Corrigendum to "Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: Comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging" [Heliyon 8(12) (December 2022) e12364]

[This corrects the article DOI: 10.1016/j.heliyon.2022.e12364.].

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI

PURPOSE

Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone to errors because of the unavoidable noise in vivo. A deep learning-based single Lorentzian Fitting Network (sLoFNet) is proposed to overcome these shortcomings.

METHODS

A neural network architecture was constructed and its hyperparameters optimized. Training was conducted on a simulated and in vivo-paired data sets of discrete signal values and their corresponding Lorentzian shape parameters. The sLoFNet performance was compared with LS on several WASSR data sets (both simulated and in vivo 3T brain scans). Prediction errors, robustness against noise, effects of sampling density, and time consumption were compared.

RESULTS

LS and sLoFNet performed comparably in terms of RMS error and mean absolute error on all in vivo data with no statistically significant difference. Although the LS method fitted well on samples with low noise, its error increased rapidly when increasing sample noise up to 4.5%, whereas the error of sLoFNet increased only marginally. With the reduction of Z-spectral sampling density, prediction errors increased for both methods, but the increase occurred earlier (at 25 vs. 15 frequency points) and was more pronounced for LS. Furthermore, sLoFNet performed, on average, 70 times faster than the LS-method.

CONCLUSION

Comparisons between LS and sLoFNet on simulated and in vivo WASSR MRI Z-spectra in terms of robustness against noise and decreased sample resolution, as well as time consumption, showed significant advantages for sLoFNet.

Tissue response curve-shape analysis of dynamic glucose-enhanced and dynamic contrast-enhanced magnetic resonance imaging in patients with brain tumor

Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p < 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.

A numerical human brain phantom for dynamic glucose-enhanced (DGE) MRI: On the influence of head motion at 3T

PURPOSE

Dynamic glucose-enhanced (DGE) MRI relates to a group of exchange-based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction.

METHODS

MPRAGE data from a tumor patient were used to simulate dynamic Z-spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head-motion-induced B0 -changes in presence of first-order shimming. The effect of retrospective motion correction was evaluated.

RESULTS

Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo-DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location.

CONCLUSION

DGE MRI studies can be corrupted by motion artifacts. Designing post-processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques.

Abnormal cerebral hemodynamics and blood-brain barrier permeability detected with perfusion MRI in systemic lupus erythematosus patients

OBJECTIVE

Dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) has previously shown alterations in cerebral perfusion in patients with systemic lupus erythematosus (SLE). However, the results have been inconsistent, in particular regarding neuropsychiatric (NP) SLE. Thus, we investigated perfusion-based measures in different brain regions in SLE patients with and without NP involvement, and additionally, in white matter hyperintensities (WMHs), the most common MRI pathology in SLE patients.

MATERIALS AND METHODS

We included 3 T MRI images (conventional and DSC) from 64 female SLE patients and 19 healthy controls (HC). Three different NPSLE attribution models were used: the Systemic Lupus International Collaborating Clinics (SLICC) A model (13 patients), the SLICC B model (19 patients), and the American College of Rheumatology (ACR) case definitions for NPSLE (38 patients). Normalized cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) were calculated in 26 manually drawn regions of interest and compared between SLE patients and HC, and between NPSLE and non-NPSLE patients. Additionally, normalized CBF, CBV and MTT, as well as absolute values of the blood-brain barrier leakage parameter (K2) were investigated in WMHs compared to normal appearing white matter (NAWM) in the SLE patients.

RESULTS

After correction for multiple comparisons, the most prevalent finding was a bilateral significant decrease in MTT in SLE patients compared to HC in the hypothalamus, putamen, right posterior thalamus and right anterior insula. Significant decreases in SLE compared to HC were also found for CBF in the pons, and for CBV in the bilateral putamen and posterior thalamus. Significant increases were found for CBF in the posterior corpus callosum and for CBV in the anterior corpus callosum. Similar patterns were found for both NPSLE and non-NPSLE patients for all attributional models compared to HC. However, no significant perfusion differences were revealed between NPSLE and non-NPSLE patients regardless of attribution model. The WMHs in SLE patients showed a significant increase in all perfusion-based metrics (CBF, CBV, MTT and K2) compared to NAWM.

CONCLUSION

Our study revealed perfusion differences in several brain regions in SLE patients compared to HC, independently of NP involvement. Furthermore, increased K2 in WMHs compared to NAWM may indicate blood-brain barrier dysfunction in SLE patients. We conclude that our results show a robust cerebral perfusion, independent from the different NP attribution models, and provide insight into potential BBB dysfunction and altered vascular properties of WMHs in female SLE patients. Despite SLE being most prevalent in females, a generalization of our conclusions should be avoided, and future studies including all sexes are needed.

Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging

Background

Estimation of the oxygen extraction fraction (OEF) by quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI) is promising but requires systematic evaluation. Extraction of OEF-related information from the tissue residue function in dynamic susceptibility contrast MRI (DSC-MRI) has also been proposed. In this study, whole-brain OEF repeatability was investigated, as well as the relationships between QSM-based OEF and DSC-MRI-based parameters, i.e., mean transit time (MTT) and an oxygen extraction index, referred to as apparent OEF (AOEF).

Method

Test-retest data were obtained from 20 healthy volunteers at 3 T. QSM maps were reconstructed from 3D gradient-echo MRI phase data, using morphology-enabled dipole inversion. DSC-MRI was accomplished using gradient-echo MRI at a temporal resolution of 1.24 s.

Results

The whole-brain QSM-based OEF was (40.4±4.8) % and, in combination with a previously published cerebral blood flow (CBF) estimate, this corresponds to a cerebral metabolic rate of oxygen level of CMRO2 = 3.36 ml O2/min/100 g. The intra-class correlation coefficient [ICC(2,1)] for OEF test-retest data was 0.73. The MTT-versus-OEF and AOEF-versus-OEF relationships showed correlation coefficients of 0.61 (p = 0.004) and 0.52 (p = 0.019), respectively.

Discussion

QSM-based OEF showed a convincing absolute level and good test-retest results in terms of the ICC. Moderate to good correlations between QSM-based OEF and DSC-MRI-based parameters were observed. The present results constitute an indicator of the level of robustness that can be achieved without applying extraordinary resources in terms of MRI equipment, imaging protocol, QSM reconstruction, and OEF analysis.

Comparison of MRI methods for measuring whole‐brain oxygen extraction fraction under different geometric conditions at 7T

Background and Purpose

Methods

Results

Conclusion

Towards robust glucose chemical exchange saturation transfer imaging in humans at 3 T: Arterial input function measurements and the effects of infusion time

Dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) has shown potential for tumor imaging using D-glucose as a biodegradable contrast agent. The DGE signal change is small at 3 T (around 1%) and accurate detection is hampered by motion. The intravenous D-glucose injection is associated with transient side effects that can indirectly generate subject movements. In this study, the aim was to study DGE arterial input functions (AIFs) in healthy volunteers at 3 T for different scanning protocols, as a step towards making the glucose chemical exchange saturation transfer (glucoCEST) protocol more robust. Two different infusion durations (1.5 and 4.0 min) and saturation frequency offsets (1.2 and 2.0 ppm) were used. The effect of subject motion on the DGE signal was studied by using motion estimates retrieved from standard retrospective motion correction to create pseudo-DGE maps, where the apparent DGE signal changes were entirely caused by motion. Furthermore, the DGE AIFs were compared with venous blood glucose levels. A significant difference (p = 0.03) between arterial baseline and postinfusion DGE signal was found after D-glucose infusion. The results indicate that the measured DGE AIF signal change depends on both motion and blood glucose concentration change, emphasizing the need for sufficient motion correction in glucoCEST imaging. Finally, we conclude that a longer infusion duration (e.g. 3-4 min) should preferably be used in glucoCEST experiments, because it can minimize the glucose infusion side effects without negatively affecting the DGE signal change.

Non-parametric deconvolution using Bézier curves for quantification of cerebral perfusion in dynamic susceptibility contrast MRI

Objective

Deconvolution is an ill-posed inverse problem that tends to yield non-physiological residue functions R(t) in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). In this study, the use of Bézier curves is proposed for obtaining physiologically reasonable residue functions in perfusion MRI.

Materials and methods

Cubic Bézier curves were employed, ensuring R(0) = 1, bounded-input, bounded-output stability and a non-negative monotonically decreasing solution, resulting in 5 parameters to be optimized. Bézier deconvolution (BzD), implemented in a Bayesian framework, was tested by simulation under realistic conditions, including effects of arterial delay and dispersion. BzD was also applied to DSC-MRI data from a healthy volunteer.

Results

Bézier deconvolution showed robustness to different underlying residue function shapes. Accurate perfusion estimates were observed, except for boxcar residue functions at low signal-to-noise ratio. BzD involving corrections for delay, dispersion, and delay with dispersion generally returned accurate results, except for some degree of cerebral blood flow (CBF) overestimation at low levels of each effect. Maps of mean transit time and delay were markedly different between BzD and block-circulant singular value decomposition (oSVD) deconvolution.

Discussion

A novel DSC-MRI deconvolution method based on Bézier curves was implemented and evaluated. BzD produced physiologically plausible impulse response, without spurious oscillations, with generally less CBF underestimation than oSVD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00995-0.

Effects of red blood cells with reduced deformability on cerebral blood flow and vascular water transport: measurements in rats using time-resolved pulsed arterial spin labelling at 9.4 T

Background

Our aim was to introduce damaged red blood cells (RBCs) as a tool for haemodynamic provocation in rats, hypothesised to cause decreased cerebral blood flow (CBF) and prolonged water capillary transfer time (CTT), and to investigate whether expected changes in CBF could be observed and if haemodynamic alterations were reflected by the CTT metric.

Methods

Damaged RBCs exhibiting a mildly reduced deformability were injected to cause aggregation of RBCs. Arterial spin labelling (ASL) magnetic resonance imaging experiments were performed at 9.4 T. Six datasets (baseline plus five datasets after injection) were acquired for each animal in a study group and a control group (13 and 10 female adult Wistar rats, respectively). For each dataset, ASL images at ten different inversion times were acquired. The CTT model was adapted to the use of a measured arterial input function, implying the use of a realistic labelling profile. Repeated measures ANOVA was used (alpha error = 0.05).

Results

After injection, significant differences between the study group and control group were observed for relative CBF in white matter (up to 20 percentage points) and putamen (up to 18–20 percentage points) and for relative CTT in putamen (up to 35–40 percentage points).

Conclusions

Haemodynamic changes caused by injection of damaged RBCs were observed by ASL-based CBF and CTT measurements. Damaged RBCs can be used as a tool for test and validation of perfusion imaging modalities. CTT model fitting was challenging to stabilise at experimental signal-to-noise ratio levels, and the number of free parameters was minimised.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41747-021-00243-z.

Mapping magnetization transfer saturation (MTsat ) in human brain at 7T: Protocol optimization under specific absorption rate constraints

PURPOSE

To optimize a whole-brain magnetization transfer saturation (MT_sat ) protocol at 7T, focusing on maximizing obtainable MT_sat under the constraints of specific absorption rate (SAR) and transmit field inhomogeneity, while avoiding bias and keeping scan time short.

THEORY AND METHODS

MT_sat is a semi-quantitative metric, obtained by spoiled gradient-echo MRI in the imaging steady-state. Optimization was based on an established 7T dual flip angle protocol, and focused on MT pulse, readout flip angle, repetition time (TR), offset frequency (Δ), and correction of residual effects from transmit field inhomogeneities by separate flip angle mapping.

RESULTS

A 100% SAR level was reached at a 180° MT pulse flip angle, using a compact sinc main lobe (4 ms duration) and minimum TR = 26.5 ms. The use of Δ = +2.0 kHz caused no discernible direct saturation, while Δ = -2.0 kHz resulted in 45% higher MT_sat in white matter (WM) compared to Δ = +2.0 kHz. A 4° readout flip angle eliminated bias while yielding a good signal-to-noise ratio. Increased TR yielded only a little increase in MT_sat , and TR = 26.5 ms (scan time 04:58 min) was thus selected. Post hoc transmit field correction clearly improved homogeneity, especially in WM.

CONCLUSIONS

The range of MT_sat is limited at 7T, and this can partly be overcome by the exploitation of the asymmetry of the macromolecular lineshape through the sign of Δ. To reduce scan time, a compact MT pulse with a sufficiently narrow frequency response should be used. TR and readout flip angle should be kept short/small. Transmit field correction through separate flip angle mapping is required.

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

OBJECTIVE

In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration.

MATERIAL AND METHODS

AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images.

RESULTS

AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s^-1 mM^-1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria.

DISCUSSION

Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

Estimation of diffusion, perfusion and fractional volumes using a multi-compartment relaxation-compensated intravoxel incoherent motion (IVIM) signal model

Compartmental diffusion MRI models that account for intravoxel incoherent motion (IVIM) of blood perfusion allow for estimation of the fractional volume of the microvascular compartment. Conventional IVIM models are known to be biased by not accounting for partial volume effects caused by free water and cerebrospinal fluid (CSF), or for tissue-dependent relaxation effects. In this work, a three-compartment model (tissue, free water and blood) that includes relaxation terms is introduced. To estimate the model parameters, in vivo human data were collected with multiple echo times (TE), inversion times (TI) and b-values, which allowed a direct relaxation estimate alongside estimation of perfusion, diffusion and fractional volume parameters. Compared to conventional two-compartment models (with and without relaxation compensation), the three-compartment model showed less effects of CSF contamination. The proposed model yielded significantly different volume fractions of blood and tissue compared to the non-relaxation-compensated model, as well as to the conventional two-compartment model, suggesting that previously reported parameter ranges, using models that do not account for relaxation, should be reconsidered.

Arterial Input Functions and Tissue Response Curves in Dynamic Glucose-Enhanced (DGE) Imaging: Comparison Between glucoCEST and Blood Glucose Sampling in Humans

Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative responses with a peak intensity that was of the order of 10 times smaller than the AIF peak and a shape that was susceptible to both noise and partial volume effects with CSF, attributed to the low contrast-to-noise ratio. The CSF response curves showed a rather large and steady increase of the glucose uptake during the scan, due to the rapid uptake of D-glucose in CSF. Importantly, and contrary to gadolinium studies, the curves differed substantially among volunteers, which was interpreted to be caused by variations in insulin response. In conclusion, while AIFs and tissue response curves can be measured in DGE experiments, partial volume effects, low concentration of D-glucose in tissue, and osmolality effects between tissue and blood may prohibit quantification of normal tissue perfusion parameters. However, separation of tumor responses from normal tissue responses would most likely be feasible.

MRI-Based Quantification of Magnetic Susceptibility in Gel Phantoms: Assessment of Measurement and Calculation Accuracy

The local magnetic field inside and around an object in a magnetic resonance imaging unit depends on the magnetic susceptibility of the object being magnetized, in combination with its geometry/orientation. Magnetic susceptibility can thus be exploited as a source of tissue contrast, and susceptibility imaging may also become a useful tool in contrast agent quantification and for assessment of venous oxygen saturation levels. In this study, the accuracy of an established procedure for quantitative susceptibility mapping (QSM) was investigated. Three gel phantoms were constructed with cylinders of varying susceptibility and geometry. Experimental results were compared with simulated and analytically calculated data. An expected linear relationship between estimated susceptibility and concentration of contrast agent was observed. Less accurate QSM-based susceptibility values were observed for cylindrical objects at angles, relative to the main magnetic field, that were close to or larger than the magic angle. Results generally improved for large objects/high spatial resolution and large volume coverage. For simulated phase maps, accurate susceptibility quantification by QSM was achieved also for more challenging geometries. The investigated QSM algorithm was generally robust to changes in measurement and calculation parameters, but experimental phase data of sufficient quality may be difficult to obtain in certain geometries.

Dynamic Susceptibility Contrast MRI at 7 T: Tail-Scaling Analysis and Inferences About Field Strength Dependence

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) following bolus injection of gadolinium contrast agent (CA) is widely used for the estimation of brain perfusion parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) for both clinical and research purposes. Although it is predicted that DSC-MRI will have superior performance at high magnetic field strengths, to the best of our knowledge, there are no reports of 7 T DSC-MRI in the literature. It is plausible that the transfer of DSC-MRI to 7 T may be accompanied by increased R₂* relaxivity in tissue and a larger difference in ΔR₂*-versus-concentration relationships between tissue and large vessels. If not accounted for, this will subsequently result in apparent CBV and CBF estimates that are higher than those reported previously at lower field strengths. The aims of this study were therefore to assess the feasibility of 7 T DSC-MRI and to investigate the apparent field-strength dependence of CBV and CBF estimates. In total, 8 healthy volunteers were examined using DSC-MRI at 7 T. A reduced CA dose of 0.05 mmol/kg was administered to decrease susceptibility artifacts. CBV, CBF, and MTT maps were calculated using standard DSC-MRI tracer-kinetic theory. Subject-specific arterial partial volume correction factors were obtained using a tail-scaling approach. Compared with literature values obtained using the tail-scaling approach at 1.5 T and 3 T, the CBV and CBF values of the present study were found to be further overestimated. This observation is potentially related to an inferred field-strength dependence of transverse relaxivities, although issues related to the CA dose must also be considered.

Separating blood and water: Perfusion and free water elimination from diffusion MRI in the human brain

The assessment of the free water fraction in the brain provides important information about extracellular processes such as atrophy and neuroinflammation in various clinical conditions as well as in normal development and aging. Free water estimates from diffusion MRI are assumed to account for freely diffusing water molecules in the extracellular space, but may be biased by other pools of molecules in rapid random motion, such as the intravoxel incoherent motion (IVIM) of blood, where water molecules perfuse in the randomly oriented capillary network. The goal of this work was to separate the signal contribution of the perfusing blood from that of free-water and of other brain diffusivities. The influence of the vascular compartment on the estimation of the free water fraction and other diffusivities was investigated by simulating perfusion in diffusion MRI data. The perfusion effect in the simulations was significant, especially for the estimation of the free water fraction, and was maintained as long as low b-value data were included in the analysis. Two approaches to reduce the perfusion effect were explored in this study: (i) increasing the minimal b-value used in the fitting, and (ii) using a three-compartment model that explicitly accounts for water molecules in the capillary blood. Estimation of the model parameters while excluding low b-values reduced the perfusion effect but was highly sensitive to noise. The three-compartment model fit was more stable and additionally, provided an estimation of the volume fraction of the capillary blood compartment. The three-compartment model thus disentangles the effects of free water diffusion and perfusion, which is of major clinical importance since changes in these components in the brain may indicate different pathologies, i.e., those originating from the extracellular space, such as neuroinflammation and atrophy, and those related to the vascular space, such as vasodilation, vasoconstriction and capillary density. Diffusion MRI data acquired from a healthy volunteer, using multiple b-shells, demonstrated an expected non-zero contribution from the blood fraction, and indicated that not accounting for the perfusion effect may explain the overestimation of the free water fraction evinced in previous studies. Finally, the applicability of the method was demonstrated with a dataset acquired using a clinically feasible protocol with shorter acquisition time and fewer b-shells.

Use of an Enhanced Gradient System for Diffusion MR Imaging with Motion-Artifact Reduction

Purpose:

A spin-echo diffusion-sensitized pulse sequence using high gradients (23 mT/m) is introduced.

Material and Methods:

In order to minimize motion artefacts, velocity-compensating gradients, ECG-triggering and post-processing with phase correction and raw data averaging using navigator echoes was performed. The in vitro ratio of diffusion coefficients for water and acetone was determined and the water self-diffusion coefficient at different temperatures was evaluated. The pulse sequence was tested in 7 healthy volunteers and in 2 tumour patients with astrocytomas of grades I—II and III—IV. Both single-slice and multi-slice techniques were used.

Results:

The incorporation of phase correction clearly improved the quality of both diffusion-encoded images and the calculated diffusion maps. Mean values of the diffusion coefficients in vivo were for CSF 2.66×10−9 m2/s and for white and grey matter 0.69×10−9 m2/s and 0.87×10−9 m2/s, respectively.

Conclusion:

Velocity-compensating gradients in combination with a high gradient strength were shown to be useful for in vivo diffusion MR imaging.

Deuterium MR Spectroscopy at 4.7 T

Deuterium MR spectroscopy was used for the determination of tissue blood flow (TBF). The tracer D2O was injected into the tissue of interest, and tracer washout was followed using a 4.7 T spectroscopy/imaging unit. Normal subcutaneous tissue in rats was studied, as well as tissue influenced by vasoactive agents (papaverine and adrenaline). The vasoactive agents introduced changes of 40% in TBF, compared with normal tissue. Normal tissue measurements were repeated using various D2O injection volumes (5–400 μl). The injection volume 5 μl gave TBF 11.7 ± 2.0 ml/100 g·min (mean ± 1 SD). This value was 40% higher than corresponding values observed at larger injection volumes (200–400 μl). This injection volume effect is probably partly due to a capillary dilution caused by tracer administration, and partly related to the non-physiological deuterium signal decrease observed in dead rats. Blood flow measurements in human colon tumours implanted in nude mice showed a rather poor reproducibility, not improved by the use of a multiple site injection technique.

A linear mixed perfusion model for tissue partial volume correction of perfusion estimates in dynamic susceptibility contrast MRI: Impact on absolute quantification, repeatability, and agreement with pseudo-continuous arterial spin labeling

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Dynamic susceptibility contrast perfusion MRI using phase-based venous output functions: comparison with pseudo-continuous arterial spin labelling and assessment of contrast agent concentration in large veins

OBJECTIVES

Contrast agent (CA) relaxivities are generally not well established in vivo, and the relationship between frequency/phase shift and magnetic susceptibility might be a useful alternative for CA quantification.

MATERIALS AND METHODS

Twenty volunteers (25-84 years old) were investigated using test-retest pre-bolus dynamic susceptibility-contrast (DSC) magnetic resonance imaging (MRI). The pre-bolus phase-based venous output function (VOF) time integral was used for arterial input function (AIF) rescaling. Resulting cerebral blood flow (CBF) data for grey matter (GM) were compared with pseudo-continuous arterial spin labelling (ASL). During the main bolus CA passage, the apparent spatial shift (pixel shift) of the superior sagittal sinus (seen in single-shot echo-planar imaging (EPI)) was converted to CA concentration and compared with conventional ΔR2*-based data and with a predicted phase-based VOF from the pre-bolus experiment.

RESULTS

The phase-based pre-bolus VOF resulted in a reasonable inter-individual GM CBF variability (coefficient of variation 28 %). Comparison with ASL CBF values implied a tissue R2*-relaxivity of 32 mM^-1 s^-1. Pixel-shift data at low concentrations (data not available at peak concentrations) were in reasonable agreement with the predicted phase-based VOF.

CONCLUSION

Susceptibility-induced phase shifts and pixel shifts are potentially useful for large-vein CA quantification. Previous predictions of a higher R2*-relaxivity in tissue than in blood were supported.

Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data

The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit.

Quantification of normal cerebral oxygen extraction and oxygen metabolism by phase-based MRI susceptometry: evaluation of repeatability using two different imaging protocols

INTRODUCTION

Global oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO₂ ) were quantified in a test-retest study. Cerebral blood flow (CBF) data, required for CMRO₂ estimation, were obtained using dynamic susceptibility contrast MRI (DSC-MRI). OEF and CMRO₂ were quantified using two separate data sets, that is, conventional high-resolution (HR) gradient echo (GRE) phase maps as well as echo planar imaging (EPI) phase maps taken from the baseline (precontrast) part of the DSC-MRI time series. The EPI phase data were included to elucidate whether an extra HR-GRE scan is needed to obtain information about OEF and CMRO₂ , or if this information can be extracted from the DSC-MRI experiment only.

METHODS

Twenty healthy volunteers were scanned using 3 T MRI on two occasions. Oxygen saturation levels were obtained from phase data measured in the great cerebral vein of Galen, based on HR-GRE as well as EPI phase maps. In combination with DSC-MRI CBF, this allowed for calculation of OEF and CMRO₂ .

RESULTS

High-resolution-gradient echo- and EPI-based phase images resulted in similar OEF spread and repeatability, with coefficients of variation/intraclass correlation coefficients of 0·26/0·95 and 0·23/0·81, respectively. Absolute OEF values (HR-GRE: 0·40 ± 0·11, EPI: 0·35 ± 0·08) were consistent with literature data. CMRO₂ showed similar repeatability, somewhat increased spread and reasonable absolute values (HR-GRE: 3·23 ± 1·26 ml O₂ /100 g min^-1 , EPI: 2·79 ± 0·89 ml O₂ /100 g min^-1 ).

DISCUSSION

In general, the results obtained by HR-GRE and EPI showed comparable characteristics. The EPI methodology could potentially be improved using a slightly modified DSC-MRI protocol (e.g. with regard to spatial resolution and slice gap).

Accuracy of Parenchymal Cerebral Blood Flow Measurements Using Pseudocontinuous Arterial Spin-Labeling in Healthy Volunteers

BACKGROUND AND PURPOSE

The arterial spin-labeling method for CBF assessment is widely available, but its accuracy is not fully established. We investigated the accuracy of a whole-brain arterial spin-labeling technique for assessing the mean parenchymal CBF and the effect of aging in healthy volunteers. Phase-contrast MR imaging was used as the reference method.

MATERIALS AND METHODS

Ninety-two healthy volunteers were included: 49 young (age range, 20-30 years) and 43 elderly (age range, 65-80 years). Arterial spin-labeling parenchymal CBF values were averaged over the whole brain to quantify the mean pCBF(ASL) value. Total CBF was assessed with phase-contrast MR imaging as the sum of flows in the internal carotid and vertebral arteries, and subsequent division by brain volume returned the pCBF(PCMRI) value. Accuracy was considered as good as that of the reference method if the systematic difference was less than 5 mL/min/100 g of brain tissue and if the 95% confidence intervals were equal to or better than ±10 mL/min/100 g.

RESULTS

pCBF(ASL) correlated to pCBF(PCMRI) (r = 0.73; P < .001). Significant differences were observed between the pCBF(ASL) and pCBF(PCMRI) values in the young (P = .001) and the elderly (P < .001) volunteers. The systematic differences (mean ± 2 standard deviations) were -4 ± 14 mL/min/100 g in the young subjects and 6 ± 12 mL/min/100 g in the elderly subjects. Young subjects showed higher values than the elderly subjects for pCBF(PCMRI) (young, 57 ± 8 mL/min/100 g; elderly, 54 ± 7 mL/min/100 g; P = .05) and pCBF(ASL) (young, 61 ± 10 mL/min/100 g; elderly, 48 ± 10 mL/min/100 g; P < .001).

CONCLUSIONS

The limits of agreement were too wide for the arterial spin-labeling method to be considered satisfactorily accurate, whereas the systematic overestimation in the young subjects and underestimation in the elderly subjects were close to acceptable. The age-related decrease in parenchymal CBF was augmented in arterial spin-labeling compared with phase-contrast MR imaging.

Measurement of vascular water transport in human subjects using time-resolved pulsed arterial spin labelling

Most approaches to arterial spin labelling (ASL) data analysis aim to provide a quantitative measure of the cerebral blood flow (CBF). This study, however, focuses on the measurement of the transfer time of blood water through the capillaries to the parenchyma (referred to as the capillary transfer time, CTT) as an alternative parameter to characterise the haemodynamics of the system. The method employed is based on a non-compartmental model, and no measurements need to be added to a common time-resolved ASL experiment. Brownian motion of labelled spins in a potential was described by a one-dimensional general Langevin equation as the starting point, and as a Fokker-Planck differential equation for the averaged distribution of labelled spins at the end point, which takes into account the effects of flow and dispersion of labelled water by the pseudorandom nature of the microvasculature and the transcapillary permeability. Multi-inversion time (multi-TI) ASL data were acquired in 14 healthy subjects on two occasions in a test-retest design, using a pulsed ASL sequence and three-dimensional gradient and spin echo (3D-GRASE) readout. Based on an error analysis to predict the size of a region of interest (ROI) required to obtain reasonably precise parameter estimates, data were analysed in two relatively large ROIs, i.e. the occipital lobe (OC) and the insular cortex (IC). The average values of CTT in OC were 260 ± 60 ms in the first experiment and 270 ± 60 ms in the second experiment. The corresponding IC values were 460 ± 130 ms and 420 ± 139 ms, respectively. Information related to the water transfer time may be important for diagnostics and follow-up of cerebral conditions or diseases characterised by a disrupted blood-brain barrier or disturbed capillary blood flow.

Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling

Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume.

Reduction of arterial partial volume effects for improved absolute quantification of DSC-MRI perfusion estimates: comparison between tail scaling and prebolus administration

PURPOSE

To evaluate and mutually compare the tail-scaling approach and the prebolus administration concept for reduction of arterial partial volume effects (PVEs), because reproducible absolute quantification of cerebral blood flow (CBF) by dynamic susceptibility contrast magnetic resonance imaging (MRI) is often hampered by PVEs in the arterial input function (AIF) registration.

MATERIALS AND METHODS

Twenty healthy volunteers were scanned in a test-retest study with 7-20 days between investigations to examine the quantitative values and the repeatability of CBF estimates obtained from the tail-scaling and the prebolus administration approaches.

RESULTS

Average grey matter CBF was 80 ± 18 mL/100 g/min (mean ± SD) using tail-scaling and 56 ± 18 mL/100 g/min using prebolus administration. The intraclass correlation coefficient was 0.52 for the tail-scaling approach and 0.86 for the prebolus administration concept.

CONCLUSION

Both correction methods resulted in considerably reduced arterial PVEs, leading to quantitative estimates of perfusion approaching those typically obtained by other perfusion modalities. The CBF estimates obtained using the prebolus administration concept showed superior repeatability. Potential sources of uncertainty in the tail-scaling approach include the use of venous concentration curves influenced by PVEs or by geometric distortions (ie, vessel pixel shifts) in the steady-state period.

Automatic brain segmentation using fractional signal modeling of a multiple flip angle, spoiled gradient-recalled echo acquisition

OBJECT

The aim of this study was to demonstrate a new automatic brain segmentation method in magnetic resonance imaging (MRI).

MATERIALS AND METHODS

The signal of a spoiled gradient-recalled echo (SPGR) sequence acquired with multiple flip angles was used to map T1, and a subsequent fit of a multi-compartment model yielded parametric maps of partial volume estimates of the different compartments. The performance of the proposed method was assessed through simulations as well as in-vivo experiments in five healthy volunteers.

RESULTS

Simulations indicated that the proposed method was capable of producing robust segmentation maps with good reliability. Mean bias was below 3% for all tissue types, and the corresponding similarity index (Dice's coefficient) was over 95% (SNR = 100). In-vivo experiments yielded realistic segmentation maps, with comparable quality to results obtained with an established segmentation method. Relative whole-brain cerebrospinal fluid, grey matter, and white matter volumes were (mean ± SE) respectively 6.8 ± 0.5, 47.3 ± 1.1, and 45.9 ± 1.3% for the proposed method, and 7.5 ± 0.6, 46.2 ± 1.2, and 46.3 ± 0.9% for the reference method.

CONCLUSION

The proposed approach is promising for brain segmentation and partial volume estimation. The straightforward implementation of the method is attractive, and protocols that already rely on SPGR-based T1 mapping may employ this method without additional scans.

Absolute quantification of perfusion by dynamic susceptibility contrast MRI using Bookend and VASO steady-state CBV calibration: a comparison with pseudo-continuous ASL

OBJECTIVE

Dynamic susceptibility contrast MRI (DSC-MRI) tends to return elevated estimates of cerebral blood flow (CBF) and cerebral blood volume (CBV). In this study, subject-specific calibration factors (CFs), based on steady-state CBV measurements, were applied to rescale the absolute level of DSC-MRI CBF.

MATERIALS AND METHODS

Twenty healthy volunteers were scanned in a test-retest approach. Independent CBV measurements for calibration were accomplished using a T1-based contrast agent steady-state method (referred to as Bookend), as well as a blood-nulling vascular space occupancy (VASO) approach. Calibrated DSC-MRI was compared with pseudo-continuous arterial spin labeling (pCASL).

RESULTS

For segmented grey matter (GM) regions of interests (ROIs), pCASL-based CBF was 63 ± 11 ml/(min 100 g) (mean ± SD). Nominal CBF from non-calibrated DSC-MRI was 277 ± 61 ml/(min 100 g), while calibrations resulted in 56 ± 23 ml/(min 100 g) (Bookend) and 52 ± 16 ml/(min 100 g) (VASO). Calibration tended to eliminate the overestimation, although the repeatability was generally moderate and the correlation between calibrated DSC-MRI and pCASL was low (r < 0.25). However, using GM instead of WM ROIs for extraction of CFs resulted in improved repeatability.

CONCLUSION

Both calibration approaches provided reasonable absolute levels of GM CBF, although the calibration methods suffered from low signal-to-noise ratio, resulting in weak repeatability and difficulties in showing high degrees of correlation with pCASL measurements.

Dynamic susceptibility contrast MRI with a prebolus contrast agent administration design for improved absolute quantification of perfusion

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Effects of blood ΔR2* non-linearity on absolute perfusion quantification using DSC-MRI: comparison with Xe-133 SPECT

PURPOSE

To evaluate whether a non-linear blood ΔR2*-versus-concentration relationship improves quantitative cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast (DSC) MRI in a comparison with Xe-133 SPECT CBF in healthy volunteers.

MATERIAL AND METHODS

Linear as well as non-linear relationships between ΔR2* and contrast agent concentration in blood were applied to the arterial input function (AIF) and the venous output function (VOF) from DSC-MRI. To reduce partial volume effects in the AIF, the arterial time integral was rescaled using a corrected VOF scheme.

RESULTS

Under the assumption of proportionality between the two modalities, the relationship CBF(MRI)=0.58CBF(SPECT) (r=0.64) was observed using the linear relationship and CBF(MRI)=0.51CBF(SPECT) (r=0.71) using the non-linear relationship.

DISCUSSION

A smaller ratio of the VOF time integral to the AIF time integral and a somewhat better correlation between global DSC-MRI and Xe-133 SPECT CBF estimates were observed using the non-linear relationship. The results did not, however, confirm the superiority of one model over the other, potentially because realistic AIF signal data may well originate from a combination of blood and surrounding tissue.

Regional values of diffusional kurtosis estimates in the healthy brain

Purpose

To provide estimates of the diffusional kurtosis in the healthy brain in anatomically defined areas and list these along previously reported values in pathologies.

Materials and Methods

Thirty-six volunteers (mean age = 33.1 years; range, 19–64 years) underwent diffusional kurtosis imaging. Mean kurtosis (MK), radial kurtosis (RK), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) were determined in 26 anatomical structures. Parameter estimates were assessed regarding age dependence.

Results

MK varied from 1.38 in the splenium of the corpus callosum to 0.66 in the caudate head, MD varied from 0.68 to 0.62 μm²/ms and FA from 0.87 to 0.29. MK, and FA showed a strong positive correlation, RK and RD a strong negative correlation. Parameter estimates showed age correlation in some regions; also the average MK and RK for all WM and all GM areas, respectively, were negatively correlated with age.

Conclusion

DKI parameter estimates MK and RK varied depending on the anatomical region and varied with age in pooled WM and GM data. MK estimates in the internal capsule, corpus callosum, and thalamus were consistent with previous studies. The range of values of MK and RK in healthy brain overlapped with that in pathologies. J. Magn. Reson. Imaging 2013;37:610–618. © 2012 Wiley Periodicals, Inc.

Core curriculum for medical physicists in radiology. Recommendations from an EFOMP/ESR working group

Some years ago it was decided that a European curriculum should be developed for medical physicists professionally engaged in the support of clinical diagnostic imaging departments. With this in mind, EFOMP (European Federation of Organisations for Medical Physics) in association with ESR (European Society of Radiology) nominated an expert working group. This curriculum is now to hand. The curriculum is intended to promote best patient care in radiology departments through the harmonization of education and training of medical physicists to a high standard in diagnostic radiology. It is recommended that a medical physicist working in a radiology department should have an advanced level of professional expertise in X-ray imaging, and additionally, depending on local availability, should acquire knowledge and competencies in overseeing ultrasound imaging, nuclear medicine, and MRI technology. By demonstrating training to a standardized curriculum, medical physicists throughout Europe will enhance their mobility, while maintaining local high standards of medical physics expertise. This document also provides the basis for improved implementation of articles in the European medical exposure directives related to the medical physics expert. The curriculum is divided into three main sections: The first deals with general competencies in the principles of medical physics. The second section describes specific knowledge and skills required for a medical physicist (medical physics expert) to operate clinically in a department of diagnostic radiology. The final section outlines research skills that are also considered to be necessary and appropriate competencies in a career as medical physicist.

Can resting-state functional MRI serve as a complement to task-based mapping of sensorimotor function? A test-retest reliability study in healthy volunteers

PURPOSE

To investigate if resting-state functional MRI (fMRI) reliably can serve as a complement to task-based fMRI for presurgical mapping of the sensorimotor cortex.

MATERIALS AND METHODS

Functional data were obtained in 10 healthy volunteers using a 3 Tesla MRI system. Each subject performed five bilateral finger tapping experiments interleaved with five resting-state experiments. Following preprocessing, data from eight volunteers were further analyzed with the general linear model (finger tapping data) and independent component analysis (rest data). Test-retest reliability estimates (hit rate and false alarm rate) for resting-state fMRI activation of the sensorimotor network were compared with the reliability estimates for task-evoked activation of the sensorimotor cortex. The reliability estimates constituted a receiver operating characteristics curve from which the area under the curve (AUC) was calculated. Statistical testing was performed to compare the two groups with respect to reliability.

RESULTS

The AUC was generally higher for the task experiments, although median AUC was not significantly different on a group level. Also, the two groups showed comparable levels of within-group variance.

CONCLUSION

Test-retest reliability was comparable between resting-state measurements and task-based fMRI, suggesting that presurgical mapping of functional networks can be a supplement to task-based fMRI in cases where patient status excludes task-based fMRI.

Evaluating the accuracy and precision of a two-compartment Kärger model using Monte Carlo simulations

Specific parameters of the neuronal tissue microstructure, such as axonal diameters, membrane permeability and intracellular water fractions are assessable using diffusion MRI. These parameters are commonly estimated using analytical models, which may introduce bias in the estimated parameters due to the approximations made when deriving the models. As an alternative to using analytical models, a database of signal curves generated by fast Monte Carlo simulations can be employed. Simulated diffusion MRI measurements were generated and evaluated using the two-compartment Kärger model as well as the simulation model based on a database containing signal curves from approximately 60000 simulations performed with different combinations of microstructural parameters. A protocol based on a pulsed gradient spin echo sequence with diffusion times of 30 and 60 ms and with gradient amplitudes obtainable with a clinical MRI scanner was employed for the investigations. When using the analytical model, a major negative bias (up to approximately 25%) in the estimated intracellular volume fraction was observed for short exchange times, while almost no bias was seen for the simulation model. In general, the simulation model improved the accuracy of the estimated parameters as compared to the analytical model, except for the exchange time parameter.

Dimensionality reduction of fMRI time series data using locally linear embedding

OBJECTIVE

Data-driven methods for fMRI analysis are useful, for example, when an a priori model of signal variations is unavailable. However, activation sources are typically assumed to be linearly mixed, although non-linear properties of fMRI data, including resting-state data, have been observed. In this work, the non-linear locally linear embedding (LLE) algorithm is introduced for dimensionality reduction of fMRI time series data.

MATERIALS AND METHODS

LLE performance was optimised and tested using simulated and volunteer data for task-evoked responses. LLE was compared with principal component analysis (PCA) as a preprocessing step to independent component analysis (ICA). Using an example data set with known non-linear properties, LLE-ICA was compared with PCA-ICA and non-linear PCA-ICA. A resting-state data set was analysed to compare LLE-ICA and PCA-ICA with respect to identifying resting-state networks.

RESULTS

LLE consistently found task-related components as well as known resting-state networks, and the algorithm compared well to PCA. The non-linear example data set demonstrated that LLE, unlike PCA, can separate non-linearly modulated sources in a low-dimensional subspace. Given the same target dimensionality, LLE also performed better than non-linear PCA.

CONCLUSION

LLE is promising for fMRI data analysis and has potential advantages compared with PCA in terms of its ability to find non-linear relationships.

Absolute quantification of cerebral blood flow: correlation between dynamic susceptibility contrast MRI and model-free arterial spin labeling

PURPOSE

To compare absolute cerebral blood flow (CBF) estimates obtained by model-free arterial spin labeling (ASL) and dynamic susceptibility contrast MRI (DSC-MRI), corrected for partial volume effects (PVEs).

METHODS

CBF was measured using DSC-MRI and model-free ASL (quantitative signal targeting with alternating radiofrequency labeling of arterial regions) at 3 T in 15 subjects with brain tumor, and the two modalities were compared with regard to CBF estimates in normal gray matter (GM) and DSC-to-ASL CBF ratios in selected tumor regions. The DSC-MRI CBF maps were calculated using a global arterial input function (AIF) from the sylvian-fissure region, but, in order to minimize PVEs, the AIF time integral was rescaled by a venous output function time integral obtained from the sagittal sinus.

RESULTS

In GM, the average DSC-MRI CBF estimate was 150+/-45 ml/(min 100 g) (mean+/-SD) while the corresponding ASL CBF was 44+/-10 ml/(min 100 g). The linear correlation between GM CBF estimates obtained by DSC-MRI and ASL was r=.89, and observed DSC-to-ASL CBF ratios differed by less than 3% between GM and tumor regions.

CONCLUSIONS

A satisfactory positive linear correlation between the CBF estimates obtained by model-free ASL and DSC-MRI was observed, and DSC-to-ASL CBF ratios showed no obvious tissue dependence.

Diffusion-weighted MRI measurements on stroke patients reveal water-exchange mechanisms in sub-acute ischaemic lesions

The aim of this study was to investigate the diffusion time dependence of signal-versus-b curves obtained from diffusion-weighted magnetic resonance imaging (DW-MRI) of sub-acute ischaemic lesions in stroke patients. In this case series study, 16 patients with sub-acute ischaemic stroke were examined with DW-MRI using two different diffusion times (60 and 260 ms). Nine of these patients showed sufficiently large lesions without artefacts to merit further analysis. The signal-versus-b curves from the lesions were plotted and analysed using a two-compartment model including compartmental exchange. To validate the model and to aid the interpretation of the estimated model parameters, Monte Carlo simulations were performed. In eight cases, the plotted signal-versus-b curves, obtained from the lesions, showed a signal-curve split-up when data for the two diffusion times were compared, revealing effects of compartmental water exchange. For one of the patients, parametric maps were generated based on the extracted model parameters. These novel observations suggest that water exchange between different water pools is measurable and thus potentially useful for clinical assessment. The information can improve the understanding of the relationship between the DW-MRI signal intensity and the microstructural properties of the lesions.