Body composition profiling at 0.55T: Feasibility and precision.

PURPOSE: Body composition MRI captures the distribution of fat and lean tissues throughout the body, and provides valuable biomarkers of obesity, metabolic disease, and muscle disorders, as well as risk assessment. Highly reproducible protocols have been developed for 1.5T and 3T MRI. The purpose of this work was to demonstrate the feasibility and test-retest repeatability of MRI body composition profiling on a 0.55T whole-body system. METHODS: Healthy adult volunteers were scanned on a whole-body 0.55T MRI system using the integrated body RF coil. Experiments were performed to refine parameter settings such as TEs, resolution, flip angle, bandwidth, acceleration, and oversampling factors. The final protocol was evaluated using a test-retest study with subject removal and replacement in 10 adult volunteers (5 M/5F, age 25-60, body mass index 20-30). RESULTS: Compared to 1.5T and 3T, the optimal flip angle at 0.55T was higher (15°), due to the shorter T1 times, and the optimal echo spacing was larger, due to smaller chemical shift between water and fat. Overall image quality was comparable to conventional field strengths, with no significant issues with fat/water swapping or inadequate SNR. Repeatability coefficient of visceral fat, subcutaneous fat, total thigh muscle volume, muscle fat infiltration, and liver fat were 11.8 cL (2.2%), 46.9 cL (1.9%), 14.6 cL (0.5%), 0.1 pp (2%), and 0.2 pp (5%), respectively (coefficient of variation in parenthesis). CONCLUSIONS: We demonstrate that 0.55T body composition MRI is feasible and present optimized scan parameters. The resulting images provide satisfactory quality for automated post-processing and produce repeatable results.

Quantitative Muscle Analysis in FSHD Using Whole-Body Fat-Referenced MRI: Composite Scores for Longitudinal and Cross-sectional Analysis.

BACKGROUND AND OBJECTIVES: Facioscapulohumeral muscular dystrophy (FSHD) is a rare, debilitating disease characterized by progressive muscle weakness. MRI is a sensitive assessment of disease severity and progression. We developed a quantitative whole-body (WB) musculoskeletal MRI (WB-MSK-MRI) protocol analyzing muscles in their entirety. This study aimed to assess WB-MSK-MRI as a potential imaging biomarker providing reliable measurements of muscle health that capture disease heterogeneity and clinically meaningful composite assessments correlating with severity and more responsive to change in clinical trials. METHODS: Participants aged 18-65 years, with genetically confirmed FSHD1, clinical severity 2 to 4 (Ricci scale, range 0-5), and ≥1 short tau inversion recovery-positive lower extremity muscle eligible for needle biopsy, enrolled at 6 sites and were imaged twice 4-12 weeks apart. Volumetric analysis of muscle fat infiltration (MFI), muscle fat fraction (MFF), and lean muscle volume (LMV) in 18 (36 total) muscles from bilateral shoulder, proximal arm, trunk, and legs was performed after automated atlas-based segmentation, followed by manual verification. A WB composite score, including muscles at highest risk for progression, and functional cross-sectional composites for correlation with relevant functional outcomes including timed up and go (TUG), FSHD-TUG, and reachable workspace (RWS), were developed. RESULTS: Seventeen participants enrolled in this study; 16 follow-up MRIs were performed at 52 days (range 36-85 days). Functional cross-sectional composites (MFF and MFI) showed moderate to strong correlations: TUG (ρ = 0.71, ρ = 0.83), FSHD-TUG (ρ = 0.73, ρ = 0.73), and RWS (left arm: ρ = -0.71, ρ = -0.53; right arm: ρ = -0.61, ρ = -0.65). WB composite variability: LMVtot, coefficient of variation (CV) 1.9% and 3.4%; MFFtot, within-subject SD (Sw) 0.5% and 1.5%; and MFItot (Sw), 0.3% and 0.4% for normal and intermediate muscles, respectively. CV and Sw were higher in intermediate (MFI ≥0.10; MFF <0.50) than in normal (MFI <0.10, MFF <0.50) muscles. DISCUSSION: We developed a WB-MSK-MRI protocol and composite measures that capture disease heterogeneity and assess muscle involvement as it correlates with FSHD-relevant clinical endpoints. Functional composites robustly correlate with functional assessments. Stability of the WB composite shows that it could be an assessment of change in therapeutic clinical trials. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that quantitative WB-MSK-MRI findings associate with FSHD1 severity measured using established functional assessments.

Quantitative muscle analysis in facioscapulohumeral muscular dystrophy using whole-body fat-referenced MRI: Protocol development, multicenter feasibility, and repeatability.

INTRODUCTION/AIMS: Functional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole-body fat-referenced magnetic resonance imaging (MRI) for use in multisite clinical trials. METHODS: Subjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0-5), were enrolled at six sites and imaged twice 4-12 weeks apart with T1-weighted two-point Dixon MRI covering the torso and upper and lower extremities. Thirty-six muscles were volumetrically segmented using semi-automatic multi-atlas-based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat-referenced quantification. RESULTS: Seventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within-patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%. DISCUSSION: We developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders.

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.

Reproducibility and repeatability of MRI-based body composition analysis.

PURPOSE: There is an absence of reproducibility studies on MRI-based body composition analysis in current literature. Therefore, the aim of this study was to investigate the between-scanner reproducibility and the repeatability of a method for MRI-based body composition analysis. METHODS: Eighteen healthy volunteers of varying body mass index and adiposity were each scanned twice on five different 1.5T and 3T scanners from three different vendors. Two-point Dixon neck-to knee images and two additional liver scans were acquired with similar protocols. Visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (ASAT) volume, thigh muscle volume, and muscle fat infiltration (MFI) in the thigh muscle were measured. Liver proton density fat fraction (PDFF) was assessed using two different methods, the scanner vendor's 6-point method and an in-house 2-point method. Within-scanner test-retest repeatability and between-scanner reproducibility were calculated using analysis of variance. RESULTS: Repeatability coefficients were 13 centiliters (cl) (VAT), 24 cl (ASAT), 17 cl (total thigh muscle volume), 0.53% (MFI), and 1.27-1.37% for liver PDFF. Reproducibility coefficients were 24 cl (VAT), 42 cl (ASAT), 31 cl (total thigh muscle volume), 1.44% (MFI), and 2.37-2.40% for liver PDFF. CONCLUSION: For all measures except MFI, the within-scanner repeatability explained much of the overall reproducibility. The two methods for measuring liver fat had similar reproducibility. This study showed that the investigated method eliminates effects due to scanner differences. The results can be used for power calculations in clinical studies or to better understand the scanner-induced variability in clinical applications.

Cerebral Perfusion Does Not Increase after Shunt Surgery for Normal Pressure Hydrocephalus.

BACKGROUND AND PURPOSE: Cerebral blood flow (CBF) has been reported to increase after shunt surgery in patients with idiopathic normal pressure hydrocephalus (iNPH). The aims of this study were to investigate if CBF, measured using the noninvasive perfusion MRI method arterial spin labeling (ASL), increased after shunt surgery, if postoperative change in CBF correlated with improvement in symptoms, and if baseline CBF data correlated with postoperative outcome. METHODS: Twenty-three patients with iNPH were prospectively included and examined with MRI of the brain and clinical tests of symptoms at baseline. Eighteen of the patients were treated with shunt implantation and were reexamined with clinical tests and MRI 3 months postoperatively. The MRI protocol included a pseudo-continuous ASL sequence for perfusion imaging. The perfusion was measured in 12 manually drawn regions of interest (ROIs). RESULTS: In the whole sample, CBF did not increase after shunting in any ROI. Preoperative CBF in medial frontal cortex correlated with an improvement in urinary incontinence after shunt surgery, r = .53, P = .022. There were no correlations between change in CBF and change in clinical symptoms postoperatively. CONCLUSIONS: The clinical value of ASL in the work-up of patients with iNPH is uncertain. In this study, ASL could not predict outcome after shunt surgery and there were no correlations between change in CBF and change in clinical symptoms after shunt surgery.

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.

CEST, ASL, and magnetization transfer contrast: How similar pulse sequences detect different phenomena.

Chemical exchange saturation transfer (CEST), arterial spin labeling (ASL), and magnetization transfer contrast (MTC) methods generate different contrasts for MRI. However, they share many similarities in terms of pulse sequences and mechanistic principles. They all use RF pulse preparation schemes to label the longitudinal magnetization of certain proton pools and follow the delivery and transfer of this magnetic label to a water proton pool in a tissue region of interest, where it accumulates and can be detected using any imaging sequence. Due to the versatility of MRI, differences in spectral, spatial or motional selectivity of these schemes can be exploited to achieve pool specificity, such as for arterial water protons in ASL, protons on solute molecules in CEST, and protons on semi-solid cell structures in MTC. Timing of these sequences can be used to optimize for the rate of a particular delivery and/or exchange transfer process, for instance, between different tissue compartments (ASL) or between tissue molecules (CEST/MTC). In this review, magnetic labeling strategies for ASL and the corresponding CEST and MTC pulse sequences are compared, including continuous labeling, single-pulse labeling, and multi-pulse labeling. Insight into the similarities and differences among these techniques is important not only to comprehend the mechanisms and confounds of the contrasts they generate, but also to stimulate the development of new MRI techniques to improve these contrasts or to reduce their interference. This, in turn, should benefit many possible applications in the fields of physiological and molecular imaging and spectroscopy.

Improved calculation of the equilibrium magnetization of arterial blood in arterial spin labeling.

PURPOSE: To propose and assess an improved method for calculating the equilibrium magnetization of arterial blood ( M0a), used for calibration of perfusion estimates in arterial spin labeling. METHODS: Whereas standard M0a calculation is based on dividing a proton density-weighted image by an average brain-blood partition coefficient, the proposed method exploits partial-volume data to adjust this ratio. The nominator is redefined as the magnetization of perfused tissue, and the denominator is redefined as a weighted sum of tissue-specific partition coefficients. Perfusion data were acquired with a pseudo-continuous arterial spin labeling sequence, and partial-volume data were acquired using a rapid saturation recovery sequence with the same readout module. Results from 7 healthy volunteers were analyzed and compared with the conventional method. RESULTS: The proposed method produced improved M0a homogeneity throughout the brain in all subjects. The mean gray matter perfusion was significantly higher with the proposed method compared with the conventional method: 61.2 versus 56.3 mL/100 g/minute (+8.7%). Although to a lesser degree, the corresponding white matter values were also significantly different: 20.8 versus 22.0 mL/100 g/minute (-5.4%). The spatial and quantitative differences between the 2 methods were similar in all subjects. CONCLUSION: Compared with the conventional approach, the proposed method produced more homogenous M0a maps, corresponding to a more accurate calibration. The proposed method also yielded significantly different perfusion values across the whole brain, and performed consistently in all subjects. The new M0a method improves quantitative perfusion estimation with arterial spin labeling, and can therefore be of considerable value in perfusion imaging applications.

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.

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.

Visual Assessment of Brain Perfusion MRI Scans in Dementia: A Pilot Study.

PURPOSE: Functional imaging is becoming increasingly important for the detection of neurodegenerative disorders. Perfusion MRI with arterial spin labeling (ASL) has been reported to provide promising diagnostic possibilities but is not yet widely used in routine clinical work. The aim of this study was to compare, in a clinical setting, the visual assessment of subtracted ASL CBF maps with and without additional smoothing, to FDG-PET data. METHODS: Ten patients with a clinical diagnosis of dementia and 11 age-matched cognitively healthy controls were examined with pseudo-continuous ASL (pCASL) and 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET). Three diagnostic physicians visually assessed the pCASL maps after subtraction only, and after postprocessing using Gaussian smoothing and GLM-based beta estimate functions. The assessment scores were compared to FDG PET values. Furthermore, the ability to discriminate patients from healthy elderly controls was assessed. RESULTS: Smoothing improved the correlation between visually assessed regional ASL perfusion scores and the FDG PET SUV-r values from the corresponding regions. However, subtracted pCASL maps discriminated patients from healthy controls better than smoothed maps. Smoothing increased the number of false-positive patient identifications. Application of beta estimate functions had only a marginal effect. CONCLUSION: Spatial smoothing of ASL images increased false positive results in the discrimination of hypoperfusion conditions from healthy elderly. It also decreased interreader agreement. However, regional characterization and subjective perception of image quality was improved.

A novel approach to measure local cerebral haematocrit using MRI.

The percentage blood volume occupied by red blood cells is known as haematocrit. While it is straightforward to measure haematocrit in large arteries, it is very challenging to do it in microvasculature (cerebral haematocrit). Currently, this can only be done using invasive methods (e.g. PET), but their use is very limited. Local variations in cerebral haematocrit have been reported in various brain abnormalities (e.g. stroke, tumours). We propose a new approach to image cerebral haematocrit using MRI, which relies on combining data from two measurements: one that provideshaematocrit-weightedand other onehaematocrit-independentvalues of the same parameter, thus providing an easily obtainable measurement of this important physiological parameter. Four different implementations are described, with one illustrated as proof-of-concept using data from healthy subjects. Cerebral haematocrit measurements were found to be in general agreement with literature values from invasive techniques (e.g. cerebral/arterial ratios of 0.88 and 0.86 for sub-cortical and cortical regions), and showed good test-retest reproducibility (e.g. coefficient-of-variation: 15% and 13% for those regions). The method was also able to detect statistically significant haematocrit gender differences in cortical regions (p < 0.01). The proposed MRI technique should have important applications in various neurological diseases, such as in stroke and brain tumours.

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.

Idiopathic normal pressure hydrocephalus: cerebral perfusion measured with pCASL before and repeatedly after CSF removal.

Pseudo-continuous arterial spin labeling (pCASL) measurements were performed in 20 patients with idiopathic normal pressure hydrocephalus (iNPH) to investigate whether cerebral blood flow (CBF) increases during the first 24 hours after a cerebrospinal fluid tap test (CSF TT). Five pCASL magnetic resonance imaging (MRI) scans were performed. Two scans were performed before removal of 40 mL CSF, and the other three at 30 minutes, 4 hours, and 24 hours, respectively after the CSF TT. Thirteen different regions of interest (ROIs) were manually drawn on coregistered MR images. In patients with increased CBF in lateral and frontal white matter after the CSF TT, gait function improved more than it did in patients with decreased CBF in these regions. However, in the whole sample, there was no significant increase in CBF after CSF removal compared with baseline investigations. The repeatability of CBF measurements at baseline was high, with intraclass correlation coefficients of 0.60 to 0.90 for different ROIs, but the median regional variability was in the range of 5% to 17%. Our results indicate that CBF in white matter close to the lateral ventricles plays a role in the reversibility of symptoms after CSF removal in patients with iNPH.

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.

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.