These associations remained significant after accounting for baseline cognition. Voxelwise analysis revealed that medial frontal cortex and anterior cingulate cortex, part of the default mode network (DMN), are among the most important regions in predicting fluid cognition.Data conclusionIn a healthy aging cohort, CBF can predict general cognitive ability as well as specific domains of cognitive function.Level of evidence1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:449-458.

Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural "contrast media". The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging. [ABSTRACT FROM AUTHOR]

A better understanding of the effect of oxygen on brain electrophysiological activity may provide a more mechanistic insight into clinical studies that use oxygen treatment in pathological conditions, as well as in studies that use oxygen to calibrate functional magnetic resonance imaging (fMRI) signals. This study applied electroencephalography (EEG) in healthy subjects and investigated how high a concentration of oxygen in inhaled air (i.e., normobaric hyperoxia) alters brain activity under resting-state and task-evoked conditions. Study 1 investigated its impact on resting EEG and revealed that hyperoxia suppressed α (8-13Hz) and β (14-35Hz) band power (by 15.6±2.3% and 14.1±3.1%, respectively), but did not change the δ (1-3Hz), θ (4-7Hz), and γ (36-75Hz) bands. Sham control experiments did not result in such changes. Study 2 reproduced these findings, and, furthermore, examined the effect of hyperoxia on visual stimulation event-related potentials (ERP). It was found that the main peaks of visual ERP, specifically N1 and P2, were both delayed during hyperoxia compared to normoxia (P = 0.04 and 0.02, respectively). In contrast, the amplitude of the peaks did not show a change. Our results suggest that hyperoxia has a pronounced effect on brain neural activity, for both resting-state and task-evoked potentials. [ABSTRACT FROM AUTHOR]

Phase-Contrast MRI (PC-MRI) is a noninvasive technique to measure blood flow. In particular, global but highly quantitative cerebral blood flow (CBF) measurement using PC-MRI complements several other CBF mapping methods such as arterial spin labeling and dynamic susceptibility contrast MRI by providing a calibration factor. The ability to estimate blood supply in physiological units also lays a foundation for assessment of brain metabolic rate. However, a major obstacle before wider applications of this method is that the slice positioning of the scan, ideally placed perpendicular to the feeding arteries, requires considerable expertise and can present a burden to the operator. In the present work, we proposed that the majority of PC-MRI scans can be positioned using an automatic algorithm, leaving only a small fraction of arteries requiring manual positioning. We implemented and evaluated an algorithm for this purpose based on feature extraction of a survey angiogram, which is of minimal operator dependence. In a comparative test-retest study with 7 subjects, the blood flow measurement using this algorithm showed an inter-session coefficient of variation (CoV) of . The Bland-Altman method showed that the automatic method differs from the manual method by between and , for of the CBF measurements. This is comparable to the variance in CBF measurement using manually-positioned PC MRI alone. In a further application of this algorithm to 157 consecutive subjects from typical clinical cohorts, the algorithm provided successful positioning in 89.7% of the arteries. In 79.6% of the subjects, all four arteries could be planned using the algorithm. Chi-square tests of independence showed that the success rate was not dependent on the age or gender, but the patients showed a trend of lower success rate (p = 0.14) compared to healthy controls. In conclusion, this automatic positioning algorithm could improve the application of PC-MRI in CBF quantification. [ABSTRACT FROM AUTHOR]