Functional Magnetic Resonance Imaging (fMRI) is broadly used to measure human brain activity, however the hemodynamic changes that comprise the fMRI response to neuronal activity are often interpreted using microscopy data in mice. These microscopy data provide ground-truth observations of how individual blood vessels respond to neuronal activity and thus form the basis of our fundamental understanding of neurovascular coupling. Although these invasive experiments provide invaluable insight, there are striking differences in the vascular architecture of mouse and human brains that may influence the hemodynamic response. Motivated by this, we developed a biophysical modeling framework for realistic hemodynamic simulations in both mouse and human cerebral cortex. For this, we utilized Vascular Anatomical Network (VAN) models that explicitly represent the full microvascular tree as a single connected network, originally based on anatomical reconstructions from a given location of mouse cerebral cortex. We extended the VAN modeling framework using synthetic VAN models representing the microvascular network at a single location of the human cerebral cortex. To account for larger size and complexity of the human VAN models, we developed an efficient computational framework to simulate the full hemodynamic responses in this human model and compared the simulated fMRI responses between mice and humans. Our biophysical simulations are based entirely on first principles (e.g., conservation of mass); model parameter values were fixed across all simulations, not tuned to fit data, as they represent meaningful physical constants taken from previous measurements. Only two simple calibrations were tuned for each simulation, to match baseline perfusion rates (blood flow) and oxygen extraction (OEF). Our results show that differences in microvasculature indeed influenced the hemodynamic response and led to observable differences in timing-e.g., the simulated fMRI response peak in humans was delayed by ~2 s compared to mice, consistent with prior fMRI observations. While there are many known differences in vascular architecture in rodents and humans, we also discovered that, unexpectedly, an asymmetry in the numbers of branches of the penetrating intracortical arterioles and venules appears to be conserved across species. We demonstrate through further simulations that this anatomical property may also be needed for suitable hemodynamic responses. Our framework thus provides a valuable tool for bridging in-vivo microscopy of microvascular dynamics to human fMRI.

PURPOSE:Echo planar time-resolved imaging (EPTI) is a new imaging approach that addresses the limitations of EPI by providing high-resolution, distortion- and T2/ T 2 * $$ {\mathrm{T}}_2^{\ast } $$  blurring-free imaging for functional MRI (fMRI). However, as in all multishot sequences, intershot phase variations induced by physiological processes can introduce temporal instabilities to the reconstructed time-series data. This study aims to reduce these instabilities in multishot EPTI. THEORY AND METHODS:In conventional multishot EPTI, the time intervals between the shots comprising each slice can introduce intershot phase variations. Here, the fast low-angle excitation echo-planar technique (FLEET), in which all shots of each slice are acquired consecutively with minimal time delays, was combined with a variable flip angle (VFA) technique to improve intershot consistency and maximize signal. A recursive Shinnar-Le Roux RF pulse design algorithm was used to generate pulses for different shots to produce consistent slice profiles and signal intensities across shots. Blipped controlled aliasing in parallel imaging simultaneous multislice was also combined with the proposed VFA-FLEET EPTI to improve temporal resolution and increase spatial coverage. RESULTS:The temporal stability of VFA-FLEET EPTI was compared with conventional EPTI at 7 T. The results demonstrated that VFA-FLEET can provide spatial-specific increase of temporal stability. We performed high-resolution task-fMRI experiments at 7 T using VFA-FLEET EPTI, and reliable BOLD responses to a visual stimulus were detected. CONCLUSION:The intershot phase variations induced by physiological processes in multishot EPTI can manifest as specific spatial patterns of physiological noise enhancement and lead to reduced temporal stability. The VFA-FLEET technique can substantially reduce these physiology-induced instabilities in multishot EPTI acquisitions. The proposed method provides sufficient stability and sensitivity for high-resolution fMRI studies.

Cerebral hypoxia significantly impacts the progression of brain tumors and their resistance to radiotherapy. This study employed streamlined quantitative blood-oxygen-level-dependent (sqBOLD) MRI to assess the oxygen extraction fraction (OEF)—a measure of how much oxygen is being extracted from vessels, with higher OEF values indicating hypoxia. Simultaneously, we utilized vessel size imaging (VSI) to evaluate microvascular dimensions and blood volume. A cohort of ten patients, divided between those with glioma and those with brain metastases, underwent a 3 Tesla MRI scan. We generated OEF, cerebral blood volume (CBV), and vessel size maps, which guided 3–4 targeted biopsies per patient. Subsequent histological analyses of these biopsies used hypoxia-inducible factor 1-alpha (HIF-1α) for hypoxia and CD31 for microvasculature assessment, followed by a correlation analysis between MRI and histological data. The results showed that while the sqBOLD model was generally applicable to brain tumors, it demonstrated discrepancies in some metastatic tumors, highlighting the need for model adjustments in these cases. The OEF, CBV, and vessel size maps provided insights into the tumor’s hypoxic condition, showing intertumoral and intratumoral heterogeneity. A significant relationship between MRI-derived measurements and histological data was only evident in the vessel size measurements (r = 0.68, p < 0.001).

In trying to elucidate the mechanisms of the blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) techniques and to expand on the potential of the transverse relaxation time (T2*) in quantitative MRI, many methods for the forward modelling of the BOLD effect have been created and analyzed. Simulations of this nature can be difficult to implement without prior experience, and differences made by methodological choices can be unclear, which provides a significant barrier of entry into the field. In this paper, we present BOLDswimsuite, a toolbox for forward modeling of the BOLD effect, which collects many of the principal methods used in the literature into a single coherent package. Implemented as a Python package, simulations are built-in scripts by combining various simulation components, while providing flexibility in methodological choices. The goal of this toolbox is to provide an open-source, reproducible software suite that is adaptable for simulations in different MRI applications, and to which additional features can be added by the user with relative ease. This paper first provides an overview of the methods available in the package and how these methods can be constructed from the toolbox’s modular code components. Then, a brief theoretical explanation of each simulation component is given, supported by the relevant contributors. Next, sample simulations and analyses that can be created using the package are presented to display its features. Finally, recommendations regarding computational requirements are included to help users choose the best simulation methods to fit their needs. This package has many use cases and significantly reduces methodological barriers to forward modeling. It can also be a good learning tool for MR physics as well as a powerful tool to promote reproducible science.### Competing Interest StatementThe authors have declared no competing interest.

Objective Monitoring brain oxygenation is critical in brain tumors, as low oxygenation influences tumor growth, pathological angiogenesis, and treatment resistance. This study examined the ability of the streamlined quantitative (sq)BOLD MRI technique to detect oxygenation changes in healthy individuals, as well as its potential application in a clinical setting. Methods We used the asymmetric spin echo (ASE) technique with FLAIR preparation, along with model-based Bayesian inference to quantify the reversible transverse relaxation rate ( R 2 ' ) and oxygen extraction fraction (OEF) across the brain at baseline and during visual stimulation in eight healthy participants at 3T; and two patients with glioma at rest only. Results Comparing sqBOLD-derived parameters between baseline and visual stimulation revealed a decrease in OEF from 0.56 ± 0.09 at baseline to 0.54 ± 0.07 at the activated state ( p = 0.04, paired t test) within a functional localizer-defined volume of interest, and a decline in R 2 ' from 6.5 ± 1.3s −1 at baseline to 6.2 ± 1.4s −1 at the activated state ( p = 0.006, paired t test) in the visual cortex. Conclusion The sqBOLD technique is sensitive enough to detect and quantify changes in oxygenation in the healthy brain and shows potential for integration into clinical settings to provide valuable information on oxygenation in glioma.

We propose a novel slice-GRAPPA reconstruction algorithm, termed multi-kernel slice-GRAPPA (mks-GRAPPA), to tackle the challenge of reconstructing high spatial resolution segmented multi-shot EPI data for fMRI. This is particularly relevant for the recently proposed Variable-Flip-Angle “FLEET” pulse sequence. For a segmentation factor, S, by training 2×S slice-GRAPPA kernels, rather than one, we demonstrate significant improvements in image quality metrics under a wide range of protocols. The multitude of kernels account for static signal discontinuities within and across segments in multi-shot EPI. In the SNR starved regime of high-res fMRI, mks-GRAPPA allows us to recover a significant portion of lost tSNR.

We utilized a synthesis algorithm to generate a vascular anatomical network model for the human cortex to act as a basis for biophysical simulations of the fMRI response. We identified key features of the vascular topology needed to generate realistic BOLD responses with this model. We used this model to show how parametric variations in vascular architecture affect the BOLD responses across cortical depths. Finally we investigated approaches to translate arteriolar dilation patterns recorded from the mouse cortex to our human model and found that they may not be capable of capturing the distinct hemodynamic response observed in human fMRI data.

PURPOSE:To achieve high-resolution multishot echo-planar imaging (EPI) for functional MRI (fMRI) with reduced sensitivity to in-plane motion and between-shot phase variations. METHODS:Two-dimensional radiofrequency pulses were incorporated in a multishot EPI sequence at 7T which selectively excited a set of in-plane bands (shutters) in the phase encoding direction, which moved between shots to cover the entire slice. A phase- and motion-corrected reconstruction was implemented for the acquisition. Brain imaging experiments were performed with instructed motion to evaluate image quality for conventional multishot and shuttered EPI. Temporal stability was assessed in three subjects by quantifying temporal SNR (tSNR) and artifact levels, and fMRI activation experiments using visual stimulation were performed to assess the strength and distribution of activation, using both conventional multishot and shuttered EPI. RESULTS:In the instructed motion experiment, ghosting was lower in shuttered EPI images without or with corrections and image quality metrics were improved with motion correction. tSNR was improved by phase correction in both conventional multishot and shuttered EPI and the acquisitions had similar tSNR without and with phase correction. However, while phase correction was necessary to maximize tSNR in conventional multishot EPI, it also increased intermittent ghosting, but did not increase intermittent ghosting in shuttered EPI. Phase correction increased activation strength in both conventional multishot and shuttered EPI, but caused increased spurious activation outside the brain and in frontal brain regions in conventional multishot EPI. CONCLUSION:Shuttered EPI supports multishot segmented EPI acquisitions with lower sensitivity to artifacts from motion for high-resolution fMRI.

Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult life span. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average R2 of 0.21) than in the CBF data (average R2 of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.

PURPOSE:To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration.THEORY AND METHODS:Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals.RESULTS:The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing.CONCLUSIONS:VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

PurposeThe primary goal of this study was to estimate the value of , the exponent in the power law relating changes of the transverse relaxation rate and intra‐extravascular local magnetic susceptibility differences as . The secondary objective was to evaluate any differences that might exist in the value of obtained using a deoxyhemoglobin‐weighted distribution versus a constant distribution assumed in earlier computations. The third objective was to estimate the value of β that is relevant for methods based on susceptibility contrast agents with a concentration of higher than that used for BOLD fMRI calculations.MethodsOur recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte‐Carlo simulations to compute from the first principles.ResultsOur results show that for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of .5 using uniform distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for , for 9.4 T, whereas at 14 T can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of is desired for experiments at high B0.ConclusionThese results improve our understanding of the relationship between R2* and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.

Quantitative BOLD (qBOLD) is a technique for mapping oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) in the human brain. Recent measurements using an asymmetric spin echo (ASE) based qBOLD approach produced estimates of DBV which were systematically higher than measurements from other techniques. In this study, we investigate two hypotheses for the origin of this DBV overestimation using simulations and consider the implications for experimental measurements. Investigations were performed by combining Monte Carlo simulations of extravascular signal with an analytical model of the intravascular signal. Hypothesis 1 DBV overestimation is due to the presence of intravascular signal which is not accounted for in the analysis model. Intravascular signal was found to have a weak effect on qBOLD parameter estimates. Hypothesis 2 DBV overestimation is due to the effects of diffusion which are not accounted for in the analysis model. The effect of diffusion on the extravascular signal was found to result in a vessel radius dependent variation in qBOLD parameter estimates. In particular, DBV overestimation peaks for vessels with radii from 20 to 30 μm and is OEF dependent. This results in the systematic underestimation of OEF. Implications The impact on experimental qBOLD measurements was investigated by simulating a more physiologically realistic distribution of vessel sizes with a small number of discrete radii. Overestimation of DBV consistent with previous experiments was observed, which was also found to be OEF dependent. This results in the progressive underestimation of the measured OEF. Furthermore, the relationship between the measured OEF and the true OEF was found to be dependent on echo time and spin echo displacement time. The results of this study demonstrate the limitations of current ASE based qBOLD measurements and provide a foundation for the optimisation of future acquisition approaches.

Purpose To derive an expression for the transverse signal time course from systems in the motional narrowing regime, such as water diffusing in blood. This was validated in silico and experimentally with ex vivo blood samples. Methods A closed‐form solution (CFS) for transverse signal decay under any train of refocusing pulses was derived using the weak field approximation. The CFS was validated via simulations of water molecules diffusing in the presence of spherical perturbers, with a range of sizes and under various pulse sequences. The CFS was compared with more conventional fits assuming monoexponential decay, including chemical exchange, using ex vivo blood Carr‐Purcell‐Meiboom‐Gill data. Results From simulations, the CFS was shown to be valid in the motional narrowing regime and partially into the intermediate dephasing regime, with increased accuracy with increasing Carr‐Purcell‐Meiboom‐Gill refocusing rate. In theoretical calculations of the CFS, fitting for the transverse relaxation rate (R 2 ) gave excellent agreement with the weak field approximation expression for R 2 for Carr‐Purcell‐Meiboom‐Gill sequences, but diverged for free induction decay. These same results were confirmed in the ex vivo analysis. Conclusion Transverse signal decay in the motional narrowing regime can be accurately described analytically. This theory has applications in areas such as tissue iron imaging, relaxometry of blood, and contrast agent imaging. Magn Reson Med 80:341–350, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The phenomenon of cortical thinning with age has been well established; however, the measured rate of change varies between studies. The source of this variation could be image acquisition techniques including hardware and vendor specific differences. Databases are often consolidated to increase the number of subjects but underlying differences between these datasets could have undesired effects. We explore differences in cerebral cortex thinning between 4 databases, totaling 1382 subjects. We investigate several aspects of these databases, including: 1) differences between databases of cortical thinning rates versus age, 2) correlation of cortical thinning rates between regions for each database, and 3) regression bootstrapping to determine the effect of the number of subjects included. We also examined the effect of different databases on age prediction modeling. Cortical thinning rates were significantly different between databases in all 68 parcellated regions (ANCOVA, P < 0.001). Subtle differences were observed in correlation matrices and bootstrapping convergence. Age prediction modeling using a leave-one-out cross-validation approach showed varying prediction performance (0.64 < R2 < 0.82) between databases. When a database was used to calibrate the model and then applied to another database, prediction performance consistently decreased. We conclude that there are indeed differences in the measured cortical thinning rates between these large-scale databases.

A new method is proposed for obtaining cerebral perfusion measurements whereby blood oxygen level dependent (BOLD) MRI is used to dynamically monitor hyperoxia-induced changes in the concentration of deoxygenated hemoglobin in the cerebral vasculature. The data is processed using kinetic modeling to yield perfusion metrics, namely: cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Ten healthy human subjects were continuously imaged with BOLD sequence while a hyperoxic (70% O-2) state was interspersed with baseline periods of normoxia. The BOLD time courses were fit with exponential uptake and decay curves and a biophysical model of the BOLD signal was used to estimate oxygen concentration functions. The arterial input function was derived from end-tidal oxygen measurements, and a deconvolution operation between the tissue and arterial concentration functions was used to yield CBF. The venous component of the CBV was calculated from the ratio of the integrals of the estimated tissue and arterial concentration functions. Mean gray and white matter measurements were found to be: 61.6 +/- 13.7 and 24.9 +/- 4.0 ml 100 g(-1) min(-1) for CBF; 1.83 +/- 0.32 and 1.10 +/- 0.19 ml 100 g(-1) for venous CBV; and 2.94 +/- 0.52 and 3.73 +/- 0.60 s for MTT, respectively. We conclude that it is possible to derive CBF, CBV and MTT metrics within expected physiological ranges via analysis of dynamic BOLD fMRI acquired during a period of hyperoxia.

Calibrated functional magnetic resonance imaging (fMRI) is a method to independently measure the metabolic and hemodynamic contributions to the blood oxygenation level dependent (BOLD) signal. This technique typically requires the use of a respiratory challenge, such as hypercapnia or hyperoxia, to estimate the calibration constant, M. There has been a recent push to eliminate the gas challenge from the calibration procedure using asymmetric spin echo (ASE) based techniques. This study uses simulations to better understand spin echo (SE) and ASE signals, analytical modelling to characterize the signal evolution, and in vivo imaging to validate the modelling. Using simulations, it is shown how ASE imaging generally underestimates M and how this depends on several parameters of the acquisition, including echo time and ASE offset, as well as the vessel size. This underestimation is the result of imperfect SE refocusing due to diffusion of water through the extravascular environment surrounding the microvasculature. By empirically characterizing this SE attenuation as an exponential decay that increases with echo time, we have proposed a quadratic ASE biophysical signal model. This model allows for the characterization and compensation of the SE attenuation if SE and ASE signals are acquired at multiple echo times. This was tested in healthy subjects and was found to significantly increase the estimates of M across grey matter. These findings show promise for improved gas-free calibration and can be extended to other relaxation-based imaging studies of brain physiology.

PurposeTo determine the contribution of paramagnetic dissolved oxygen in blood plasma to blood‐oxygenation‐level‐dependent (BOLD) signal changes in hyperoxic calibrated BOLD studies.MethodsBovine blood plasma samples were prepared with partial pressures of oxygen (pO2) ranging from 110 to 600 mmHg. R1, R2, and R2* of the plasma with dissolved oxygen were measured using quantitative MRI sequences at 3 Tesla. Simulations were performed to predict the relative effects of dissolved oxygen and deoxyhemoglobin changes in hyperoxia calibrated BOLD.ResultsThe relaxivities of dissolved oxygen in plasma were found to be r1, O2 =1.97 ± 0.09 ×10‐4 s‐1mmHg‐1, r2, O2 =2.3 ± 0.7 ×10‐4 s‐1mmHg‐1, and r2, O2* = 2.3 ± 0.7 ×10‐4 s‐1mmHg‐1. Simulations predict that neither the transverse nor longitudinal relaxation rates of dissolved oxygen contribute significantly to the BOLD signal during hyperoxia.ConclusionDuring hyperoxia, the increases in R2 and R2* of blood from dissolved oxygen in plasma are considerably less than the decreases in R2 and R2* from venous deoxyhemoglobin. R1 effects due to dissolved oxygen are also predicted to be negligible. As a result, dissolved oxygen in arteries should not contribute significantly to the hyperoxic calibrated BOLD signal. Magn Reson Med 76:1905–1911, 2016. © 2015 International Society for Magnetic Resonance in Medicine

Purpose It has been predicted that, during hyperoxia, excess O 2 dissolved in arterial blood will significantly alter the blood's magnetic susceptibility. This would confound the interpretation of the hyperoxia‐induced blood oxygenation level‐dependent signal as arising solely from changes in deoxyhemoglobin. This study, therefore, aimed to determine how dissolved O 2 affects the susceptibility of blood. Theory and Methods We present a comprehensive model for the effect of dissolved O 2 on the susceptibility of blood and compare it with another recently published model, referred to here as the ideal gas model (IGM). For validation, distilled water and samples of bovine plasma were oxygenated over a range of hyperoxic O 2 concentrations and their susceptibilities were determined using multiecho gradient echo phase imaging. Results In distilled water and plasma, the measured changes in susceptibility were very linear, with identical slopes of 0.062 ppb/mm Hg of O 2 . This change was dramatically less than previously predicted using the IGM and was close to that predicted by our model. The primary source of error in the IGM is the overestimation of the volume fraction occupied by dissolved O 2 . Conclusion Under most physiological conditions, the susceptibility of dissolved O 2 can be disregarded in MRI studies employing hyperoxia. Magn Reson Med 75:363–371, 2016. © 2015 Wiley Periodicals, Inc.