Background The systemic low‐frequency oscillation (sLFO) functional (f)MRI signals extracted from the internal carotid artery (ICA) and the superior sagittal sinus (SSS) are found to have valuable physiological information. Purpose 1) To further develop and validate a method utilizing these signals to measure the delay times from the ICAs and the SSS. 2) To establish the delay time as an effective perfusion biomarker that associates with cerebral circulation time (CCT). 3) To explore within subject variations, and the effects of gender and age on the delay times. Study Type Prospective. Subjects In all, 100 healthy adults (Human Connectome Project [HCP], age range 22–36 years, 54 females and 46 males), 56 healthy children (Adolescent Brain Cognitive Development project) were included. Field Strength/Sequence Echo planar imaging (EPI) sequence at 3T. Assessment The sLFO fMRI signals from the ICAs and the SSSs were extracted from the resting state fMRI data. The maximum cross‐correlation coefficients and their corresponding delay times were calculated. The gender and age differences of delay times were assessed statistically. Statistical Tests T‐tests were conducted to measure the gender differences. The Kruskal–Wallis test was used to detect age differences. Results Consistent and robust results were found from 80% of the 400 HCP scans included. Negative correlations (–0.67) between the ICA and the SSS signals were found with the ICA signal leading the SSS signal by ∼5 sec. Within subject variation was 2.23 sec at the 5% significance level. The delay times were not significantly different between genders (P = 0.9846, P = 0.2288 for the left and right ICA, respectively). Significantly shorter delay times (4.3 sec) were found in the children than in the adults (P < 0.01). Data Conclusion We have shown that meaningful perfusion information (ie, CCT) can be derived from the sLFO fMRI signals of the large blood vessels. Level of Evidence: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1504–1513.

It is commonly believed that cerebrospinal fluid (CSF) movement is facilitated by blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF movement was recently found during non-rapid eye movement (NREM) sleep via functional MRI. This finding raises other fundamental questions: 1) the explanation of coupling between hemodynamic oscillations and CSF movement from fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF movement. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF movement through the lens of fMRI. Time delays between CSF movement and global hemodynamics were calculated. The observed delays between hemodynamics and CSF movement match those predicted by the model. Moreover, by conducting separate fMRI scans of the brain and neck, we confirmed the low frequency CSF movement at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF movement is facilitated by changes in cerebral blood volume mainly in the low frequency range, even when the individual is awake.

Elevated carbon dioxide (CO2) in breathing air is widely used as a vasoactive stimulus to assess cerebrovascular functions under hypercapnia (i.e., “stress test” for the brain). Blood-oxygen-level-dependent (BOLD) is a contrast mechanism used in functional magnetic resonance imaging (fMRI). BOLD is used to study CO2-induced cerebrovascular reactivity (CVR), which is defined as the voxel-wise percentage BOLD signal change per mmHg change in the arterial partial pressure of CO2 (PaCO2). Besides the CVR, two additional important parameters reflecting the cerebrovascular functions are the arrival time of arterial CO2 at each voxel, and the waveform of the local BOLD signal. In this study, we developed a novel analytical method to accurately calculate the arrival time of elevated CO2 at each voxel using the systemic low frequency oscillations (sLFO: 0.01-0.1 Hz) extracted from the CO2 challenge data. In addition, 26 candidate hemodynamic response functions (HRF) were used to quantitatively describe the temporal brain reactions to a CO2 stimulus. We demonstrated that our approach improved the traditional method by allowing us to accurately map three perfusion-related parameters: the relative arrival time of blood, the hemodynamic response function, and CVR during a CO2 challenge.

The blood-oxygen-level-dependent (BOLD) signal in functional MRI (fMRI) measures neuronal activation indirectly. Previous studies have found aperiodic, systemic low-frequency oscillations (sLFOs, ~0.1Hz) in BOLD signals from resting-state (RS) fMRI, which reflects the non-neuronal cerebral perfusion information. In this study, we investigated the possibility of extracting vascular information from the sLFOs in RS BOLD fMRI, which could provide complementary information to the neuronal activations. Two features of BOLD signals were exploited. First, time delays between the sLFOs of big blood vessels and brain voxels were calculated to determine cerebral circulation times and blood arrival times. Second, voxel-wise standard deviations (SD) of LFOs were calculated to represent the blood densities. We explored those features on the publicly available Myconnectome dataset (a two-year study of an individual subject (Male)), which contains 45 RS scans acquired after the subject had coffee, and 45 coffee-free RS scans, acquired on different days. Our results showed that shorter time delays and smaller SDs were detected in caffeinated scans. This is consistent with the vasoconstriction effects of caffeine, which leads to increased blood flow velocity. We also compared our results with previous findings on neuronal networks from the same dataset. Our finding showed that brain regions with the significant vascular effect of caffeine coincide with those with significant neuronal effect, indicating close interaction. This study provides methods to assess the physiological information from RS fMRI. Together with the neuronal information, we can study simultaneously the underlying correlations and interactions between vascular and neuronal networks, especially in pharmacological studies.

Cerebral spinal fluid (CSF) plays an important role in the clearance of metabolic waste products from the brain, yet the driving forces of CSF flow are not fully understood. It is commonly believed that CSF flow is facilitated by the blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF flow was found recently during non-rapid eye movement sleep (NREM) sleep via functional MRI. However, questions remain regarding 1) the explanation of coupling between hemodynamic oscillations and CSF flow using fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF flow. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF flow through the lens of fMRI. We found that the observed delays between these two signals match those predicted by the model. Moreover, by conducting separated fMRI scans of the brain and neck, we confirmed the low frequency CSF flow at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF flow is facilitated by hemodynamic oscillations mainly in the low frequency range, even when the individual is awake.

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Vasoactive stress tests (i.e. hypercapnia, elevated partial pressure of arterial CO 2 [PaCO 2 ]) are commonly used in functional MRI (fMRI), to induce cerebral blood flow changes and expose hidden perfusion deficits in the brain. Compared with fMRI, near-infrared spectroscopy (NIRS) is an alternative low-cost, real-time, and non-invasive tool, which can be applied in out-of-hospital settings. To develop and optimize vasoactive stress tests for NIRS, several hypercapniainduced tasks were tested using concurrent-NIRS/fMRI on healthy subjects. The results indicated that the cerebral and extracerebral reactivity to elevated PaCO 2 depended on the rate of the CO 2 increase. A steep increase resulted in different cerebral and extracerebral reactivities, leading to unpredictable NIRS measurements compared with fMRI. However, a ramped increase, induced by ramped-CO 2 inhalation or breath-holding tasks, induced synchronized cerebral, and extracerebral reactivities, resulting in consistent NIRS and fMRI measurements. These results demonstrate that only tasks that increase PaCO 2 gradually can produce reliable NIRS results.