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Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Systemic physiological dynamics, such as heart rate variability (HRV) and respiration volume per time (RVT), are known to account for significant variance in the blood oxygen level dependent (BOLD) signal of resting-state functional magnetic resonance imaging (rsfMRI). However, synchrony between these cardiorespiratory changes and the BOLD signal could be due to neuronal (i.e., autonomic activity inducing changes in heart rate and respiration) or vascular (i.e., cardiorespiratory activity facilitating hemodynamic changes and thus the BOLD signal) effects and the contributions of these effects may differ spatially, temporally, and spectrally. In this study, we characterize these brain-body dynamics using a wavelet analysis in rapidly sampled rsfMRI data with simultaneous pulse oximetry and respiratory monitoring of the Human Connectome Project. Our time-frequency analysis across resting-state networks (RSNs) revealed differences in the coherence of the BOLD signal and heartbeat interval (HBI)/RVT dynamics across frequencies, with unique profiles per network. Somatomotor (SMN), visual (VN), and salience (VAN) networks demonstrated the greatest synchrony with both systemic physiological signals when compared to other networks; however, significant coherence was observed in all RSNs regardless of direct autonomic involvement. Our phase analysis revealed distinct frequency profiles of percentage of time with significant coherence between BOLD and systemic physiological signals for different phase offsets across RSNs, suggesting that the phase offset and temporal order of signals varies by frequency. Lastly, our analysis of temporal variability of coherence provides insight on potential influence of autonomic state on brain-body communication. Overall, the novel wavelet analysis enables an efficient characterization of the dynamic relationship between cardiorespiratory activity and the BOLD signal in spatial, temporal, and spectral dimensions to inform our understanding of autonomic states and improve our interpretation of the BOLD signal., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Resting-state (rs) functional magnetic resonance imaging (fMRI) is used to detect low-frequency fluctuations in the blood oxygen-level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD-derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high-resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI-derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel-wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Purpose: Susceptibility-based blood oxygenation measurements in small vessels of the brain derive from gradient echo (GRE) phase and can provide localized assessment of brain function and pathology. However, when vessel diameter becomes smaller than the acquisition voxel size, partial volume effects compromise these measurements. The purpose of this study was to develop a technique to improve the reliability of vessel oxygenation estimates in the presence of partial volume effects., Methods: Intravoxel susceptibility variations are present when a vessel and parenchyma experience partial volume effects, modifying the voxel's GRE phase signal and attenuating the GRE magnitude signal. Using joint utilization of magnitude and phase (JUMP), both vessel susceptibility and voxel partial volume fraction can be estimated, providing measurements of venous oxygen saturation ( Yv) in straight, nearly vertical vessels that have improved robustness to partial volume effects., Results: JUMP was demonstrated by estimating vessel Yv in numerical and in vivo experiments. Deviations from ground truth of Yv measurements in vessels tilted up to 30° from B0 were reduced by over 50% when using JUMP compared with phase-only techniques., Conclusion: JUMP exploits both magnitude and phase data in GRE imaging to mitigate partial volume effects in estimation of vessel oxygenation. Magn Reson Med 77:1713-1727, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

The magnetism of hemoglobin - being paramagnetic in its deoxy and diamagnetic in its oxy state - offers unique opportunities to probe oxygen metabolism in blood and tissues. The magnetic susceptibility χ of blood scales linearly with blood oxygen saturation, which can be obtained by measuring the magnetic field ΔB of the intravascular MR signal relative to tissue. In contrast to χ, the induced field ΔB is non-local. Therefore, to obtain the intravascular susceptibility Δχ relative to adjoining tissue from the measured ΔB demands solution of an inverse problem. Fortunately, for ellipsoidal structures, to which a straight, cylindrically shaped blood vessel segment conforms, the solution is trivial. The article reviews the principle of MR susceptometry-based blood oximetry. It then discusses applications for quantification of whole-brain oxygen extraction - typically on the basis of a measurement in the superior sagittal sinus - and, in conjunction with total cerebral blood flow, the cerebral metabolic rate of oxygen (CMRO 2 ). By simultaneously measuring flow and venous oxygen saturation (SvO 2 ) a temporal resolution of a few seconds can be achieved, allowing the study of the response to non-steady-state challenges such as volitional apnea. Extensions to regional measurements in smaller cerebral veins are also possible, as well as voxelwise quantification of venous blood saturation in cerebral veins accomplished by quantitative susceptibility mapping (QSM) techniques. Applications of susceptometry-based oximetry to studies of metabolic and degenerative disorders of the brain are reviewed. Lastly, the technique is shown to be applicable to other organ systems such as the extremities using SvO 2 as a dynamic tracer to monitor the kinetics of the microvascular response to induced ischemia. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Purpose: To introduce the wave-CAIPI (controlled aliasing in parallel imaging) acquisition and reconstruction technique for highly accelerated 3D imaging with negligible g-factor and artifact penalties., Methods: The wave-CAIPI 3D acquisition involves playing sinusoidal gy and gz gradients during the readout of each kx encoding line while modifying the 3D phase encoding strategy to incur interslice shifts as in 2D-CAIPI acquisitions. The resulting acquisition spreads the aliasing evenly in all spatial directions, thereby taking full advantage of 3D coil sensitivity distribution. By expressing the voxel spreading effect as a convolution in image space, an efficient reconstruction scheme that does not require data gridding is proposed. Rapid acquisition and high-quality image reconstruction with wave-CAIPI is demonstrated for high-resolution magnitude and phase imaging and quantitative susceptibility mapping., Results: Wave-CAIPI enables full-brain gradient echo acquisition at 1 mm isotropic voxel size and R = 3 × 3 acceleration with maximum g-factors of 1.08 at 3T and 1.05 at 7T. Relative to the other advanced Cartesian encoding strategies (2D-CAIPI and bunched phase encoding) wave-CAIPI yields up to two-fold reduction in maximum g-factor for nine-fold acceleration at both field strengths., Conclusion: Wave-CAIPI allows highly accelerated 3D acquisitions with low artifact and negligible g-factor penalties, and may facilitate clinical application of high-resolution volumetric imaging., (© 2014 Wiley Periodicals, Inc.)

Purpose: To enable fast reconstruction of quantitative susceptibility maps with total variation penalty and automatic regularization parameter selection., Methods: ℓ(1) -Regularized susceptibility mapping is accelerated by variable splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and fast Fourier transforms. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization., Results: Compared with the nonlinear conjugate gradient (CG) solver, the proposed method is 20 times faster. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering, and ℓ(1) -regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 min using MATLAB on a standard workstation compared with 22 min using the CG solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 min, which would have taken 4 h with the CG algorithm. The proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5 times faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional blood oxygen level-dependent susceptibility mapping, where processing of the massive time series dataset would otherwise be prohibitive with the CG solver., Conclusion: Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: To demonstrate acquisition and processing methods for quantitative oxygenation venograms that map in vivo oxygen saturation (SvO2 ) along cerebral venous vasculature., Methods: Regularized quantitative susceptibility mapping (QSM) is used to reconstruct susceptibility values and estimate SvO2 in veins. QSM with ℓ1 and ℓ2 regularization are compared in numerical simulations of vessel structures with known magnetic susceptibility. Dual-echo, flow-compensated phase images are collected in three healthy volunteers to create QSM images. Bright veins in the susceptibility maps are vectorized and used to form a three-dimensional vascular mesh, or venogram, along which to display SvO2 values from QSM., Results: Quantitative oxygenation venograms that map SvO2 along brain vessels of arbitrary orientation and geometry are shown in vivo. SvO2 values in major cerebral veins lie within the normal physiological range reported by (15) O positron emission tomography. SvO2 from QSM is consistent with previous MR susceptometry methods for vessel segments oriented parallel to the main magnetic field. In vessel simulations, ℓ1 regularization results in less than 10% SvO2 absolute error across all vessel tilt orientations and provides more accurate SvO2 estimation than ℓ2 regularization., Conclusion: The proposed analysis of susceptibility images enables reliable mapping of quantitative SvO2 along venograms and may facilitate clinical use of venous oxygenation imaging., (Copyright © 2013 Wiley Periodicals, Inc.)

Venous oxygen saturation (Y(v) ) in cerebral veins and the cerebral metabolic rate of oxygen (CMRO(2)) are important indicators for brain function and disease. Although MRI has been used for global measurements of these parameters, currently there is no recognized technique to quantify regional Y(v) and CMRO(2) using noninvasive imaging. This article proposes a technique to quantify CMRO(2) from independent MRI estimates of Y(v) and cerebral blood flow. The approach uses standard gradient-echo and arterial spin labeling acquisitions to make these measurements. Using MR susceptometry on gradient-echo phase images, Y(v) was quantified for candidate vein segments in gray matter that approximate a long cylinder parallel to the main magnetic field. Local cerebral blood flow for the identified vessel was determined from a corresponding region in the arterial spin labeling perfusion map. Fick's principle of arteriovenous difference was then used to quantify CMRO(2) locally around each vessel. Application of this method in young, healthy subjects provided gray matter averages of 59.6% ± 2.3% for Y(v), 51.7 ± 6.4 mL/100 g/min for cerebral blood flow, and 158 ± 18 μmol/100 g/min for CMRO(2) (mean ± SD, n = 12), which is consistent with values previously reported by positron emission tomography and MRI., (Copyright © 2011 Wiley Periodicals, Inc.)