The value of resting-state functional MRI in subacute ischemic stroke: comparison with dynamic susceptibility contrast-enhanced perfusion MRI

Resting-State fMRI: Emerging Concepts for Future Clinical Application

Resting-state functional magnetic resonance imaging (rsfMRI) has been developed as a method of investigating spontaneous neural activity. Based on its low-frequency signal synchronization, rsfMRI has made it possible to identify multiple macroscopic structures termed resting-state networks (RSNs) on a single scan of less than 10 minutes. It is easy to implement even in clinical practice, in which assigning tasks to patients can be challenging. These advantages have accelerated the adoption and growth of rsfMRI. Recently, studies on the global rsfMRI signal have attracted increasing attention. Because it primarily arises from physiological events, less attention has hitherto been paid to the global signal than to the local network (i.e., RSN) component. However, the global signal is not a mere nuisance or a subsidiary component. On the contrary, it is quantitatively the dominant component that accounts for most of the variance in the rsfMRI signal throughout the brain and provides rich information on local hemodynamics that can serve as an individual-level diagnostic biomarker. Moreover, spatiotemporal analyses of the global signal have revealed that it is closely and fundamentally associated with the organization of RSNs, thus challenging the basic assumptions made in conventional rsfMRI analyses and views on RSNs. This review introduces new concepts emerging from rsfMRI spatiotemporal analyses focusing on the global signal and discusses how they may contribute to future clinical medicine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Hemodynamic timing in resting-state and breathing-task BOLD fMRI

The blood flow response to a vasoactive stimulus demonstrates regional heterogeneity across both the healthy brain and in cerebrovascular pathology. The timing of a regional hemodynamic response is emerging as an important biomarker of cerebrovascular dysfunction, as well as a confound within fMRI analyses. Previous research demonstrated that hemodynamic timing is more robustly characterized when a larger systemic vascular response is evoked by a breathing challenge, compared to when only spontaneous fluctuations in vascular physiology are present (i.e., in resting-state data). However, it is not clear whether hemodynamic delays in these two conditions are physiologically interchangeable, and how methodological signal-to-noise factors may limit their agreement. To address this, we generated whole-brain maps of hemodynamic delays in nine healthy adults. We assessed the agreement of voxel-wise gray matter (GM) hemodynamic delays between two conditions: resting-state and breath-holding. We found that delay values demonstrated poor agreement when considering all GM voxels, but increasingly greater agreement when limiting analyses to voxels showing strong correlation with the GM mean time-series. Voxels showing the strongest agreement with the GM mean time-series were primarily located near large venous vessels, however these voxels explain some, but not all, of the observed agreement in timing. Increasing the degree of spatial smoothing of the fMRI data enhanced the correlation between individual voxel time-series and the GM mean time-series. These results suggest that signal-to-noise factors may be limiting the accuracy of voxel-wise timing estimates and hence their agreement between the two data segments. In conclusion, caution must be taken when using voxel-wise delay estimates from resting-state and breathing-task data interchangeably, and additional work is needed to evaluate their relative sensitivity and specificity to aspects of vascular physiology and pathology.

Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI

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.

Reproducibility of cerebral perfusion measurements using BOLD delay

BOLD delay is an emerging, noninvasive method for assessing cerebral perfusion that does not require the use of intravenous contrast agents and is thus particularly suited for longitudinal monitoring. In this study, we assess the reproducibility of BOLD delay using data from 136 subjects with normal cerebral perfusion scanned on two separate occasions with scanners, sequence parameters, and intervals between scans varying between subjects. The effects of various factors on the reproducibility of BOLD delay, defined here as the differences in BOLD delay values between the scanning sessions, were investigated using a linear mixed model. Reproducibility was additionally assessed using the intraclass correlation coefficient of BOLD delay between sessions. Reproducibility was highest in the posterior cerebral artery territory. The mean BOLD delay test-retest difference after accounting for the aforementioned factors was 1.2 s (95% CI = 1.0 to 1.4 s). Overall, BOLD delay shows good reproducibility, but care should be taken when interpreting longitudinal BOLD delay changes that are either very small or are located in certain brain regions.

Artificially-reconstructed brain images with stroke lesions from non-imaging data: modeling in categorized patients based on lesion occurrence and sparsity

Brain imaging is necessary for understanding disease symptoms, including stroke. However, frequent imaging procedures encounter practical limitations. Estimating the brain information (e.g., lesions) without imaging sessions is beneficial for this scenario. Prospective estimating variables are non-imaging data collected from standard tests. Therefore, the current study aims to examine the variable feasibility for modelling lesion locations. Heterogeneous variables were employed in the multivariate logistic regression. Furthermore, patients were categorized (i.e., unsupervised clustering through k-means method) by the charasteristics of lesion occurrence (i.e., ratio between the lesioned and total regions) and sparsity (i.e., density measure of lesion occurrences across regions). Considering those charasteristics in models improved estimation performances. Lesions (116 regions in Automated Anatomical Labeling) were adequately predicted (sensitivity: 80.0-87.5% in median). We confirmed that the usability of models was extendable to different resolution levels in the brain region of interest (e.g., lobes, hemispheres). Patients' charateristics (i.e., occurrence and sparsity) might also be explained by the non-imaging data as well. Advantages of the current approach can be experienced by any patients (i.e., with or without imaging sessions) in any clinical facilities (i.e., with or without imaging instrumentation).

RP-Rs-fMRIomics as a Novel Imaging Analysis Strategy to Empower Diagnosis of Brain Gliomas

Rs-fMRI can provide rich information about functional processes in the brain with a large array of imaging parameters and is also suitable for investigating the biological processes in cerebral gliomas. We aimed to propose an imaging analysis method of RP-Rs-fMRIomics by adopting omics analysis on rs-fMRI with exhaustive regional parameters and subsequently estimating its feasibility on the prediction diagnosis of gliomas. In this retrospective study, preoperative rs-fMRI data were acquired from patients confirmed with diffuse gliomas (n = 176). A total of 420 features were extracted through measuring 14 regional parameters of rs-fMRI as much as available currently in 10 specific narrow frequency bins and three parts of gliomas. With a randomly split training and testing dataset (ratio 7:3), four classifiers were implemented to construct and optimize RP-Rs-fMRIomics models for predicting glioma grade, IDH status and Karnofsky Performance Status scores. The RP-Rs-fMRIomics models (AUROC 0.988, 0.905, 0.801) were superior to the corresponding traditional single rs-fMRI index (AUROC 0.803, 0.731, 0.632) in predicting glioma grade, IDH and survival. The RP-Rs-fMRIomics analysis, featuring high interpretability, was competitive for prediction of glioma grading, IDH genotype and prognosis. The method expanded the clinical application of rs-fMRI and also contributed a new imaging analysis for brain tumor research.

Coupling between cerebrovascular oscillations and CSF flow fluctuations during wakefulness: An fMRI study

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.

Effects of Thresholding on Voxel-Wise Correspondence of Breath-Hold and Resting-State Maps of Cerebrovascular Reactivity

Functional magnetic resonance imaging for presurgical brain mapping enables neurosurgeons to identify viable tissue near a site of operable pathology which might be at risk of surgery-induced damage. However, focal brain pathology (e.g., tumors) may selectively disrupt neurovascular coupling while leaving the underlying neurons functionally intact. Such neurovascular uncoupling can result in false negatives on brain activation maps thereby compromising their use for surgical planning. One way to detect potential neurovascular uncoupling is to map cerebrovascular reactivity using either an active breath-hold challenge or a passive resting-state scan. The equivalence of these two methods has yet to be fully established, especially at a voxel level of resolution. To quantitatively compare breath-hold and resting-state maps of cerebrovascular reactivity, we first identified threshold settings that optimized coverage of gray matter while minimizing false responses in white matter. When so optimized, the resting-state metric had moderately better gray matter coverage and specificity. We then assessed the spatial correspondence between the two metrics within cortical gray matter, again, across a wide range of thresholds. Optimal spatial correspondence was strongly dependent on threshold settings which if improperly set tended to produce statistically biased maps. When optimized, the two CVR maps did have moderately good correspondence with each other (mean accuracy of 73.6%). Our results show that while the breath-hold and resting-state maps may appear qualitatively similar they are not quantitatively identical at a voxel level of resolution.

A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI

Individualized treatment of acute stroke depends on the timely detection of ischemia and potentially salvageable tissue in the brain. Using functional MRI (fMRI), it is possible to characterize cerebral blood flow from blood‐oxygen‐level‐dependent (BOLD) signals without the administration of exogenous contrast agents. In this study, we applied spatial independent component analysis to resting‐state fMRI data of 37 stroke patients scanned within 24 hr of symptom onset, 17 of whom received follow‐up scans the next day. Our analysis revealed “Hypoperfusion spatially‐Independent Components” (HICs) whose spatial patterns of BOLD signal resembled regions of delayed perfusion depicted by dynamic susceptibility contrast MRI. These HICs were detected even in the presence of excessive patient motion, and disappeared following successful tissue reperfusion. The unique spatial and temporal features of HICs allowed them to be distinguished with high accuracy from other components in a user‐independent manner (area under the curve = 0.93, balanced accuracy = 0.90, sensitivity = 1.00, and specificity = 0.85). Our study therefore presents a new, noninvasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.

A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO₂ pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO₂ pressure: a breath-hold task to induce hypercapnia (CO₂ increase) and a cued deep breathing task to induce hypocapnia (CO₂ decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO₂ by systematically shifting the CO₂ regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO₂ and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.

Vector Phase Analysis Approach for Sleep Stage Classification: A Functional Near-Infrared Spectroscopy-Based Passive Brain-Computer Interface

A passive brain-computer interface (BCI) based upon functional near-infrared spectroscopy (fNIRS) brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex (DPFC) of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation (CORE) state was continuously measured. Vector phase analysis (VPA) was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features (mean oxyhemoglobin, signal peak, and the sum of peaks) along with six VPA features (trajectory slopes of VPA indices) were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects' data. Trajectory slopes of CORE vector magnitude and angle: m(|R|) and m(∠R) are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification.

Evidence of Age-Related Hemodynamic and Functional Connectivity Impairment: A Resting State fMRI Study

Purpose: To assess age-related changes in intrinsic functional brain connectivity and hemodynamics during adulthood in the context of the retrogenesis hypothesis, which states that the rate of age-related changes is higher in late-myelinating (prefrontal, lateral-posterior temporal) cerebrocortical areas as compared to early myelinating (parietal, occipital) regions. In addition, to examine the dependence of age-related changes upon concurrent subclinical depression symptoms which are common even in healthy aging. Methods: Sixty-four healthy adults (28 men) aged 23-79 years (mean 45.0, SD = 18.8 years) were examined. Resting-state functional MRI (rs-fMRI) time series were used to compute voxel-wise intrinsic connectivity contrast (ICC) maps reflecting the strength of functional connectivity between each voxel and the rest of the brain. We further used Time Shift Analysis (TSA) to estimate voxel-wise hemodynamic lead or lag for each of 22 ROIs from the automated anatomical atlas (AAL). Results: Adjusted for depression symptoms, gender and education level, reduced ICC with age was found primarily in frontal, temporal regions, and putamen, whereas the opposite trend was noted in inferior occipital cortices (p < 0.002). With the same covariates, increased hemodynamic lead with advancing age was found in superior frontal cortex and thalamus, with the opposite trend in inferior occipital cortex (p < 0.002). There was also evidence of reduced coupling between voxel-wise intrinsic connectivity and hemodynamics in the inferior parietal cortex. Conclusion: Age-related intrinsic connectivity reductions and hemodynamic changes were demonstrated in several regions-most of them part of DMN and salience networks-while impaired neurovascular coupling was, also, found in parietal regions. Age-related reductions in intrinsic connectivity were greater in anterior as compared to posterior cortices, in line with implications derived from the retrogenesis hypothesis. These effects were affected by self-reported depression symptoms, which also increased with age.

Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide

Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.

Hyperpolarized 129Xe Time-of-Flight MR Imaging of Perfusion and Brain Function

Perfusion measurements can provide vital information about the homeostasis of an organ and can therefore be used as biomarkers to diagnose a variety of cardiovascular, renal, and neurological diseases. Currently, the most common techniques to measure perfusion are ¹⁵O positron emission tomography (PET), xenon-enhanced computed tomography (CT), single photon emission computed tomography (SPECT), dynamic contrast enhanced (DCE) MRI, and arterial spin labeling (ASL) MRI. Here, we show how regional perfusion can be quantitively measured with magnetic resonance imaging (MRI) using time-resolved depolarization of hyperpolarized (HP) xenon-129 (¹²⁹Xe), and the application of this approach to detect changes in cerebral blood flow (CBF) due to a hemodynamic response in response to brain stimuli. The investigated HP ¹²⁹Xe Time-of-Flight (TOF) technique produced perfusion images with an average signal-to-noise ratio (SNR) of 10.35. Furthermore, to our knowledge, the first hemodynamic response (HDR) map was acquired in healthy volunteers using the HP ¹²⁹Xe TOF imaging. Responses to visual and motor stimuli were observed. The acquired HP TOF HDR maps correlated well with traditional proton blood oxygenation level-dependent functional MRI. Overall, this study expands the field of HP MRI with a novel dynamic imaging technique suitable for rapid and quantitative perfusion imaging.

The Effect of Scan Length on the Assessment of BOLD Delay in Ischemic Stroke

Objectives: To evaluate the impact of resting-state functional MRI scan length on the diagnostic accuracy, image quality and lesion volume estimation of BOLD delay maps used for brain perfusion assessment in acute ischemic stroke.

Methods: Sixty-three acute ischemic stroke patients received a 340 s resting-state functional MRI within 24 h of stroke symptom onset. BOLD delay maps were calculated from the full scan and four shortened versions (68 s, 136 s, 204 s, 272 s). The BOLD delay lesions on these maps were compared in terms of spatial overlap and volumetric agreement with the lesions derived from the full scans and with time-to-maximum (Tmax) lesions derived from DSC-MRI in a subset of patients (n = 10). In addition, the interpretability and quality of these maps were compared across different scan lengths using mixed models.

Results: Shortened BOLD delay scans showed a small volumetric bias (ranging from 0.05 to 5.3 mL; between a 0.13% volumetric underestimation and a 7.7% overestimation relative to the mean of the volumes, depending on scan length) compared to the full scan. Decreased scan length was associated with decreased spatial overlap with both the BOLD delay lesions derived from the full scans and with Tmax lesions. Only the two shortest scan lengths (68 and 136 s) were associated with substantially decreased interpretability, decreased structure clarity, and increased noisiness of BOLD delay maps.

Conclusions: BOLD delay maps derived from resting-state fMRI scans lasting 272 and 204 s provide sufficient diagnostic quality and adequate assessment of perfusion lesion volumes. Such shortened scans may be helpful in situations where quick clinical decisions need to be made.

Resting-state Functional Magnetic Resonance Imaging Identifies Cerebrovascular Reactivity Impairment in Patients With Arterial Occlusive Diseases: A Pilot Study

BACKGROUND

The development of noninvasive approaches for identifying hypoperfused brain tissue at risk is of major interest. Recently, the temporal-shift (TS) maps estimated from resting-state blood oxygenation level-dependent (BOLD) signals have been proposed for determining hemodynamic state.

OBJECTIVE

To examine the equivalency of the TS map and the cerebrovascular reactivity (CVR) map derived from acetazolamide-challenged single-photon emission computed tomography (SPECT) in identifying hemodynamic impairment in patients with arterial occlusive diseases.

METHODS

Twenty-three patients with arterial occlusive diseases who underwent SPECT were studied. With a recursive TS analysis of low-frequency fluctuation of the BOLD signal, a TS map relative to the global signal was created for each patient. The voxel-by-voxel correlation coefficient was calculated to examine the image similarity between TS and SPECT-based cerebral blood flow (CBF) or CVR maps in each patient. Furthermore, simple linear regression analyses were performed to examine the quantitative relationship between the TS of BOLD signals and CVR in each cerebrovascular territory.

RESULTS

The within-patient, voxel-by-voxel comparison revealed that the TS map was more closely correlated with SPECT-CVR map ([Z(r)] = 0.42 ± 0.18) than SPECT-CBF map ([Z(r)] = 0.058 ± 0.11; P < .001, paired t-test). The regression analysis showed a significant linear association between the TS of BOLD signals and CVR in the anterior circulation where the reduction of CVR was evident in the patient group.

CONCLUSION

BOLD TS analysis has potential as a noninvasive alternative to current methods based on CVR for identification of tissue at risk of ischemic stroke.

Non-invasive monitoring of longitudinal changes in cerebral hemodynamics in acute ischemic stroke using BOLD signal delay

Relative delays in blood-oxygen-level-dependent (BOLD) signal oscillations can be used to assess cerebral perfusion without using contrast agents. However, little is currently known about the utility of this method in detecting clinically relevant perfusion changes over time. We investigated the relationship between longitudinal BOLD delay changes, vessel recanalization, and reperfusion in 15 acute stroke patients with vessel occlusion examined within 24 h of symptom onset (D0) and one day later (D1). We created BOLD delay maps using time shift analysis of resting-state functional MRI data and quantified perfusion lesion volume changes (using the D1/D0 volume ratio) and severity changes (using a linear mixed model) over time. Between baseline and follow-up, BOLD delay lesions shrank (median D1/D0 ratio = 0.2, IQR = 0.03-0.7) and BOLD delay severity decreased (b = -4.4 s) in patients with recanalization, whereas they grew (median D1/D0 ratio = 1.47, IQR = 1.1-1.7) and became more severe (b = 4.3 s) in patients with persistent vessel occlusion. Clinically relevant changes in cerebral perfusion in early stroke can be detected using BOLD delay, making this non-invasive method a promising option for detecting tissue at risk of infarction and monitoring stroke patients following recanalization therapy.

Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals

Perfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the “perfusion lag structure,” a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S₀, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.

Erroneous Resting-State fMRI Connectivity Maps Due to Prolonged Arterial Arrival Time and How to Fix Them

In resting-state functional MRI (rs-fMRI), functional networks are assessed utilizing the temporal correlation between spontaneous blood oxygen level-dependent signal fluctuations of spatially remote brain regions. Recently, several groups have shown that temporal shifts are present in rs-fMRI maps in patients with cerebrovascular disease due to spatial differences in arterial arrival times, and that this can be exploited to map arrival times in the brain. This suggests that rs-fMRI connectivity mapping may be similarly sensitive to such temporal shifts, and that standard rs-fMRI analysis methods may fail to identify functional connectivity networks. To investigate this, we studied the default mode network (DMN) in Moyamoya disease patients and compared it with normal healthy volunteers. Our results show that using standard independent component analysis (ICA) and seed-based approaches, arterial arrival delays lead to inaccurate incomplete characterization of functional connectivity within the DMN in Moyamoya disease patients. Furthermore, we propose two techniques to correct these errors, for seed-based and ICA methods, respectively. Using these methods, we demonstrate that it is possible to mitigate the deleterious effects of arterial arrival time on the assessment of functional connectivity of the DMN. As these corrections have not been applied to the vast majority of >200 prior rs-fMRI studies in patients with cerebrovascular disease, we suggest that they be interpreted with great caution. Correction methods should be applied in any rs-fMRI connectivity study of subjects expected to have abnormally delayed arterial arrival times.

A Modified Encephalo-Duro-Synangiosis Technique Induced Neovascularization in Symptomatic Atherosclerotic Carotid Artery Occlusion: A Phase I trial

OBJECTIVE

To the best of our knowledge, the present study is the first to assess the safety and feasibility of a modified encephalo-galeo-duro-synangiosis operation in patients with atherosclerotic carotid artery occlusion.

METHODS

Eight patients who had experienced new ipsilateral cerebrovascular events after the diagnosis of carotid artery occlusion were recruited. To facilitate extracranial-to-intracranial collateralization, 5 or 6 burr holes were made, and the dura mater and arachnoid were opened. The patients were closely monitored for complications and underwent conventional angiography, magnetic resonance imaging, and perfusion-weighted magnetic resonance imaging at baseline and 1 year of follow-up. After 10 years, the patients who were still alive were interviewed and assessed for functional outcomes and neurological status.

RESULTS

No surgery-related adverse events were observed, apart from temporary headache and subcutaneous effusion. Four of six patients had developed an extracranial-to-intracranial collateral blood vessels on angiography, and these patients had no incident ischemic events during the follow-up period. During the long-term follow-up period (10 years), 3 patients had died. Of those living, 4 of the 5 patients reported total resolution of the symptoms, with no incident ischemic events. One patient still experienced disability from an ischemic stroke that occurred as a result of the 1-year follow-up angiography.

CONCLUSIONS

Encephalo-duro-galeo-synangiosis for symptomatic carotid occlusion seems to be safe and feasible and might be able to induce extracranial-to-intracranial collaterals in patients with carotid artery occlusion. Further studies are needed to define the optimal therapeutic window and yield of burr hole surgery in the treatment of symptomatic carotid occlusive disease as an adjuvant to extracranial-intracranial bypass.

One-step analysis of brain perfusion and function for acute stroke patients after reperfusion: A resting-state fMRI study

BACKGROUND

Resting-state functional magnetic resonance imaging (rs-fMRI) can noninvasively estimate the perfusion and function of the brain.

PURPOSE

To investigate the perfusion and functional status using rs-fMRI in acute ischemic stroke (AIS) patients after reperfusion therapy.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-five AIS patients who underwent dynamic susceptibility contrast (DSC) upon hospital admission and both rs-fMRI and DSC scans at 24 hours after reperfusion therapy.

FIELD STRENGTH/SEQUENCE

3T; DSC, rs-fMRI.

ASSESSMENT

The time delay of the blood oxygenation level-dependent (BOLD) signal was calculated using time-shift-analysis (TSA) and compared with the time to peak (TTP) derived from the DSC. For patients who exhibited partial or complete reperfusion in the supratentorial hemisphere, we quantified the function of different regions (healthy tissue, reperfused tissue, not reperfused tissue) by using three rs-fMRI measurements (functional connectivity, the amplitude of low-frequency fluctuation [ALFF] and regional homogeneity [ReHo]). Correlations between the functional measurements and modified Rankin Scale (mRS) scores were calculated.

STATISTICAL TESTS

Dice coefficient (DC) analysis, two-sample t-tests, Pearson correlation coefficient.

RESULTS

Twelve patients who exhibited complete reperfusion on their TTP maps showed no time-delayed areas on the TSA maps. For the remaining 13 patients with partial reperfusion (5/13) or no reperfusion (8/13) on the TTP maps, the TSA detected comparable time-delayed areas. Eleven out of 13 patients showed moderate to good overlap (mean DC, 0.58 ± 0.1) between the TTP and TSA results. Fourteen patients were chosen for functional analyses and most patients (12/14) showed abnormal functional connectivity in the reperfused regions. The reperfused and not reperfused tissues had lower mean ReHo values than those of the healthy tissue (both P < 0.001). The mRS scores showed negative correlation with mean ReHo values of reperfused region (R = -0.523, P = 0.027). DATA CONCLUSION: rs-fMRI might be a useful way to estimate both the perfusion and functional status for AIS patients after reperfusion therapy.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:221-229.

Non-invasive evaluation of cerebral perfusion in patients with transient ischemic attack: an fMRI study

Detection of hypoperfused tissue due to the ischemia is considered to be important in understanding the cerebral perfusion status and may be helpful in guiding therapeutic decisions for patients with transient ischemic attack (TIA). We hypothesized that the combination of two non-invasive fMRI techniques: resting-state BOLD-fMRI time-shift analysis (TSA) approach and 3D ASL, could detect the cerebral hemodynamic status in TIA patients noninvasively. From April 2015 to June 2016, 51 TIA patients were recruited in this study. We calculated the time delay between the resting-state BOLD signal at each voxel and the whole-brain signal using TSA approach and compared the results to CBF map derived from ASL. Out of the 51 patients, 24 patients with normal arrival time and CBF were in Stage 0; 14 patients who showed delayed arrival time and normal CBF which indicated elevated CBV were in Stage I; the other 13 patients who had both delayed arrival time and decreased CBF were in Stage II, the group average spatial overlap, i.e., Dice coefficient, of the two measurements was 0.55. Four patients in Stage 0 (17.4%), three patients in Stage I (23.1%) and five patients in Stage II (45.5%) suffered ischemic stroke or TIA symptoms in 1 year after MRI scan. The patients in Stage II was at highest risk of subsequent events when compared to other two stages. The combination of resting-state BOLD-fMRI and ASL hold the potential to noninvasively identify the hemodynamic status in TIA patients and help predict the risk of subsequent events.

Detecting perfusion deficit in Alzheimer's disease and mild cognitive impairment patients by resting-state fMRI

BACKGROUND

Vascular factors contributing to cerebral hypoperfusion are implicated in the risk of developing Alzheimer's disease (AD).

PURPOSE

To investigate the time-shift mapping created time-shift value of the brain by resting-state functional magnetic resonance imaging (rs-fMRI), and to determine the differences in time-shift value among AD, mild cognitive impairment (MCI), and normal control (NC) groups to better understand the disease.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-four AD, 24 MCI, and 24 age-matched NC participants.

FIELD STRENGTH/SEQUENCE

T₂ *-weighted single-shot echo-planar imaging sequence was performed at 3T. In addition, a T₁ -weighted fast spoiled gradient-echo sequence was acquired for coregistration.

ASSESSMENT

The brain time-shift value was determined from rs-fMRI-based blood oxygenation level-dependent (BOLD) signal in the three groups by time-shift mapping. The perfusion patterns were also investigated in the NC group.

STATISTICAL TESTS

One-way analysis of variance and chi-squared tests were used to compare demographic information. The normalized time-shift maps were analyzed in a second-level test using SPM8. All analyses were evaluated with a significance level of P < 0.05 after false discovery rate (FDR) correction.

RESULTS

The time-shift maps obtained from rs-fMRI are consistent with the cerebral blood supply atlas. Compared with NC, both MCI and AD groups had less early perfusion arrival areas among the whole brain. In the delayed time-shift value for the AD group, the areas were located in the bilateral precuneus, the sensory-motor cortex in the left hemisphere, and the bilateral calcarine sulcus, which were different from the MCI group (both P < 0.05, FDR corrected).

DATA CONCLUSION

The time-shift mapping method could detect perfusion deficits in AD and MCI noninvasively. The perfusion deficits detected by rs-fMRI may provide new insight for understanding the mechanism of neurodegeneration. Level of Evidence 2 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2019;49:1099-1104.

Alteration of Venous Drainage Route in Idiopathic Normal Pressure Hydrocephalus and Normal Aging

Idiopathic normal pressure hydrocephalus (iNPH) is a highly prevalent condition in the elderly population; however, the underlying pathophysiology in relation to the aging process remains unclear. To investigate the effect of removal of cerebrospinal fluid by lumbar “tap test” on the cerebral circulation in patients with iNPH, 14 patients with “probable” iNPH were studied using a novel blood tracking technique based on blood oxygenation level-dependent (BOLD) magnetic resonance signal intensity. By tracking the propagation of the low-frequency component of the BOLD signal, extended venous drainage times were observed in the periventricular region of the patients, which was reversed by tap test. Interestingly, the venous drainage time in the periventricular region exhibited an age-related prolongation in the healthy control group. Additional regression analyses involving 81 control subjects revealed a dissociation of deep and superficial venous systems with increasing age, presumably reflecting focal inefficiency in the deep system. Our results not only provide insights into the etiology of iNPH, but also point to a potential non-invasive biomarker for screening iNPH.

Acute single channel EEG predictors of cognitive function after stroke

BACKGROUND

Early and accurate identification of factors that predict post-stroke cognitive outcome is important to set realistic targets for rehabilitation and to guide patients and their families accordingly. However, behavioral measures of cognition are difficult to obtain in the acute phase of recovery due to clinical factors (e.g. fatigue) and functional barriers (e.g. language deficits). The aim of the current study was to test whether single channel wireless EEG data obtained acutely following stroke could predict longer-term cognitive function.

METHODS

Resting state Relative Power (RP) of delta, theta, alpha, beta, delta/alpha ratio (DAR), and delta/theta ratio (DTR) were obtained from a single electrode over FP1 in 24 participants within 72 hours of a first-ever stroke. The Montreal Cognitive Assessment (MoCA) was administered at 90-days post-stroke. Correlation and regression analyses were completed to identify relationships between 90-day cognitive function and electrophysiological data, neurological status, and demographic characteristics at admission.

RESULTS

Four acute qEEG indices demonstrated moderate to high correlations with 90-day MoCA scores: DTR (r = -0.57, p = 0.01), RP theta (r = 0.50, p = 0.01), RP delta (r = -0.47, p = 0.02), and DAR (r = -0.45, p = 0.03). Acute DTR (b = -0.36, p < 0.05) and stroke severity on admission (b = -0.63, p < 0.01) were the best linear combination of predictors of MoCA scores 90-days post-stroke, accounting for 75% of variance.

CONCLUSIONS

Data generated by a single pre-frontal electrode support the prognostic value of acute DAR, and identify DTR as a potential marker of post-stroke cognitive outcome. Use of single channel recording in an acute clinical setting may provide an efficient and valid predictor of cognitive function after stroke.

A Resilient, Non-neuronal Source of the Spatiotemporal Lag Structure Detected by BOLD Signal-Based Blood Flow Tracking

Recent evidence has suggested that blood oxygenation level-dependent (BOLD) signals convey information about brain circulation via low frequency oscillation of systemic origin (sLFO) that travels through the vascular structure ("lag mapping"). Prompted by its promising application in both physiology and pathology, we examined this signal component using multiple approaches. A total of 30 healthy volunteers were recruited to perform two reproducibility experiments at 3 Tesla using multiband echo planar imaging. The first experiment investigated the effect of denoising and the second was designed to study the effect of subject behavior on lag mapping. The lag map's intersession test-retest reproducibility and image contrast were both diminished by removal of either the neuronal or the non-neuronal (e.g., cardiac, respiratory) components by independent component analysis-based denoising, suggesting that the neurovascular coupling also comprises a part of the BOLD lag structure. The lag maps were, at the same time, robust against local perfusion increases due to visuomotor task and global changes in perfusion induced by breath-holding at the same level as the intrasession reliability. The lag structure was preserved after time-locked averaging to the visuomotor task and breath-holding events, while any preceding signal changes were canceled out for the visuomotor task, consistent with the passive effect of neurovascular coupling in the venous side of the vasculature. These findings support the current assumption that lag mapping primarily reflects vascular structure despite the presence of sLFO perturbation of neuronal or non-neuronal origin and, thus, emphasize the vascular origin of the lag map, encouraging application of BOLD-based blood flow tracking.