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The partial volume effect (PVE) is an important source of bias in brain perfusion measurements. The impact of tissue PVEs in perfusion measurements with dynamic susceptibility contrast MRI (DSC-MRI) has not yet been well established. The purpose of this study was to suggest a partial volume correction (PVC) approach for DSC-MRI and to study how PVC affects DSC-MRI perfusion results.A linear mixed perfusion model for DSC-MRI was derived and evaluated by way of simulations. Twenty healthy volunteers were scanned twice, including DSC-MRI, arterial spin labeling (ASL), and partial volume measurements. Two different algorithms for PVC were employed and assessed.Simulations showed that the derived model had a tendency to overestimate perfusion values in voxels with high fractions of cerebrospinal fluid. PVC reduced the tissue volume dependence of DSC-MRI perfusion values from 44.4% to 4.2% in gray matter and from 55.3% to 14.2% in white matter. One PVC method significantly improved the voxel-wise repeatability, but PVC did not improve the spatial agreement between DSC-MRI and ASL perfusion maps.Significant PVEs were found for DSC-MRI perfusion estimates, and PVC successfully reduced those effects. The findings suggest that PVC might be an important consideration for DSC-MRI applications. Magn Reson Med 77:2203-2214, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Filter exchange imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends, eg, on the cell membrane permeability. The aim was to optimize and analyze the ability of FEXI to infer differences in the apparent exchange rate (AXR) in the brain between two populations.

Arterial partial-volume effects (PVEs) often hamper reproducible absolute quantification of cerebral blood flow (CBF) and cerebral blood volume (CBV) obtained by dynamic susceptibility contrast MRI (DSC-MRI). The aim of this study was to examine whether arterial PVEs in DSC-MRI data can be minimized by rescaling the arterial input function (AIF) using a sagittal-sinus venous output function obtained following a prebolus administration of a low dose of contrast agent.

Purpose: Quantification of cerebral blood flow can be accomplished by model-free arterial spin labeling using the quantitative STAR labeling of arterial regions (QUASAR) sequence. The required deconvolution is normally based on block-circulant singular value decomposition (cSVD)/oscillation SVD (oSVD), an algorithm associated with nonphysiological residue functions and potential effects of arterial dispersion. The aim of this work was to amend this by implementing nonlinear stochastic regularization (NSR) deconvolution, previously used to retrieve realistic residue functions in dynamic susceptibility contrast MRI. METHODS: To characterize the residue function in model-free arterial spin labeling, and possibly to improve absolute cerebral blood flow quantification, NSR was applied to deconvolution of QUASAR data. For comparison, SVD-based deconvolution was also employed. Residue function characteristics and cerebral blood flow values from 10 volunteers were obtained. Simulations were performed to support the in vivo results. RESULTS: NSR was able to resolve realistic residue functions in contrast to the SVD-based methods. Mean cerebral blood flow estimates in gray matter were 36.6 ± 2.6, 28.6 ± 3.3, 40.9 ± 3.6, and 42.9 ± 3.9 mL/100 g/min for cSVD, oSVD, NSR, and NSR with correction for arterial dispersion, respectively. In simulations, the NSR-based perfusion estimates showed better accuracy than the SVD-based approaches. CONCLUSION: Perfusion quantification by model-free arterial spin labeling is evidently dependent on the selected deconvolution method, and NSR is a feasible alternative to SVD-based methods. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc. (Less)

We present the first in vivo application of the filter-exchange imaging protocol for diffusion MRI. The protocol allows noninvasive mapping of the rate of water exchange between microenvironments with different self-diffusivities, such as the intracellular and extracellular spaces in tissue. Since diffusional water exchange across the cell membrane is a fundamental process in human physiology and pathophysiology, clinically feasible and noninvasive imaging of the water exchange rate would offer new means to diagnose disease and monitor treatment response in conditions such as cancer and edema. The in vivo use of filter-exchange imaging was demonstrated by studying the brain of five healthy volunteers and one intracranial tumor (meningioma). Apparent exchange rates in white matter range from 0.8 ± 0.08 s(-1) in the internal capsule, to 1.6 ± 0.11 s(-1) for frontal white matter, indicating that low values are associated with high myelination. Solid tumor displayed values of up to 2.9 ± 0.8 s(-1) . In white matter, the apparent exchange rate values suggest intra-axonal exchange times in the order of seconds, confirming the slow exchange assumption in the analysis of diffusion MRI data. We propose that filter-exchange imaging could be used clinically to map the water exchange rate in pathologies. Filter-exchange imaging may also be valuable for evaluating novel therapies targeting the function of aquaporins. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc. (Less)

Water exchange through the cell membranes is an important feature of cells and tissues. The rate of exchange is determined by factors such as membrane lipid composition and organization, as well as the type and activity of aquaporins. A method for noninvasively estimating the rate of water exchange would be useful for characterizing pathological conditions, e.g., tumors, multiple sclerosis, and ischemic stroke, expected to be associated with a change of the membrane barrier properties. This study describes the filter exchange imaging method for determining the rate of water exchange between sites having different apparent diffusion coefficients. The method is based on the filter-exchange pulsed gradient spin-echo NMR spectroscopy experiment, which is here modified to be compatible with the constraints of clinical MR scanners. The data is analyzed using a model-free approach yielding maps of the apparent exchange rate, here being introduced in analogy with the concept of the apparent diffusion coefficient. Proof-of-principle experiments are performed on microimaging and whole-body clinical scanners using yeast suspension phantoms. The limitations and appropriate experimental conditions are examined. The results demonstrate that filter exchange imaging is a fast and reliable method for characterizing exchange, and that it has the potential to become a powerful diagnostic tool. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

Purpose Filter exchange imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends, eg, on the cell membrane permeability. The aim was to optimize and analyze the ability of FEXI to infer differences in the apparent exchange rate (AXR) in the brain between two populations. Methods A FEXI protocol was optimized for minimal measurement variance in the AXR. The AXR variance was investigated by test‐retest acquisitions in six brain regions in 18 healthy volunteers. Preoperative FEXI data and postoperative microphotos were obtained in six meningiomas and five astrocytomas. Results Protocol optimization reduced the coefficient of variation of AXR by approximately 40%. Test‐retest AXR values were heterogeneous across normal brain regions, from 0.3 ± 0.2 s−1 in the corpus callosum to 1.8 ± 0.3 s−1 in the frontal white matter. According to analysis of statistical power, in all brain regions except one, group differences of 0.3–0.5 s−1 in the AXR can be inferred using 5 to 10 subjects per group. An AXR difference of this magnitude was observed between meningiomas (0.6 ± 0.1 s−1) and astrocytomas (1.0 ± 0.3 s−1). Conclusions With the optimized protocol, FEXI has the ability to infer relevant differences in the AXR between two populations for small group sizes. Magn Reson Med 77:1104–1114, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

The Rician distribution of noise in magnitude magnetic resonance (MR) images is particularly problematic in low signal-to-noise ratio (SNR) regions. The Rician noise distribution causes a nonzero minimum signal in the image, which is often referred to as the rectified noise floor. True low signal is likely to be concealed in the noise, and quantification is severely hampered in low-SNR regions. To address this problem we performed noise reduction (or denoising) by Wiener-like filtering in the wavelet domain. The filtering was applied to complex MRI data before construction of the magnitude image. The noise-reduction algorithm was applied to simulated and experimental diffusion-weighted (DW) images. Denoising considerably reduced the signal standard deviation (SD, by up to 87% in simulated images) and decreased the background noise floor (by approximately a factor of 6 in simulated and experimental images).

A new technique for assessing tissue blood flow using hyperpolarized tracers, based on the fact that the magnetization of a hyperpolarized substance can be destroyed permanently, is described. Assessments of blood flow with this technique are inherently insensitive to arterial delay and dispersion, and allow for quantification of the transit time and dispersion in the arteries that supply the investigated tissue. Renal cortical blood flow was studied in six rabbits using a 13C-labeled compound (2-hydroxyethylacrylate) that was polarized by the parahydrogen-induced polarization (PHIP) technique. The renal cortical blood flow was estimated to be 5.7/5.4 +/- 1.6/1.3 ml/min per milliliter of tissue (mean +/- SD, right/left kidney), and the mean transit time and dispersion in the renal arteries were determined to be 1.47/1.42 +/- 0.07/0.07 s and 1.78/1.93 +/- 0.40/0.42 s2, respectively.

Cerebral perfusion was assessed with 13C MRI in a rat model after intravenous injections of the 13C-labeled compound bis-1,1-(hydroxymethyl)-1-13C-cyclopropane-D8 in aqueous solutions hyperpolarized by dynamic nuclear polarization (DNP). Since the tracer acted as a direct signal source, several of the problems associated with techniques based on traditional dynamic susceptibility contrast (DSC) MRI contrast agents were avoided. Maps of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) were calculated. The MTT was determined to be 2.8 ± 0.8 sec. However, arterial partial-volume effects in the animal model prevented accurate absolute quantification of CBF and CBV. It was demonstrated that depolarization of the hyperpolarized 13C tracer via relaxation and the imaging sequence had little influence on CBF assessment when the time resolution of the imaging sequence was short compared to the MTT. However, CBV and MTT were increasingly underestimated as MTT or the depolarization rate increased if depolarization was not taken into account. With a modified bolus-tracking theory depolarization could be compensated for, assuming that the depolarization rate was known. Three separate compensation methods were investigated experimentally and by numerical simulations. Magn Reson Med 51:464–472, 2004. © 2004 Wiley-Liss, Inc.

Arterial partial-volume effects (PVEs) often hamper reproducible absolute quantification of cerebral blood flow (CBF) and cerebral blood volume (CBV) obtained by dynamic susceptibility contrast MRI (DSC-MRI). The aim of this study was to examine whether arterial PVEs in DSC-MRI data can be minimized by rescaling the arterial input function (AIF) using a sagittal-sinus venous output function obtained following a prebolus administration of a low dose of contrast agent.The study was carried out as a test-retest experiment in 20 healthy volunteers to examine the repeatability of the CBF and CBV estimates. All subjects were scanned twice with 7-20 days between investigations.DSC-MRI returned an overestimated average whole-brain CBF of 220 ± 44 mL/100 g/min (mean ± SD) before correction and 44 ± 15 mL/100 g/min when applying the prebolus design, averaged over all scans. Average whole-brain CBV was 20 ± 2.0 mL/100 g before correction and 4.0 ± 1.0 mL/100 g after prebolus correction.Quantitative estimates of CBF and CBV, obtained with the proposed prebolus DSC-MRI technique, approached those typically obtained by other perfusion modalities. The CBF and CBV estimates showed good repeatability.

Purpose: Quantification of cerebral blood flow can be accomplished by model-free arterial spin labeling using the quantitative STAR labeling of arterial regions (QUASAR) sequence. The required deconvolution is normally based on block-circulant singular value decomposition (cSVD)/oscillation SVD (oSVD), an algorithm associated with nonphysiological residue functions and potential effects of arterial dispersion. The aim of this work was to amend this by implementing nonlinear stochastic regularization (NSR) deconvolution, previously used to retrieve realistic residue functions in dynamic susceptibility contrast MRI. METHODS: To characterize the residue function in model-free arterial spin labeling, and possibly to improve absolute cerebral blood flow quantification, NSR was applied to deconvolution of QUASAR data. For comparison, SVD-based deconvolution was also employed. Residue function characteristics and cerebral blood flow values from 10 volunteers were obtained. Simulations were performed to support the in vivo results. RESULTS: NSR was able to resolve realistic residue functions in contrast to the SVD-based methods. Mean cerebral blood flow estimates in gray matter were 36.6 ± 2.6, 28.6 ± 3.3, 40.9 ± 3.6, and 42.9 ± 3.9 mL/100 g/min for cSVD, oSVD, NSR, and NSR with correction for arterial dispersion, respectively. In simulations, the NSR-based perfusion estimates showed better accuracy than the SVD-based approaches. CONCLUSION: Perfusion quantification by model-free arterial spin labeling is evidently dependent on the selected deconvolution method, and NSR is a feasible alternative to SVD-based methods. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.

A new technique for assessing tissue blood flow using hyperpolarized tracers, based on the fact that the magnetization of a hyperpolarized substance can be destroyed permanently, is described. Assessments of blood flow with this technique are inherently insensitive to arterial delay and dispersion, and allow for quantification of the transit time and dispersion in the arteries that supply the investigated tissue. Renal cortical blood flow was studied in six rabbits using a 13C-labeled compound (2-hydroxyethylacrylate) that was polarized by the parahydrogen-induced polarization (PHIP) technique. The renal cortical blood flow was estimated to be 5.7/5.4 +/- 1.6/1.3 ml/min per milliliter of tissue (mean +/- SD, right/left kidney), and the mean transit time and dispersion in the renal arteries were determined to be 1.47/1.42 +/- 0.07/0.07 s and 1.78/1.93 +/- 0.40/0.42 s2, respectively.

Cerebral perfusion was assessed with 13C MRI in a rat model after intravenous injections of the 13C-labeled compound bis-1,1-(hydroxymethyl)-1-13C-cyclopropane-D8 in aqueous solutions hyperpolarized by dynamic nuclear polarization (DNP). Since the tracer acted as a direct signal source, several of the problems associated with techniques based on traditional dynamic susceptibility contrast (DSC) MRI contrast agents were avoided. Maps of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) were calculated. The MTT was determined to be 2.8 +/- 0.8 sec. However, arterial partial-volume effects in the animal model prevented accurate absolute quantification of CBF and CBV. It was demonstrated that depolarization of the hyperpolarized 13C tracer via relaxation and the imaging sequence had little influence on CBF assessment when the time resolution of the imaging sequence was short compared to the MTT. However, CBV and MTT were increasingly underestimated as MTT or the depolarization rate increased if depolarization was not taken into account. With a modified bolus-tracking theory depolarization could be compensated for, assuming that the depolarization rate was known. Three separate compensation methods were investigated experimentally and by numerical simulations.

The noninvasive thermometry method is based on the temperature dependence of the proton resonance frequency (PRF). High-quality temperature images can be obtained from phase information of standard gradient-echo sequences with an accuracy of 0.2 degrees C in phantoms. This work was focused on the in vivo capabilities of this method. An experimental setup was designed that allows a qualitative in vivo verification. The lower-leg muscles of a volunteer were cooled and afterwards reheated with an external water bolus. The temperature of the bolus water varied between 17 degrees C and 37 degrees C. The in vivo temperature images can be used to extract the temperature in muscle tissue. The data in the fat tissue are difficult to interpret because of the predominance of susceptibility effects. The results confirm the method's potential for hyperthermia control.