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One of the major findings from multimodal neuroimaging studies in the past decade is that the human brain is anatomically and functionally organized into large-scale networks. In resting state fMRI (rs-fMRI), spatial patterns emerge when temporal correlations between various brain regions are tallied, evidencing networks of ongoing intercortical cooperation. However, the dynamic structure governing the brain's spontaneous activity is far less understood due to the short and noisy nature of the rs-fMRI signal. Here, we develop a wavelet-based regularity analysis based on noise estimation capabilities of the wavelet transform to measure recurrent temporal pattern stability within the rs-fMRI signal across multiple temporal scales. The method consists of performing a stationary wavelet transform to preserve signal structure, followed by construction of "lagged" subsequences to adjust for correlated features, and finally the calculation of sample entropy across wavelet scales based on an "objective" estimate of noise level at each scale. We found that the brain's default mode network (DMN) areas manifest a higher level of irregularity in rs-fMRI time series than rest of the brain. In 25 aged subjects with mild cognitive impairment and 25 matched healthy controls, wavelet-based regularity analysis showed improved sensitivity in detecting changes in the regularity of rs-fMRI signals between the two groups within the DMN and executive control networks, compared with standard multiscale entropy analysis. Wavelet-based regularity analysis based on noise estimation capabilities of the wavelet transform is a promising technique to characterize the dynamic structure of rs-fMRI as well as other biological signals.

BackgroundNeuroimaging studies can shed light on the neurobiological underpinnings of autism spectrum disorders (ASD). Studies of the resting brain have shown both altered baseline metabolism from PET/SPECT and altered functional connectivity (FC) of intrinsic brain networks based on resting-state fMRI. To date, however, no study has investigated these two physiological parameters of resting brain function jointly, or explored the relationship between these measures and ASD symptom severity.MethodsHere, we used pseudo-continuous arterial spin labeling with 3D background-suppressed GRASE to assess resting cerebral blood flow (CBF) and FC in 17 youth with ASD and 22 matched typically developing (TD) children.ResultsA pattern of altered resting perfusion was found in ASD versus TD children including frontotemporal hyperperfusion and hypoperfusion in the dorsal anterior cingulate cortex. We found increased local FC in the anterior module of the default mode network (DMN) accompanied by decreased CBF in the same area. In our cohort, both alterations were associated with greater social impairments as assessed with the Social Responsiveness Scale (SRS-total T scores). While FC was correlated with CBF in TD children, this association between FC and baseline perfusion was disrupted in children with ASD. Furthermore, there was reduced long-range FC between anterior and posterior modules of the DMN in children with ASD.ConclusionTaken together, the findings of this study--the first to jointly assess resting CBF and FC in ASD--highlight new avenues for identifying novel imaging markers of ASD symptomatology.

Simultaneous multi-slice (SMS) or multiband (MB) imaging has recently been attempted for arterial spin labeled (ASL) perfusion MRI in conjunction with echo-planar imaging (EPI) readout. It was found that SMS-EPI can reduce the T1 relaxation effect of the label and improve image coverage and resolution with little penalty in signal-to-noise ratio (SNR). However, EPI still suffers from geometric distortion and signal dropout from field inhomogeneity effects especially at high and ultrahigh magnetic fields. Here we present a novel scheme for achieving high fidelity distortion-free quantitative perfusion imaging by combining pseudo-continuous ASL (pCASL) with SMS Turbo-FLASH (TFL) readout at both 3 and 7 T. Bloch equation simulation was performed to characterize and optimize the TFL-based pCASL perfusion signal. Two MB factors (3 and 5) were implemented in SMS-TFL pCASL and compared with standard 2D TFL and EPI pCASL sequences. The temporal SNR of SMS-TFL pCASL relative to that of standard TFL pCASL was 0.76 ± 0.10 and 0.74 ± 0.11 at 7 T and 0.70 ± 0.05 and 0.65 ± 0.05 at 3T for MB factor of 3 and 5, respectively. By implementing background suppression in conjunction with SMS-TFL at 3T, the relative temporal SNR improved to 0.84 ± 0.09 and 0.79 ± 0.10 for MB factor of 3 and 5, respectively. Compared to EPI pCASL, significantly increased temporal SNR (p

IntroductionA main obstacle that impedes standardized clinical and research applications of arterial spin labeling (ASL), is the substantial differences between the commercial implementations of ASL from major MRI vendors. In this study, we compare a single identical 2D gradient-echo EPI pseudo-continuous ASL (PCASL) sequence implemented on 3T scanners from three vendors (General Electric Healthcare, Philips Healthcare and Siemens Healthcare) within the same center and with the same subjects.Material and methodsFourteen healthy volunteers (50% male, age 26.4±4.7years) were scanned twice on each scanner in an interleaved manner within 3h. Because of differences in gradient and coil specifications, two separate studies were performed with slightly different sequence parameters, with one scanner used across both studies for comparison. Reproducibility was evaluated by means of quantitative cerebral blood flow (CBF) agreement and inter-session variation, both on a region-of-interest (ROI) and voxel level. In addition, a qualitative similarity comparison of the CBF maps was performed by three experienced neuro-radiologists.ResultsThere were no CBF differences between vendors in study 1 (p>0.1), but there were CBF differences of 2-19% between vendors in study 2 (p0.1) but one of the ROIs (p

Simultaneous multi-slice (SMS) or multiband (MB) imaging has recently been attempted for arterial spin labeled (ASL) perfusion MRI in conjunction with echo-planar imaging (EPI) readout. It was found that SMS-EPI can reduce the T1 relaxation effect of the label and improve image coverage and resolution with little penalty in signal-to-noise ratio (SNR). However, EPI still suffers from geometric distortion and signal dropout from field inhomogeneity effects especially at high and ultrahigh magnetic fields. Here we present a novel scheme for achieving high fidelity distortion-free quantitative perfusion imaging by combining pseudo-continuous ASL (pCASL) with SMS Turbo-FLASH (TFL) readout at both 3 and 7 T. Bloch equation simulation was performed to characterize and optimize the TFL-based pCASL perfusion signal. Two MB factors (3 and 5) were implemented in SMS-TFL pCASL and compared with standard 2D TFL and EPI pCASL sequences. The temporal SNR of SMS-TFL pCASL relative to that of standard TFL pCASL was 0.76 ± 0.10 and 0.74 ± 0.11 at 7 T and 0.70 ± 0.05 and 0.65 ± 0.05 at 3T for MB factor of 3 and 5, respectively. By implementing background suppression in conjunction with SMS-TFL at 3T, the relative temporal SNR improved to 0.84 ± 0.09 and 0.79 ± 0.10 for MB factor of 3 and 5, respectively. Compared to EPI pCASL, significantly increased temporal SNR (p

The purpose of this study was to investigate the relationship between hyperperfusion and hemorrhagic transformation (HT) in acute ischemic stroke (AIS). Pseudo-continuous arterial spin labeling (ASL) with background suppressed 3D GRASE was performed during routine clinical magnetic resonance imaging (MRI) on AIS patients at various time points. Arterial spin labeling cerebral blood flow (CBF) maps were visually inspected for the presence of hyperperfusion. Hemorrhagic transformation was followed during hospitalization and was graded on gradient recalled echo (GRE) scans into hemorrhagic infarction (HI) and parenchymal hematoma (PH). A total of 361 ASL scans were collected from 221 consecutive patients with middle cerebral artery stroke from May 2010 to September 2013. Hyperperfusion was more frequently detected posttreatment (odds ratio (OR) = 4.8, 95% confidence interval (CI) 2.5 to 8.9, P < 0.001) and with high National Institutes of Health Stroke Scale (NIHSS) scores at admission (P

Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2 × 2 × 2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905 ± 0.033 between-sessions; 0.885 ± 0.052 between-scanners) than ASL (0.545 ± 0.048; 0.575 ± 0.059). Nevertheless, ASL provided highly reproducible (0.955 ± 0.021; 0.970 ± 0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

Rigorous statistical analysis of multimodal imaging datasets is challenging. Mass-univariate methods for extracting correlations between image voxels and outcome measurements are not ideal for multimodal datasets, as they do not account for interactions between the different modalities. The extremely high dimensionality of medical images necessitates dimensionality reduction, such as principal component analysis (PCA) or independent component analysis (ICA). These dimensionality reduction techniques, however, consist of contributions from every region in the brain and are therefore difficult to interpret. Recent advances in sparse dimensionality reduction have enabled construction of a set of image regions that explain the variance of the images while still maintaining anatomical interpretability. The projections of the original data on the sparse eigenvectors, however, are highly collinear and therefore difficult to incorporate into multi-modal image analysis pipelines. We propose here a method for clustering sparse eigenvectors and selecting a subset of the eigenvectors to make interpretable predictions from a multi-modal dataset. Evaluation on a publicly available dataset shows that the proposed method outperforms PCA and ICA-based regressions while still maintaining anatomical meaning. To facilitate reproducibility, the complete dataset used and all source code is publicly available.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.

Magnetic resonance imaging (MRI) captures the dynamics of brain development with multiple modalities that quantify both structure and function. These measurements may yield valuable insights into the neural patterns that mark healthy maturation or that identify early risk for psychiatric disorder. The Pediatric Template of Brain Perfusion (PTBP) is a free and public neuroimaging resource that will help accelerate the understanding of childhood brain development as seen through the lens of multiple modality neuroimaging and in relation to cognitive and environmental factors. The PTBP uses cross-sectional and longitudinal MRI to quantify cortex, white matter, resting state functional connectivity and brain perfusion, as measured by Arterial Spin Labeling (ASL), in 120 children 7-18 years of age. We describe the PTBP and show, as a demonstration of validity, that global summary measurements capture the trajectories that demarcate critical turning points in brain maturation. This novel resource will allow a more detailed understanding of the network-level, structural and functional landmarks that are obtained during normal adolescent brain development.

This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.

We present RIPMMARC (Rotation Invariant Patch-based Multi-Modality Analysis aRChitecture), a flexible and widely applicable method for extracting information unique to a given modality from a multi-modal data set. We use RIPMMARC to improve the interpretation of arterial spin labeling (ASL) perfusion images by removing the component of perfusion that is predicted by the underlying anatomy. Using patch-based, rotation invariant descriptors derived from the anatomical image, we learn a predictive relationship between local neuroanatomical structure and the corresponding perfusion image. This relation allows us to produce an image of perfusion that would be predicted given only the underlying anatomy and a residual image that represents perfusion information that cannot be predicted by anatomical features. Our learned structural features are significantly better at predicting brain perfusion than tissue probability maps, which are the input to standard partial volume correction techniques. Studies in test-retest data show that both the anatomically predicted and residual perfusion signals are highly replicable for a given subject. In a pediatric population, both the raw perfusion and structurally predicted images are tightly linked to age throughout adolescence throughout the brain. Interestingly, the residual perfusion also shows a strong correlation with age in selected regions including the hippocampi (corr = 0.38, p-value

Coronary artery disease (CAD) poses a risk to the cerebrovascular function of older adults and has been linked to impaired cognitive abilities. Using magnetic resonance perfusion imaging, we investigated changes in resting cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) to hypercapnia in 34 CAD patients and 21 age-matched controls. Gray matter volume (GMV) images were acquired and used as a confounding variable to separate changes in structure from function. Compared to healthy controls, CAD patients demonstrated reduced CBF in the superior frontal, anterior cingulate (AC), insular, pre- and post-central gyri, middle temporal, and superior temporal regions. Subsequent analysis of these regions demonstrated decreased CVR in the AC, insula, post-central and superior frontal regions. Except in the superior frontal and precentral regions, regional reductions in CBF and CVR were identified in brain areas where no detectable reductions in GMV were observed, demonstrating that these vascular changes were independent of brain atrophy. Because aerobic fitness training can improve brain function, potential changes in regional CBF were investigated in the CAD patients after completion of a 6-months exercise-based cardiac rehabilitation program. Increased CBF was observed in the bilateral AC, as well as recovery of CBF in the dorsal aspect of the right AC, where the magnitude of increased CBF was roughly equal to the reduction in CBF at baseline compared to controls. These exercise-related improvements in CBF in the AC is intriguing given the role of this area in cognitive processing and regulation of cardiovascular autonomic control.

PurposeTo explore the feasibility of 2D and 3D golden-angle radial acquisition strategies in conjunction with k-space weighted image contrast (KWIC) temporal filtering to achieve noncontrast enhanced dynamic MRA (dMRA) with high spatial resolution, low streaking artifacts and high temporal fidelity.MethodsSimulations and in vivo examinations in eight normal volunteers and an arteriovenous malformation patient were carried out. Both 2D and 3D golden angle radial sequences, preceded by spin tagging, were used for dMRA of the brain. The radial dMRA data were temporally filtered using the KWIC strategy and compared with matched standard Cartesian techniques.ResultsThe 2D and 3D dynamic MRA image series acquired with the proposed radial techniques demonstrated excellent image quality without discernible temporal blurring compared with standard Cartesian based approaches. The image quality of radial dMRA was equivalent to or higher than that of Cartesian dMRA by visual inspection. A reduction factor of up to 10 and 3 in scan time was achieved for 2D and 3D radial dMRA compared with the Cartesian-based counterparts.ConclusionThe proposed 2D and 3D radial dMRA techniques demonstrated image quality comparable or even superior to those obtained with standard Cartesian methods, but within a fraction of the scan time.

MRI and PET provide complementary information for studying brain function. While the potential use of simultaneous MRI/PET for clinical diagnostic and disease staging has been demonstrated recently; the biological relevance of concurrent functional MRI-PET brain imaging to dissect neurochemically distinct components of the blood oxygenation level dependent (BOLD) fMRI signal has not yet been shown. We obtained sixteen fMRI-PET data sets from eight healthy volunteers. Each subject participated in randomized order in a pain scan and a control (nonpainful pressure) scan on the same day. Dynamic PET data were acquired with an opioid radioligand, [(11)C]diprenorphine, to detect endogenous opioid releases in response to pain. BOLD fMRI data were collected at the same time to capture hemodynamic responses. In this simultaneous human fMRI-PET imaging study, we show co-localized responses in thalamus and striatum related to pain processing, while modality specific brain networks were also found. Co-localized fMRI and PET signal changes in the thalamus were positively correlated suggesting that pain-induced changes in opioid neurotransmission contribute a significant component of the fMRI signal change in this region. Simultaneous fMRI-PET provides unique opportunities allowing us to relate specific neurochemical events to functional hemodynamic activation and to investigate the impacts of neurotransmission on neurovascular coupling of the human brain in vivo.

The effect of high dose isoflurane on cerebral blood flow (CBF) was investigated in adult macaque monkeys receiving 1% to 2% isoflurane with the pseudo continuous arterial-spin-labeling (pCASL) MRI technique. High concentration (2%) of isoflurane resulted in significant increase in the mean CBF of the global, cortical, subcortical regions and the regional CBF in all subcortical structures and most cortical structures (such as motor cortex, anterior cingulate cortex, but not media prefrontal cortex). In addition, the changes of regional CBF in the affected regions correlated linearly with increasing isoflurane concentrations. The study demonstrates region-specific CBF abnormal increase in adult macaque monkeys under high dose (2%) isoflurane and suggests that the brain functionality in the corresponding structures may be affected and need to be taken consideration in either human or non-human primate neuroimaging studies.

Stress is a constant characteristic of everyday life in our society, playing a role in triggering several chronic disorders. Therefore, there is an ongoing need to develop new methods in order to manage stress reactions. The regulatory function of right medial-prefrontal cortex (mPFC) is frequently reported by imaging studies during psychosocial stress situations. Here, we examined the effects of inhibitory and excitatory preconditioning stimulation via cathodal and anodal transcranial direct current stimulation (tDCS) on psychosocial stress related behavioral indicators and physiological factors, including the cortisol level in the saliva and changes in brain perfusion. Twenty minutes real or sham tDCS was applied over the right mPFC of healthy subjects before the performance of the Trier Social Stress Test (TSST). Regional cerebral blood flow (rCBF) was measured during stimulation and after TSST, using pseudo-continuous arterial spin labeling (pCASL). Comparing the effect of the different stimulation conditions, during anodal stimulation we found higher rCBF in the right mPFC, compared to the sham and in the right amygdala, superior PFC compared to the cathodal condition. Salivary cortisol levels showed a decrease in the anodal and increase in cathodal groups after completion of the TSST. The behavioral stress indicators indicated the increase of stress level, however, did not show any significant differences among groups. In this study we provide the first insights into the neuronal mechanisms mediating psychosocial stress responses by prefrontal tDCS.

In this paper, we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects.

The present study explored multi-scale entropy (MSE) analysis to investigate the entropy of resting state fMRI signals across multiple time scales. MSE analysis was developed to distinguish random noise from complex signals since the entropy of the former decreases with longer time scales while the latter signal maintains its entropy due to a "self-resemblance" across time scales. A long resting state BOLD fMRI (rs-fMRI) scan with 1000 data points was performed on five healthy young volunteers to investigate the spatial and temporal characteristics of entropy across multiple time scales. A shorter rs-fMRI scan with 240 data points was performed on a cohort of subjects consisting of healthy young (age 23 ± 2 years, n = 8) and aged volunteers (age 66 ± 3 years, n = 8) to investigate the effect of healthy aging on the entropy of rs-fMRI. The results showed that MSE of gray matter, rather than white matter, resembles closely that of f (-1) noise over multiple time scales. By filtering out high frequency random fluctuations, MSE analysis is able to reveal enhanced contrast in entropy between gray and white matter, as well as between age groups at longer time scales. Our data support the use of MSE analysis as a validation metric for quantifying the complexity of rs-fMRI signals.

Diffusion tensor imaging is widely used in brain connectivity research. As more and more studies recruit large numbers of subjects, it is important to design registration methods which are not only theoretically rigorous, but also computationally efficient. However, the requirement of reorienting diffusion tensors complicates and considerably slows down registration procedures, due to the correlated impacts of registration forces at adjacent voxel locations. Based on the diffeomorphic Demons algorithm (Vercauteren , 2009), we propose a fast local trust region algorithm for handling inseparable registration forces for quadratic energy functions. The method guarantees that, at any time and at any voxel location, the velocity is always within its local trust region. This local regularization allows efficient calculation of the transformation update with numeric integration instead of completely solving a large linear system at every iteration. It is able to incorporate exact reorientation and regularization into the velocity optimization, and preserve the linear complexity of the diffeomorphic Demons algorithm. In an experiment with 84 diffusion tensor images involving both pair-wise and group-wise registrations, the proposed algorithm achieves better registration in comparison with other methods solving large linear systems (Yeo , 2009). At the same time, this algorithm reduces the computation time and memory demand tenfold.

ObjectivesTo present a multi-delay pseudo-continuous ASL (pCASL) protocol that offers simultaneous measurements of cerebral blood flow (CBF) and arterial transit time (ATT), and to study correlations between multi-delay pCASL and CT perfusion in moyamoya disease.MethodsA 4 post-labeling delay (PLD) pCASL protocol was applied on 17 patients with moyamoya disease who also underwent CT perfusion imaging. ATT was estimated using the multi-delay protocol and included in the calculation of CBF. ASL and CT perfusion images were rated for lesion severity/conspicuity. Pearson correlation coefficients were calculated across voxels between the two modalities in grey and white matter of each subject respectively and between normalized mean values of ASL and CT perfusion measures in major vascular territories.ResultsSignificant associations between ASL and CT perfusion were detected using subjective ratings, voxel-wise analysis in grey and white matter and region of interest (ROI)-based analysis of normalized mean perfusion. The correlation between ASL CBF and CT perfusion was improved using the multi-delay pCASL protocol compared to CBF acquired at a single PLD of 2 s (P

PurposeTo investigate the reliability and accuracy of two pseudo-continuous arterial spin labeling (pCASL) sequences, using two-dimensional (2D) gradient-echo echo planar imaging (EPI) and 3D gradient and spin echo (GRASE) as the readout, respectively.Materials and methodsEach sequence was performed twice 4 weeks apart on six normal control subjects, six elderly subjects with mild cognitive impairment (MCI), and one participant with Alzheimer's disease (AD). Eight of these subjects also underwent H2 (15) O positron emission tomography (PET) scans on the same day or proximal to their second MRI scan. The longitudinal repeatability of EPI and GRASE pCASL were evaluated with the intraclass correlation coefficient (ICC) and within-subject coefficient of variation (wsCV).ResultsThe ICCs of global perfusion measurements were 0.697 and 0.413 for GRASE and EPI based pCASL respectively. GRASE pCASL also demonstrated a higher longitudinal repeatability for regional perfusion measurements across 24 regions-of-interests (ICC = 0.707; wsCV = 10.9%) compared with EPI pCASL (ICC = 0.362; wsCV = 15.3%). When compared with PET, EPI pCASL showed a higher degree of spatial correlation with PET than GRASE pCASL, although the difference was not statistically significant.ConclusionThe 3D GRASE pCASL offers better repeatability than 2D EPI pCASL, thereby may provide a reliable imaging marker for the evaluation of disease progression and treatment effects in MCI and early AD subjects.

PurposeThe goal of this study was to introduce a new noncontrast enhanced 4D dynamic MR angiography (dMRA) technique termed multibolus TrueFISP-based spin tagging with alternating radiofrequency (TrueSTAR).MethodsMultibolus TrueFISP-based spin tagging with alternating radiofrequency was developed by taking advantage of the phenomenon that the steady-state signal of TrueFISP is minimally disturbed by periodically inserted magnetization preparations (e.g., spin tagging) that are sandwiched by two α/2 RF pulses. Both theoretical analysis and experimental studies were carried out to optimize the proposed method which was compared with both pulsed and pseudo-continuous arterial spin labeling-based dMRA in healthy volunteers. Optimized multibolus dMRA was also applied in a patient with arteriovenous malformation to demonstrate its potential clinical utility.ResultsMultibolus dMRA offered a prolonged tagging bolus compared to the standard single-bolus dMRA, and allowed improved visualization of the draining veins in the arteriovenous malformation patient. Compared to pseudo-continuous arterial spin labeling-based dMRA, multibolus dMRA provided visualization of the full passage of the labeled blood with the flexibility for both static and dynamic magnetic resonance angiography.ConclusionBy combining the benefits of pulsed and pseudo-continuous arterial spin labeling-based dMRA, multibolus TrueFISP-based spin tagging with alternating radiofrequency can prolong and enhance the tagging bolus without sacrificing imaging speed or temporal resolution.

This study examined the relationship of γ-aminobutyric acid (GABA) and glutamate levels from the anterior and posterior cingulates (AC and PC) with cerebral blood flow (CBF) at rest. (1)H magnetic resonance spectroscopy measurements in the AC and PC and pseudo-continuous arterial spin labeling data were acquired from 10 healthy controls. GABA levels from the AC were strongly inversely correlated with global (whole-brain) CBF (r=-0.91, p=0.0015). GABA levels from the PC and glutamate levels from both regions were not significantly correlated with CBF. We hypothesize that GABA-mediated inhibition of AC activation of the locus coeruleus-norepinephrine pathway may influence global CBF.

Functional magnetic resonance imaging (fMRI) in the resting state, particularly fMRI based on the blood-oxygenation level-dependent (BOLD) signal, has been extensively used to measure functional connectivity in the brain. However, the mechanisms of vascular regulation that underlie the BOLD fluctuations during rest are still poorly understood. In this work, using dual-echo pseudo-continuous arterial spin labeling and MR angiography (MRA), we assess the spatio-temporal contribution of cerebral blood flow (CBF) to the resting-state BOLD signals and explore how the coupling of these signals is associated with regional vasculature. Using a general linear model analysis, we found that statistically significant coupling between resting-state BOLD and CBF fluctuations is highly variable across the brain, but the coupling is strongest within the major nodes of established resting-state networks, including the default-mode, visual, and task-positive networks. Moreover, by exploiting MRA-derived large vessel (macrovascular) volume fraction, we found that the degree of BOLD-CBF coupling significantly decreased as the ratio of large vessels to tissue volume increased. These findings suggest that the portion of resting-state BOLD fluctuations at the sites of medium-to-small vessels (more proximal to local neuronal activity) is more closely regulated by dynamic regulations in CBF, and that this CBF regulation decreases closer to large veins, which are more distal to neuronal activity.

BackgroundUnilateral ischemic stroke disrupts the well balanced interactions within bilateral cortical networks. Restitution of interhemispheric balance is thought to contribute to post-stroke recovery. Longitudinal measurements of cerebral blood flow (CBF) changes might act as surrogate marker for this process.ObjectiveTo quantify longitudinal CBF changes using arterial spin labeling MRI (ASL) and interhemispheric balance within the cortical sensorimotor network and to assess their relationship with motor hand function recovery.MethodsLongitudinal CBF data were acquired in 23 patients at 3 and 9 months after cortical sensorimotor stroke and in 20 healthy controls using pulsed ASL. Recovery of grip force and manual dexterity was assessed with tasks requiring power and precision grips. Voxel-based analysis was performed to identify areas of significant CBF change. Region-of-interest analyses were used to quantify the interhemispheric balance across nodes of the cortical sensorimotor network.ResultsDexterity was more affected, and recovered at a slower pace than grip force. In patients with successful recovery of dexterous hand function, CBF decreased over time in the contralesional supplementary motor area, paralimbic anterior cingulate cortex and superior precuneus, and interhemispheric balance returned to healthy control levels. In contrast, patients with poor recovery presented with sustained hypoperfusion in the sensorimotor cortices encompassing the ischemic tissue, and CBF remained lateralized to the contralesional hemisphere.ConclusionsSustained perfusion imbalance within the cortical sensorimotor network, as measured with task-unrelated ASL, is associated with poor recovery of dexterous hand function after stroke. CBF at rest might be used to monitor recovery and gain prognostic information.

Resting-state brain activity has been investigated extensively using BOLD contrast. However, BOLD signal represents the combined effects of multiple physiological processes and its spatial localization is less accurate than that of cerebral blood flow and volume (CBF and CBF, respectively). In this study, we demonstrate that resting-state brain activity can be reliably detected by spontaneous fluctuations of CBV-weighted signal using whole-brain gradient and spin echo (GRASE) based vascular space occupancy (VASO) imaging. Specifically, using independent component analysis, intrinsic brain networks, including default mode, salience, executive control, visual, auditory, and sensorimotor networks were revealed robustly by the VASO technique. We further demonstrate that task-evoked VASO signal aligned well with expected gray matter areas, while blood-oxygenation level dependent (BOLD) signal extended outside of these areas probably due to their different spatial specificity. The improved spatial localization of VASO is consistent with previous studies using animal models. Moreover, we showed that the 3D-GRASE VASO images had reduced susceptibility-induced signal voiding, compared to the BOLD technique. This is attributed to the fact that VASO does not require T2* weighting, thus the acquisition can use a shorter TE and can employ spin-echo scheme. Consequently VASO-based functional connectivity signals were well preserved in brain regions that tend to suffer from signal loss and geometric distortion in BOLD, such as orbital prefrontal cortex. Our study suggests that 3D-GRASE VASO imaging, with its improved spatial specificity and less sensitivity to susceptibility artifacts, may have advantages in resting-state fMRI studies.

To determine how arterial spin labeling (ASL) measured perfusion relates to baseline metabolism, we compared resting state cerebral perfusion using pseudo-continuous ASL and cerebral glucose metabolism using (18)F-FDG PET in 20 normal volunteers. Greater regional metabolism relative to perfusion was observed in the putamen, orbitofrontal and temporal lobes, whereas perfusion was relatively higher in the hippocampus and insula. In a region of interest analysis limited to gray matter, the overall mean correlation between perfusion and metabolism across voxels was r=0.43 with considerable regional variability. Cross-voxel correlations between relative perfusion and metabolism in mean ASL and PET images of all 20 subjects were the highest in the striatum (caudate: r=0.78; putamen: r=0.81), and the lowest in medial temporal structures (amygdala: r=0.087; hippocampus: r=-0.26). Correlations between mean relative perfusion and metabolism across 20 subjects were the highest in the striatum (caudate: r=0.76; putamen: r=0.58), temporal lobe (r=0.59), and frontal lobe (r=0.52), but very poor in all other structures (r

To determine how arterial spin labeling (ASL) measured perfusion relates to baseline metabolism, we compared resting state cerebral perfusion using pseudo-continuous ASL and cerebral glucose metabolism using (18)F-FDG PET in 20 normal volunteers. Greater regional metabolism relative to perfusion was observed in the putamen, orbitofrontal and temporal lobes, whereas perfusion was relatively higher in the hippocampus and insula. In a region of interest analysis limited to gray matter, the overall mean correlation between perfusion and metabolism across voxels was r=0.43 with considerable regional variability. Cross-voxel correlations between relative perfusion and metabolism in mean ASL and PET images of all 20 subjects were the highest in the striatum (caudate: r=0.78; putamen: r=0.81), and the lowest in medial temporal structures (amygdala: r=0.087; hippocampus: r=-0.26). Correlations between mean relative perfusion and metabolism across 20 subjects were the highest in the striatum (caudate: r=0.76; putamen: r=0.58), temporal lobe (r=0.59), and frontal lobe (r=0.52), but very poor in all other structures (r

Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

Information on renal perfusion is essential for the diagnosis and prognosis of kidney function. Quantification using gadolinium chelates is limited as a result of filtration through renal glomeruli and safety concerns in patients with kidney dysfunction. Arterial spin labeling MRI is a noninvasive technique for perfusion quantification that has been applied to humans and animals. However, because of the low sensitivity and vulnerability to motion and susceptibility artifacts, its application to mice has been challenging. In this article, mouse renal perfusion was studied using flow-sensitive alternating inversion recovery at 7 T. Good perfusion image quality was obtained with spin-echo echo-planar imaging after controlling for respiratory, susceptibility and fat artifacts by triggering, high-order shimming and water excitation, respectively. High perfusion was obtained in the renal cortex relative to the medulla, and signal was absent in scans carried out post mortem. Cortical perfusion increased from 397 ± 36 (mean ± standard deviation) to 476 ± 73 mL/100 g/min after switching from 100% oxygen to carbogen with 95% oxygen and 5% carbon dioxide. The perfusion in the medulla was 2.5 times lower than that in the cortex and changed from 166 ± 41 mL/100 g/min under oxygen to 203 ± 40 mL/100 g/min under carbogen. T1 decreased in both the cortex (from 1570 ± 164 to 1377 ± 72 ms, p

Obstructive sleep apnea (OSA) is a condition characterized by upper airway muscle atonia with continued diaphragmatic efforts, resulting in repeated airway obstructions, periods of intermittent hypoxia, large thoracic pressure changes, and substantial shifts in arterial pressure with breathing cessation and resumption. The hypoxic exposure and hemodynamic changes likely induce the structural and functional deficits found in multiple brain areas, as shown by magnetic resonance imaging (MRI) procedures. Altered cerebral blood flow (CBF) may contribute to these localized deficits; thus, we examined regional CBF, using arterial spin labeling procedures, in 11 OSA (age, 49.1±12.2 years; 7 male) and 16 control subjects (42.3±10.2 years; 6 male) with a 3.0-Tesla MRI scanner. CBF maps were calculated, normalized to a common space, and regional CBF values across the brain quantified. Lowered CBF values emerged near multiple bilateral brain sites in OSA, including the corticospinal tracts, superior cerebellar peduncles, and pontocerebellar fibers. Lateralized, decreased CBF appeared near the left inferior cerebellar peduncles, left tapetum, left dorsal fornix/stria terminalis, right medial lemniscus, right red nucleus, right midbrain, and midline pons. Regional CBF values in OSA are significantly reduced in major sensory and motor fiber systems and motor regulatory sites, especially in structures mediating motor coordination; those reductions are often lateralized. The asymmetric CBF declines in motor regulatory areas may contribute to loss of coordination between upper airway and diaphragmatic musculature, and lead to further damage in the syndrome.

PurposeThis study aimed to quantitatively investigate two main magnetization transfer effects at low B1: the nuclear Overhauser enhancement (NOE) and amide proton transfer in the human brain at 7 T.MethodsThe magnetization transfer effects in the human brain were characterized using a four-pool proton model, which consisted of bulk water, macromolecules, an amide group of mobile proteins and peptides, and NOE-related protons resonating upfield. The pool sizes, exchange rates, and relaxation times of these proton pools were investigated quantitatively by fitting, and the net signals of amide proton transfer and NOE were simulated based on the fitted parameters.ResultsThe results showed that the four-pool model fitted the experimental data quite well, and the NOE effects in human brain at 7 T had a broad spectrum distribution. The NOE effects peaked at a B1 of ∼ 1-1.4 μT and were significantly stronger in the white matter than in the gray matter, corresponding to a pool-size ratio ∼ 2:1. As the amide proton transfer effect was relatively small compared with the NOE effects, magnetization transfer asymmetry analysis yielded an NOE-dominated contrast in the healthy human brain in this range of B1.ConclusionThese findings are important to identify the source of NOE effects and to quantify amide proton transfer effects in human brain at 7 T.

We implemented pseudo-continuous ASL (pCASL) with 2D and 3D balanced steady state free precession (bSSFP) readout for mapping blood flow in the human brain, retina, and kidney, free of distortion and signal dropout, which are typically observed in the most commonly used echo-planar imaging acquisition. High resolution functional brain imaging in the human visual cortex was feasible with 3D bSSFP pCASL. Blood flow of the human retina could be imaged with pCASL and bSSFP in conjunction with a phase cycling approach to suppress the banding artifacts associated with bSSFP. Furthermore, bSSFP based pCASL enabled us to map renal blood flow within a single breath hold. Control and test-retest experiments suggested that the measured blood flow values in retina and kidney were reliable. Because there is no specific imaging tool for mapping human retina blood flow and the standard contrast agent technique for mapping renal blood flow can cause problems for patients with kidney dysfunction, bSSFP based pCASL may provide a useful tool for the diagnosis of retinal and renal diseases and can complement existing imaging techniques.

PurposeTo explore the use of approximate entropy (ApEn) as an index of the complexity and the synchronicity of resting state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in normal aging and cognitive decline associated with familial Alzheimer's disease (fAD).Materials and methodsResting state BOLD fMRI data were acquired at 3T from two independent cohorts of subjects consisting of healthy young (age 23 ± 2 years, n = 8) and aged volunteers (age 66 ± 3 years, n = 8), as well as 22 fAD associated subjects (14 mutation carriers, age 41.2 ± 15.8 years; and eight nonmutation carrying family members, age 28.8 ± 5.9 years). Mean ApEn values were compared between the two age groups and correlated with cognitive performance in the fAD group. Cross-ApEn (C-ApEn) was further calculated to assess the asynchrony between precuneus and the rest of the brain.ResultsComplexity of brain activity measured by mean ApEn in gray and white matter decreased with normal aging. In the fAD group, cognitive impairment was associated with decreased mean ApEn in gray matter as well as decreased regional ApEn in right precuneus, right lateral parietal regions, left precentral gyrus, and right paracentral gyrus. A pattern of asynchrony between BOLD fMRI series emerged from C-ApEn analysis, with significant regional anti-correlation with cross-correlation coefficient of functional connectivity analysis.ConclusionApEn and C-ApEn may be useful for assessing the complexity and synchronicity of brain activity in normal aging and cognitive decline associated with neurodegenerative diseases.

Background and purposeTo compare the diagnostic performance of arterial spin-labeling (ASL) and dynamic susceptibility contrast (DSC) perfusion in detecting cerebral blood flow (CBF) changes before and after endovascular recanalization in acute ischemic syndrome.MethodsThe inclusion criteria for this retrospective study were patients with acute ischemic syndrome who underwent endovascular recanalization and acquisition of both ASL and DSC before and after revascularization. ASL-CBF and multiparametric DSC maps were evaluated for image quality, location, and type of perfusion abnormality. Relative CBF (rCBF) was calculated in the infarction core and hypoperfused areas using coregistered ASL and DSC. Core and hypoperfused rCBF were used for paired pretreatment and posttreatment comparisons. Interobserver and intermodality agreement were evaluated by κ test, and t test was calculated for ASL and DSC rCBF values.ResultsTwenty-five patients met our inclusion criteria. Five studies were rated nondiagnostic, resulting in 45 pairs of DSC-ASL available for comparison. ASL and DSC agreed on type and location of the perfusion abnormality in 71% and 80% of cases, respectively. The image quality of ASL was lower than DSC, resulting in interobserver variability for the type (κ=0.45) and location (κ=0.56) of perfusion abnormality. ASL was unable to show any type of perfusion abnormality in 11% of patients. In successfully recanalized patients, hyperperfusion (rCBF >1) was detected in 100% on DSC and 47% on ASL.ConclusionsASL is less sensitive than DSC for detecting rCBF changes in patients with acute ischemic syndrome, particularly with respect to hyperperfusion after successful recanalization.

Motivations of arterial spin labeling (ASL) at ultrahigh magnetic fields include prolonged blood T1 and greater signal-to-noise ratio (SNR). However, increased B0 and B1 inhomogeneities and increased specific absorption ratio (SAR) challenge practical ASL implementations. In this study, Turbo-FLASH (Fast Low Angle Shot) based pulsed and pseudo-continuous ASL sequences were performed at 7T, by taking advantage of the relatively low SAR and short TE of Turbo-FLASH that minimizes susceptibility artifacts. Consistent with theoretical predictions, the experimental data showed that Turbo-FLASH based ASL yielded approximately 4 times SNR gain at 7T compared to 3T. High quality perfusion images were obtained with an in-plane spatial resolution of 0.85×1.7 mm(2). A further functional MRI study of motor cortex activation precisely located the primary motor cortex to the precentral gyrus, with the same high spatial resolution. Finally, functional connectivity between left and right motor cortices as well as supplemental motor area were demonstrated using resting state perfusion images. Turbo-FLASH based ASL is a promising approach for perfusion imaging at 7T, which could provide novel approaches to high spatiotemporal resolution fMRI and to investigate the functional connectivity of brain networks at ultrahigh field.

The purpose of the present study was to present a multi-delay multi-parametric pseudo-continuous arterial spin labeling (pCASL) protocol with background suppressed 3D GRASE (gradient and spin echo) readout for perfusion imaging in acute ischemic stroke. PCASL data at 4 post-labeling delay times (PLD = 1.5, 2, 2.5, 3 s) were acquired within 4.5 min in 24 patients (mean age 79.7 ± 11.4 years; 11 men) with acute middle cerebral artery (MCA) stroke who also underwent dynamic susceptibility contrast (DSC) enhanced perfusion imaging. Arterial transit times (ATT) were estimated through the calculation of weighted delays across the 4 PLDs, which were included in the calculation of cerebral blood flow (CBF) and arterial cerebral blood volume (CBV). Mean perfusion parameters derived using pCASL and DSC were measured within MCA territories and infarct regions identified on diffusion weighted MRI. The results showed highly significant correlations between pCASL and DSC CBF measurements (r > = 0.70, p  = 0.45, p