Optimal design of pulsed arterial spin labeling MRI experiments

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications

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

Comparative Assessment of the Proteolytic Stability and Impact of Poly-Arginine Peptides R18 and R18D on Infarct Growth and Penumbral Tissue Preservation Following Middle Cerebral Artery Occlusion in the Sprague Dawley Rat

Poly-arginine peptides R18 and R18D have previously been demonstrated to be neuroprotective in ischaemic stroke models. Here we examined the proteolytic stability and efficacy of R18 and R18D in reducing infarct core growth and preserving the ischaemic penumbra following middle cerebral artery occlusion (MCAO) in the Sprague Dawley rat. R18 (300 or 1000 nmol/kg), R18D (300 nmol/kg) or saline were administered intravenously 10 min after MCAO induced using a filament. Serial perfusion and diffusion-weighted MRI imaging was performed to measure changes in the infarct core and penumbra from time points between 45- and 225-min post-occlusion. Repeated measures analyses of infarct growth and penumbral tissue size were evaluated using generalised linear mixed models (GLMMs). R18D (300 nmol/kg) was most effective in slowing infarct core growth (46.8 mm3 reduction; p < 0.001) and preserving penumbral tissue (21.6% increase; p < 0.001), followed by R18 at the 300 nmol/kg dose (core: 29.5 mm3 reduction; p < 0.001, penumbra: 12.5% increase; p < 0.001). R18 at the 1000 nmol/kg dose had a significant impact in slowing core growth (19.5 mm3 reduction; p = 0.026), but only a modest impact on penumbral preservation (6.9% increase; p = 0.062). The in vitro anti-excitotoxic neuroprotective efficacy of R18D was also demonstrated to be unaffected when preincubated for 1-3 h or overnight, in a cell lysate prepared from dying neurons or with the proteolytic enzyme, plasmin, whereas the neuroprotective efficacy of R18 was significantly reduced after a 2-h incubation. These findings highlight the capacity of poly-arginine peptides to reduce infarct growth and preserve the ischaemic penumbra, and confirm the superior efficacy and proteolytic stability of R18D, which indicates that this peptide is likely to retain its neuroprotective properties when co-administered with alteplase during thrombolysis for acute ischaemic stroke.

The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the single-compartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T_1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T_1t is fixed to a population average. This approach can cause CBF quantification errors, as T_1t can vary significantly inter- and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T_1t , the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T_1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T_1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T_1t value between population averages of T_1t and the longitudinal relaxation time of blood T_1b .

Designing and comparing optimized pseudo-continuous Arterial Spin Labeling protocols for measurement of cerebral blood flow

Arterial Spin Labeling (ASL) is a non-invasive, non-contrast, perfusion imaging technique which is inherently SNR limited. It is, therefore, important to carefully design scan protocols to ensure accurate measurements. Many pseudo-continuous ASL (PCASL) protocol designs have been proposed for measuring cerebral blood flow (CBF), but it has not yet been demonstrated which design offers the most accurate and repeatable CBF measurements. In this study, a wide range of literature PCASL protocols were first optimized for CBF accuracy and then compared using Monte Carlo simulations and in vivo experiments. The protocols included single-delay, sequential and time-encoded multi-timepoint protocols, and several novel protocol designs, which are hybrids of time-encoded and sequential multi-timepoint protocols. It was found that several multi-timepoint protocols produced more confident, accurate, and repeatable CBF estimates than the single-delay protocol, while also generating maps of arterial transit time. Of the literature protocols, the time-encoded protocol with T₁-adjusted label durations gave the most confident and accurate CBF estimates in vivo (16% and 40% better than single-delay), while the sequential multi-timepoint protocol was the most repeatable (20% more repeatable than single-delay). One of the novel hybrid protocols, Hybrid_T1-adj, was found to produce the most confident, accurate and repeatable CBF estimates out of all the protocols tested in both simulations and in vivo (24%, 47%, and 28% more confident, accurate, and repeatable than single-delay in vivo). The Hybrid_T1-adj protocol makes use of the best aspects of both time-encoded and sequential multi-timepoint protocols and should be a useful tool for accurately and efficiently measuring CBF.

Robust arterial transit time and cerebral blood flow estimation using combined acquisition of Hadamard-encoded multi-delay and long-labeled long-delay pseudo-continuous arterial spin labeling: a simulation and in vivo study

Arterial transit time (ATT) prolongation causes an error of cerebral blood flow (CBF) measurement during arterial spin labeling (ASL). To improve the accuracy of ATT and CBF in patients with prolonged ATT, we propose a robust ATT and CBF estimation method for clinical practice. The proposed method consists of a three-delay Hadamard-encoded pseudo-continuous ASL (H-pCASL) with an additional-encoding and single-delay with long-labeled long-delay (1dLLLD) acquisition. The additional-encoding allows for the reconstruction of a single-delay image with long-labeled short-delay (1dLLSD) in addition to the normal Hadamard sub-bolus images. Five different images (normal Hadamard 3 delay, 1dLLSD, 1dLLLD) were reconstructed to calculate ATT and CBF. A Monte Carlo simulation and an in vivo study were performed to access the accuracy of the proposed method in comparison to normal 7-delay (7d) H-pCASL with equally divided sub-bolus labeling duration (LD). The simulation showed that the accuracy of CBF is strongly affected by ATT. It was also demonstrated that underestimation of ATT and CBF by 7d H-pCASL was higher with longer ATT than with the proposed method. Consistent with the simulation, the 7d H-pCASL significantly underestimated the ATT compared to that of the proposed method. This underestimation was evident in the distal anterior cerebral artery (ACA; P = 0.0394) and the distal posterior cerebral artery (PCA; 2 P = 0.0255). Similar to the ATT, the CBF was underestimated with 7d H-pCASL in the distal ACA (P = 0.0099), distal middle cerebral artery (P = 0.0109), and distal PCA (P = 0.0319) compared to the proposed method. Improving the SNR of each delay image (even though the number of delays is small) is crucial for ATT estimation. This is opposed to acquiring many delays with short LD. The proposed method confers accurate ATT and CBF estimation within a practical acquisition time in a clinical setting.

Towards a 'resolution limit' for DW-MRI tumor microstructural models: A simulation study investigating the feasibility of distinguishing between microstructural changes

PURPOSE

To determine the feasibility of extracting sufficiently precise estimates of cell radius, R, and intracellular volume fraction, fi , from DW-MRI data in order to distinguish between specific microstructural changes tissue may undergo, specifically focusing on cell death in tumors.

METHODS

Simulations with optimized and non-optimized clinical acquisitions were performed for a range of microstructures, using a two-compartment model. The ability to distinguish between (i) cell shrinkage with cell density constant, mimicking apoptosis, and (ii) cell size constant with cell density decreasing, mimicking loss of cells, was evaluated based on the precision of simulated parameter estimates. Relationships between parameter precision, SNR, and the magnitude of specific parameter changes, were used to infer SNR requirements for detecting changes.

RESULTS

Accuracy and precision depended on microstructural properties, SNR, and the acquisition protocol. The main benefit of optimized acquisitions tended to be improved accuracy and precision of R, particularly for small cells. In most cases considered, higher SNR was required for detecting changes in R than for changes in fi .

CONCLUSIONS

Given the relative changes in R and fi due to apoptosis, simulations indicate that, for a range of microstructures, detecting changes in R require higher SNR than detecting changes in fi , and that such SNR is typically not achieved in clinical data. This suggests that if apoptotic cell size decreases are to be detected in clinical settings, improved SNR is required. Comparing measurement precision with the magnitude of expected biological changes should form part of the validation process for potential biomarkers.

Imaging brain microstructure with diffusion MRI: practicality and applications

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.

A general framework for optimizing arterial spin labeling MRI experiments

PURPOSE

Arterial spin labeling (ASL) MRI is a non-invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post-labeling delays (PLDs) of a multi-PLD pseudo-continuous ASL experiment and validating the improvement using simulations and in vivo data.

THEORY AND METHODS

A simple framework is proposed based on the use of the Cramér-Rao lower bound to find the protocol design which minimizes the predicted parameter estimation errors. Protocols were optimized for cerebral blood flow (CBF) accuracy or both CBF and arterial transit time (ATT) accuracy and compared to a conventional multi-PLD protocol, with evenly spaced PLDs, and a single-PLD protocol, using simulations and in vivo experiments in healthy volunteers.

RESULTS

Simulations and in vivo data agreed extremely well with the predicted performance of all protocols. For the in vivo experiments, optimizing for just CBF resulted in a 48% and 15% decrease in CBF errors, relative to the reference multi-PLD and single-PLD protocols, respectively. Optimizing for both CBF and ATT reduced CBF errors by 37%, without a reduction in ATT accuracy, relative to the reference multi-PLD protocol.

CONCLUSION

The presented framework can effectively design ASL experiments to minimize measurement errors based on the requirements of the scan.

Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramér-Rao Bound Meets Spin Dynamics

Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which simultaneously acquires multiple MR tissue parameter maps in a single experiment. In this paper, we present an estimation-theoretic framework to perform experiment design for MR fingerprinting. Specifically, we describe a discrete-time dynamic system to model spin dynamics, and derive an estimation-theoretic bound, i.e., the Cramér-Rao bound, to characterize the signal-to-noise ratio (SNR) efficiency of an MR fingerprinting experiment. We then formulate an optimal experiment design problem, which determines a sequence of acquisition parameters to encode MR tissue parameters with the maximal SNR efficiency, while respecting the physical constraints and other constraints from the image decoding/reconstruction process. We evaluate the performance of the proposed approach with numerical simulations, phantom experiments, and in vivo experiments. We demonstrate that the optimized experiments substantially reduce data acquisition time and/or improve parameter estimation. For example, the optimized experiments achieve about a factor of two improvement in the accuracy of T2 maps, while keeping similar or slightly better accuracy of T1 maps. Finally, as a remarkable observation, we find that the sequence of optimized acquisition parameters appears to be highly structured rather than randomly/pseudo-randomly varying as is prescribed in the conventional MR fingerprinting experiments.

Modification to the Rice-Vannucci perinatal hypoxic-ischaemic encephalopathy model in the P7 rat improves the reliability of cerebral infarct development after 48hours

BACKGROUND

The Rice-Vannucci model of hypoxic-ischaemic encephalopathy (HIE) has been associated with a high degree of variability with respect to the development of cerebral infarction and infarct lesion volume. For this reason, we examined the occurrence of communicational blood flow within the common carotid (CCA), internal (ICA), and external (ECA) carotid arteries following CCA occlusion as a source of variability in the model.

NEW METHOD

We propose a novel modification to the Rice-Vannucci model, whereby both the CCA and ECA are permanently ligated; mitigating communicational blood flow.

RESULTS

Using magnetic resonance angiography, phase-contrast velocity encoding, and pulsed arterial spin labelling, the modified Rice-Vannucci model (CCA/ECA occlusion) was demonstrated to mitigate communicational blood flow, whilst significantly reducing ipsilateral hemispherical cerebral blood flow (CBF). Comparatively, the original Rice-Vannucci model (CCA occlusion) demonstrated anterograde and retrograde blood flow within the ICA and CCA, respectively, with a non-significant reduction in ipsilateral CBF. Furthermore, CCA/ECA occlusion plus hypoxia (8% O₂/92% N₂; 2.5h) resulted in 100% of animals presenting with an infarct (vs 87%), significantly larger infarct volume at 48h (18.5% versus 10.0%; p<0.01), reduced standard deviation (±10% versus ±15%), and significantly worsened functional outcomes when compared to CCA occlusion plus hypoxia.

COMPARISON WITH EXISTING METHOD

We compared a modified Rice-Vannucci model (CCA/ECA occlusion±hypoxia) to the commonly used Rice-Vannucci model (CCA occlusion±hypoxia).

CONCLUSION

This study demonstrates that CCA/ECA occlusion in the Rice-Vannucci model of HIE reduces infarct volume variability by limiting communicational blood flow.

Investigation of the performance of variable-density Z-spectrum acquisition scheme in MR chemical exchange saturation transfer effect quantification

Chemical exchange saturation transfer (CEST) MRI emerges as a powerful imaging method to probe chemical exchange between bulk water and labile protons. Conventional CEST imaging needs detailed Z-spectrum acquisition, even at frequencies with limited information for CEST parameter quantification, which harms imaging efficiency and is not favorable in practical applications. In this study, a variable-density Z-spectrum acquisition scheme was proposed. Data with saturation frequencies close to water, labile protons and their negative frequency offset was densely sampled, while the remaining part was sparsely acquired. The accuracy of the proposed method in CEST ratio measurement was investigated with numerical simulation. Compared to the conventionally evenly distributed Z-spectrum acquisition method, the proposed scheme showed significant improvement of CEST ratio characterization with existence of noise and static magnetic field inhomogeneity. With the additional advantage of easy implementation, the developed Z-spectrum acquisition scheme provides a useful framework for accurate CEST parameter quantification without compromising the imaging time.

Optimization of arterial spin labeling MRI for quantitative tumor perfusion in a mouse xenograft model

Perfusion is an important biomarker of tissue function and has been associated with tumor pathophysiology such as angiogenesis and hypoxia. Arterial spin labeling (ASL) MRI allows noninvasive and quantitative imaging of perfusion; however, the application in mouse xenograft tumor models has been challenging due to the low sensitivity and high perfusion heterogeneity. In this study, flow-sensitive alternating inversion recovery (FAIR) ASL was optimized for a mouse xenograft tumor. To assess the sensitivity and reliability for measuring low perfusion, the lumbar muscle was used as a reference region. By optimizing the number of averages and inversion times, muscle perfusion as low as 32.4 ± 4.8 (mean ± standard deviation) ml/100 g/min could be measured in 20 min at 7 T with a quantification error of 14.4 ± 9.1%. Applying the optimized protocol, heterogeneous perfusion ranging from 49.5 to 211.2 ml/100 g/min in a renal carcinoma was observed. To understand the relationship with tumor pathology, global and regional tumor perfusion was compared with histological staining of blood vessels (CD34), hypoxia (CAIX) and apoptosis (TUNEL). No correlation was observed when the global tumor perfusion was compared with these pathological parameters. Regional analysis shows that areas of high perfusion had low microvessel density, which was due to larger vessel area compared with areas of low perfusion. Nonetheless, these were not correlated with hypoxia or apoptosis. The results suggest that tumor perfusion may reflect certain aspect of angiogenesis, but its relationship with other pathologies needs further investigation.

Rapid 3D dynamic arterial spin labeling with a sparse model-based image reconstruction

Dynamic arterial spin labeling (ASL) MRI measures the perfusion bolus at multiple observation times and yields accurate estimates of cerebral blood flow in the presence of variations in arterial transit time. ASL has intrinsically low signal-to-noise ratio (SNR) and is sensitive to motion, so that extensive signal averaging is typically required, leading to long scan times for dynamic ASL. The goal of this study was to develop an accelerated dynamic ASL method with improved SNR and robustness to motion using a model-based image reconstruction that exploits the inherent sparsity of dynamic ASL data. The first component of this method is a single-shot 3D turbo spin echo spiral pulse sequence accelerated using a combination of parallel imaging and compressed sensing. This pulse sequence was then incorporated into a dynamic pseudo continuous ASL acquisition acquired at multiple observation times, and the resulting images were jointly reconstructed enforcing a model of potential perfusion time courses. Performance of the technique was verified using a numerical phantom and it was validated on normal volunteers on a 3-Tesla scanner. In simulation, a spatial sparsity constraint improved SNR and reduced estimation errors. Combined with a model-based sparsity constraint, the proposed method further improved SNR, reduced estimation error and suppressed motion artifacts. Experimentally, the proposed method resulted in significant improvements, with scan times as short as 20s per time point. These results suggest that the model-based image reconstruction enables rapid dynamic ASL with improved accuracy and robustness.

Improving perfusion quantification in arterial spin labeling for delayed arrival times by using optimized acquisition schemes

OBJECTIVE

The improvement in Arterial Spin Labeling (ASL) perfusion quantification, especially for delayed bolus arrival times (BAT), with an acquisition redistribution scheme mitigating the T1 decay of the label in multi-TI ASL measurements is investigated. A multi inflow time (TI) 3D-GRASE sequence is presented which adapts the distribution of acquisitions accordingly, by keeping the scan time constant.

MATERIAL AND METHODS

The MR sequence increases the number of averages at long TIs and decreases their number at short TIs and thus compensating the T1 decay of the label. The improvement of perfusion quantification is evaluated in simulations as well as in-vivo in healthy volunteers and patients with prolonged BATs due to age or steno-occlusive disease.

RESULTS

The improvement in perfusion quantification depends on BAT. At healthy BATs the differences are small, but become larger for longer BATs typically found in certain diseases. The relative error of perfusion is improved up to 30% at BATs>1500ms in comparison to the standard acquisition scheme.

CONCLUSION

This adapted acquisition scheme improves the perfusion measurement in comparison to standard multi-TI ASL implementations. It provides relevant benefit in clinical conditions that cause prolonged BATs and is therefore of high clinical relevance for neuroimaging of steno-occlusive diseases.

Investigating white matter perfusion using optimal sampling strategy arterial spin labeling at 7 Tesla

PURPOSE

Cerebral blood flow (CBF) is an informative physiological marker for tissue health. Arterial spin labeling (ASL) is a noninvasive MRI method of measuring this parameter, but it has proven difficult to measure white matter (WM) CBF due to low intrinsic contrast-to-noise ratio compared with gray matter (GM). Here we combine ultra-high field and optimal sampling strategy (OSS) ASL to investigate WM CBF in reasonable scan times.

METHODS

A FAIR-based ASL sequence at 7T was combined with a real-time-feedback OSS technique, to iteratively improve post-label image acquisition times (TIs) on a tissue- and subject-specific basis to obtain WM CBF quantification.

RESULTS

It was found 77% of WM voxels gave a reasonable CBF fit. Averaged WM CBF for these voxels was found to be 16.3 ± 1.5 mL/100 g/min (discarding partial-volumed voxels). The generated TI schedule was also significantly different when altering the OSS weighted-tissue-mask, favoring longer TIs in WM.

CONCLUSION

WM CBF could be reasonably quantified in over 75% of identified voxels, from a total preparation and scan time of 15 min. OSS results suggest longer TIs should be used versus general GM ASL settings; this may become more important in WM disease studies.

Optimal sampling schedule for chemical exchange saturation transfer

The sampling schedule for chemical exchange saturation transfer imaging is normally uniformly distributed across the saturation frequency offsets. When this kind of evenly distributed sampling schedule is used to quantify the chemical exchange saturation transfer effect using model-based analysis, some of the collected data are minimally informative to the parameters of interest. For example, changes in labile proton exchange rate and concentration mainly affect the magnetization near the resonance frequency of the labile pool. In this study, an optimal sampling schedule was designed for a more accurate quantification of amine proton exchange rate and concentration, and water center frequency shift based on an algorithm previously applied to magnetization transfer and arterial spin labeling. The resulting optimal sampling schedule samples repeatedly around the resonance frequency of the amine pool and also near to the water resonance to maximize the information present within the data for quantitative model-based analysis. Simulation and experimental results on tissue-like phantoms showed that greater accuracy and precision (>30% and >46%, respectively, for some cases) were achieved in the parameters of interest when using optimal sampling schedule compared with evenly distributed sampling schedule. Hence, the proposed optimal sampling schedule could replace evenly distributed sampling schedule in chemical exchange saturation transfer imaging to improve the quantification of the chemical exchange saturation transfer effect and parameter estimation.

Pseudo-continuous arterial spin labelling MRI for non-invasive, whole-brain, serial quantification of cerebral blood flow following aneurysmal subarachnoid haemorrhage

Delayed cerebral ischaemia (DCI) is the major cause of mortality and morbidity following aneurysmal subarachnoid haemorrhage (SAH). Recent experimental evidence from animal models has highlighted the need for non-invasive and robust measurements of brain tissue perfusion in patients in order to help understand the pathophysiology underlying DCI. Quantitative, serial, whole-brain cerebral perfusion measurements were obtained with pseudo-continuous arterial spin labelling (PCASL) magnetic resonance imaging (MRI) in six SAH patients acutely following endovascular coiling. This technique requires no injected contrast or radioactive isotopes. MRI scanning was well tolerated. Artefact from endovascular coils was minimal. PCASL MRI was able to detect time-dependent and patient-specific changes in voxel-wise and regional cerebral blood flow. These changes reflected changes in clinical condition. Data obtained in healthy controls using the same experimental protocol confirm the reliability and reproducibility of these results. This is the first study to use whole-brain, quantitative PCASL to identify time-dependent changes in cerebral blood flow at the tissue level in the acute period following SAH. This technique has the potential to better understand changes in cerebral pathophysiology as a consequence of aneurysm rupture.

Combined arterial spin labeling and diffusion-weighted imaging for noninvasive estimation of capillary volume fraction and permeability-surface product in the human brain

A number of two-compartment models have been developed for the analysis of arterial spin labeling (ASL) data, from which both cerebral blood flow (CBF) and capillary permeability-surface product (PS) can be estimated. To derive values of PS, the volume fraction of the ASL signal arising from the intravascular space (v(bw)) must be known a priori. We examined the use of diffusion-weighted imaging (DWI) and subsequent analysis using the intravoxel incoherent motion model to determine v(bw) in the human brain. These data were then used in a two-compartment ASL model to estimate PS. Imaging was performed in 10 healthy adult subjects, and repeated in five subjects to test reproducibility. In gray matter (excluding large arteries), mean voxel-wise v(bw) was 2.3±0.2 mL blood/100 g tissue (all subjects mean±s.d.), and CBF and PS were 44±5 and 108±2 mL per 100 g per minute, respectively. After spatial smoothing using a 6-mm full width at half maximum Gaussian kernel, the coefficient of repeatability of CBF, v(bw) and PS were 8 mL per 100 g per minute, 0.4 mL blood/100 g tissue, and 13 mL per 100 g per minute, respectively. Our results show that the combined use of ASL and DWI can provide a new, noninvasive methodology for estimating v(bw) and PS directly, with reproducibility that is sufficient for clinical use.

Multicentre imaging measurements for oncology and in the brain

Multicentre imaging studies of brain tumours (and other tumour and brain studies) can enable a large group of patients to be studied, yet they present challenging technical problems. Differences between centres can be characterised, understood and minimised by use of phantoms (test objects) and normal control subjects. Normal white matter forms an excellent standard for some MRI parameters (e.g. diffusion or magnetisation transfer) because the normal biological range is low (<2-3%) and the measurements will reflect this, provided the acquisition sequence is controlled. MR phantoms have benefits and they are necessary for some parameters (e.g. tumour volume). Techniques for temperature monitoring and control are given. In a multicentre study or treatment trial, between-centre variation should be minimised. In a cross-sectional study, all groups should be represented at each centre and the effect of centre added as a covariate in the statistical analysis. In a serial study of disease progression or treatment effect, individual patients should receive all of their scans at the same centre; the power is then limited by the within-subject reproducibility. Sources of variation that are generic to any imaging method and analysis parameters include MR sequence mismatch, B(1) errors, CT effective tube potential, region of interest generation and segmentation procedure. Specific tissue parameters are analysed in detail to identify the major sources of variation and the most appropriate phantoms or normal studies. These include dynamic contrast-enhanced and dynamic susceptibility contrast gadolinium imaging, T(1), diffusion, magnetisation transfer, spectroscopy, tumour volume, arterial spin labelling and CT perfusion.

Detection of symptomatic vasospasm after subarachnoid haemorrhage: initial findings from single time-point and serial measurements with arterial spin labelling

OBJECTIVES

To detect symptomatic hemispheres during the postoperative course of subarachnoid haemorrhage (SAH) using arterial spin labelling (ASL).

METHODS

Eighteen patients with aneurysmal SAH were included; four exhibited symptomatic vasospasm postoperatively. All patients underwent ASL on days 9-10 (single time-point ASL). Nine patients underwent serial measurements of ASL (serial ASL) on days 1-2, 9-10 and 13-21, and seven patients also underwent imaging on days 4-7. CBF in the posterior part of the MCA territory was measured, and the ipsilateral/contralateral ratio of CBF was calculated. Differences between symptomatic hemispheres and others underwent ROC analysis.

RESULTS

Single time-point ASL revealed that CBF(day9-10) and CBF(i/c_day9-10) were significantly lower in symptomatic hemispheres than in asymptomatic hemispheres (P < 0.001). Serial ASL was significantly decreased on CBF(day4-7) compared with CBF(day1-2) and on CBF(day9-10) compared with CBF(day4-7), and significantly increased on CBF(day13-21) compared with CBF(day9-10). ROC analysis of single time-point ASL revealed that AUC for CBF(day9-10) was 0.95, significantly higher than CBF(i/c_day9-10) (P < 0.001). ROC analysis of serial ASL showed that AUC for CBF(day9-10) was 0.93 and significantly higher than CBF(day9-10/day1-2) and CBF(i/c_day9-10) (P < 0.001).

CONCLUSIONS

Single time-point ASL revealed significant CBF reduction in symptomatic hemispheres compared with asymptomatic hemispheres. Serial ASL showed time-dependent CBF changes after SAH.

KEY POINTS

• MR arterial spin labelling (ASL) can non-invasively assess cerebral blood flow (CBF) • ASL revealed significant CBF reduction in symptomatic hemispheres compared with asymptomatic hemispheres • Serial ASL measurements enable observation of time-dependent CBF changes after SAH • ASL is non- invasive and suitable for serial repeated examinations.

Application of a whole-body pharmacokinetic model for targeted radionuclide therapy to NM404 and FLT

We have previously developed a model that provides relative dosimetry estimates for targeted radionuclide therapy (TRT) agents. The whole-body and tumor pharmacokinetic (PK) parameters of this model can be noninvasively measured with molecular imaging, providing a means of comparing potential TRT agents. Parameter sensitivities and noise will affect the accuracy and precision of the estimated PK values and hence dosimetry estimates. The aim of this work is to apply a PK model for TRT to two agents with different magnitudes of clearance rates, NM404 and FLT, explore parameter sensitivity with respect to time and investigate the effect of noise on parameter precision and accuracy. Twenty-three tumor bearing mice were injected with a 'slow-clearing' agent, (124)I-NM404 (n = 10), or a 'fast-clearing' agent, (18)F-FLT (3'-deoxy-3'-fluorothymidine) (n = 13) and imaged via micro-PET/CT pseudo-dynamically or dynamically, respectively. Regions of interest were drawn within the heart and tumor to create time-concentration curves for blood pool and tumor. PK analysis was performed to estimate the mean and standard error of the central compartment efflux-to-influx ratio (k(12)/k(21)), central elimination rate constant (k(el)), and tumor influx-to-efflux ratio (k(34)/k(43)), as well as the mean and standard deviation of the dosimetry estimates. NM404 and FLT parameter estimation results were used to analyze model accuracy and parameter sensitivity. The accuracy of the experimental sampling schedule was compared to that of an optimal sampling schedule found using Cramer-Rao lower bounds theory. Accuracy was assessed using correlation coefficient, bias and standard error of the estimate normalized to the mean (SEE/mean). The PK parameter estimation of NM404 yielded a central clearance, k(el) (0.009 ± 0.003 h(-1)), normal body retention, k(12)/k(21) (0.69 ± 0.16), tumor retention, k(34)/k(43) (1.44 ± 0.46) and predicted dosimetry, D(tumor) (3.47 ± 1.24 Gy). The PK parameter estimation of FLT yielded a central elimination rate constant, k(el) (0.050 ± 0.025 min(-1)), normal body retention, k(12)/k(21) (2.21 ± 0.62) and tumor retention, k(34)/k(43) (0.65 ± 0.17), and predicted dosimetry, D(tumor) (0.61 ± 0.20 Gy). Compared to experimental sampling, optimal sampling decreases the dosimetry bias and SEE/mean for NM404; however, it increases bias and decreases SEE/mean for FLT. For both NM404 and FLT, central compartment efflux rate constant, k(12), and central compartment influx rate constant, k(21), possess mirroring sensitivities at relatively early time points. The instantaneous concentration in the blood, C(0), was most sensitive at early time points; central elimination, k(el), and tumor efflux, k(43), are most sensitive at later time points. A PK model for TRT was applied to both a slow-clearing, NM404, and a fast-clearing, FLT, agents in a xenograft murine model. NM404 possesses more favorable PK values according to the PK TRT model. The precise and accurate measurement of k(12), k(21), k(el), k(34) and k(43) will translate into improved and precise dosimetry estimations. This work will guide the future use of this PK model for assessing the relative effectiveness of potential TRT agents.

Quantitative measurement of cerebral physiology using respiratory-calibrated MRI

Functional magnetic resonance imaging typically measures signal increases arising from changes in the transverse relaxation rate over small regions of the brain and associates these with local changes in cerebral blood flow, blood volume and oxygen metabolism. Recent developments in pulse sequences and image analysis methods have improved the specificity of the measurements by focussing on changes in blood flow or changes in blood volume alone. However, FMRI is still unable to match the physiological information obtainable from positron emission tomography (PET), which is capable of quantitative measurements of blood flow and volume, and can indirectly measure resting metabolism. The disadvantages of PET are its cost, its availability, its poor spatial resolution and its use of ionising radiation. The MRI techniques introduced here address some of these limitations and provide physiological data comparable with PET measurements. We present an 18-minute MRI protocol that produces multi-slice whole-brain coverage and yields quantitative images of resting cerebral blood flow, cerebral blood volume, oxygen extraction fraction, CMRO(2), arterial arrival time and cerebrovascular reactivity of the human brain in the absence of any specific functional task. The technique uses a combined hyperoxia and hypercapnia paradigm with a modified arterial spin labelling sequence.

Measurement of absolute arterial cerebral blood volume in human brain without using a contrast agent

Arterial cerebral blood volume (CBV(a) ) is a vital indicator of tissue perfusion and vascular reactivity. We extended the recently developed inflow vascular-space-occupancy (iVASO) MRI technique, which uses spatially selective inversion to suppress the signal from blood flowing into a slice, with a control scan to measure absolute CBV(a) using cerebrospinal fluid (CSF) for signal normalization. Images were acquired at multiple blood nulling times to account for the heterogeneity of arterial transit times across the brain, from which both CBV(a) and arterial transit times were quantified. Arteriolar CBV(a) was determined separately by incorporating velocity-dependent bipolar crusher gradients. Gray matter (GM) CBV(a) values (n=11) were 2.04 ± 0.27 and 0.76 ± 0.17 ml blood/100 ml tissue without and with crusher gradients (b=1.8 s/mm(2) ), respectively. Arterial transit times were 671 ± 43 and 785 ± 69 ms, respectively. The arterial origin of the signal was validated by measuring its T(2) , which was within the arterial range. The proposed approach does not require exogenous contrast agent administration, and provides a non-invasive alternative to existing blood volume techniques for mapping absolute CBV(a) in studies of brain physiology and neurovascular diseases.

Optimal sampling and estimation in PASL perfusion imaging

Pulsed arterial spin labeling (PASL) techniques potentially allow the absolute, noninvasive quantification of brain perfusion using MRI. This can be achieved by fitting a kinetic model to the data acquired at a number of sampling times. However, the intrinsically low signal-to-noise ratio of PASL measurements usually requires substantial signal averaging, which may result in undesirably long scanning times. A judicious choice of the sampling points is, therefore, crucial in order to minimize scanning time, while optimizing estimation accuracy. On the other hand, a priori information regarding the model parameters may improve estimation performance. Here, we propose a Bayesian framework to determine an optimal sampling strategy and estimation method for the measurement of brain perfusion and arterial transit time (ATT). A Bayesian Fisher information criterion is used to determine the optimal sampling points and a MAP criterion is employed for the estimation of the model parameters, both taking into account the uncertainty in the model parameters as well as the amount of noise in the data. By Monte Carlo simulations, we show that using optimal compared to uniform sampling strategies, as well as the Bayesian estimator relative to a standard least squares approach, improves the accuracy of perfusion and ATT measurements. Moreover, we also demonstrate the applicability of the proposed approach to real data, with the advantage of reduced intersubject variability relative to conventional sampling and estimation approaches.

Arterial spin-labeling MRI can identify the presence and intensity of collateral perfusion in patients with moyamoya disease

BACKGROUND AND PURPOSE

Determining the presence and adequacy of collateral blood flow is important in cerebrovascular disease. Therefore, we explored whether a noninvasive imaging modality, arterial spin labeling (ASL) MRI, could be used to detect the presence and intensity of collateral flow using digital subtraction angiography (DSA) and stable xenon CT cerebral blood flow as gold standards for collaterals and cerebral blood flow, respectively.

METHODS

ASL and DSA were obtained within 4 days of each other in 18 patients with Moyamoya disease. Two neurointerventionalists scored DSA images using a collateral grading scale in regions of interest corresponding to ASPECTS methodology. Two neuroradiologists similarly scored ASL images based on the presence of arterial transit artifact. Agreement of ASL and DSA consensus scores was determined, including kappa statistics. In 15 patients, additional quantitative xenon CT cerebral blood flow measurements were performed and compared with collateral grades.

RESULTS

The agreement between ASL and DSA consensus readings was moderate to strong, with a weighted kappa value of 0.58 (95% confidence interval, 0.52-0.64), but there was better agreement between readers for ASL compared with DSA. Sensitivity and specificity for identifying collaterals with ASL were 0.83 (95% confidence interval, 0.77-0.88) and 0.82 (95% confidence interval, 0.76-0.87), respectively. Xenon CT cerebral blood flow increased with increasing DSA and ASL collateral grade (P<0.05).

CONCLUSIONS

ASL can noninvasively predict the presence and intensity of collateral flow in patients with Moyamoya disease using DSA as a gold standard. Further study of other cerebrovascular diseases, including acute ischemic stroke, is warranted.

Challenges for Non-Invasive Brain Perfusion Quantification Using Arterial Spin Labeling

Arterial Spin Labeling (ASL) sequences for perfusion Magnetic Resonance Imaging (MRI) have recently become available to be used in the clinical practice, offering a completely noninvasive technique for the quantitative evaluation of brain perfusion. Despite its great potential, ASL perfusion imaging still presents important methodological challenges before its incorporation in routine protocols. Specifically, in some pathological conditions in which the cerebrovascular dynamics is altered, the standard application of ASL may lead to measurement errors. In these cases, it would be possible to estimate perfusion, as well as arterial transit times, by collecting images at multiple time points and then fitting a mathematical model to the data. This approach can be optimized by selecting a set of optimal imaging time points and incorporating knowledge about the physiological distributions of the parameters into the model estimation procedures. In this study, we address the challenges that arise in the measurement of brain perfusion using PASL, due to variations in the arterial transit times, by estimating the errors produced using different types of acquisitions and proposing methods for minimizing such errors. We show by simulation that multiple inversion time ASL acquisitions are expected to reduce measurement errors relative to standard approaches. In data collected from a group of subjects, we further observed reduced inter-subject variability in perfusion measurements when using a multiple versus single inversion time acquisitions. Both measurement errors and variability were further reduced if optimized acquisition and analysis techniques were employed.

MR angiography and arterial spin labelling

MRI offers the ability to visualise and measure blood flow in the human body non-invasively. MR angiography (MRA) provides images of the arterial blood vessels within the body and allows measurement of blood velocities along these arteries. Arterial spin labelling (ASL) is a method for measuring the perfusion of blood into tissue (i.e. blood flow at the capillary level). This provides a key indicator of nutrient supply to the tissue. In this chapter, we have described the technical basis and practical implementation of these methods, emphasising their non-invasive (no contrast agents required) and quantitative nature.

Real-time adaptive sequential design for optimal acquisition of arterial spin labeling MRI data

An optimal sampling schedule strategy based on the Fisher information matrix and the D-optimality criterion has previously been proposed as a formal framework for optimizing inversion time scheduling for multi-inversion-time arterial spin labeling experiments. Optimal sampling schedule possesses the primary advantage of improving parameter estimation precision but requires a priori estimation of plausible parameter distributions that may not be available in all situations. An adaptive sequential design approach addresses this issue by incorporating the optimal sampling schedule strategy into an adaptive process that iteratively updates the parameter estimates and adjusts the optimal sampling schedule accordingly as data are acquired. In this study, the adaptive sequential design method was experimentally implemented with a real-time feedback scheme on a clinical MRI scanner and was tested in six normal volunteers. Adapted schedules were found to accommodate the intrinsically prolonged arterial transit times in the occipital lobe of the brain. Simulation of applying the adaptive sequential design approach on subjects with pathologically reduced perfusion was also implemented. Simulation results show that the adaptive sequential design approach is capable of incorporating pathologic parameter information into an optimal arterial spin labeling scheduling design within a clinically useful experimental time.

Arterial transit time effects in pulsed arterial spin labeling CBF mapping: insight from a PET and MR study in normal human subjects

Arterial transit time (ATT), a key parameter required to calculate absolute cerebral blood flow in arterial spin labeling (ASL), is subject to much uncertainty. In this study, ASL ATTs were estimated on a per-voxel basis using data measured by both ASL and positron emission tomography in the same subjects. The mean ATT increased by 260 +/- 20 (standard error of the mean) ms when the imaging slab shifted downwards by 54 mm, and increased from 630 +/- 30 to 1220 +/- 30 ms for the first slice, with an increase of 610 +/- 20 ms over a four-slice slab when the gap between the imaging and labeling slab increased from 20 to 74 mm. When the per-slice ATTs were employed in ASL cerebral blood flow quantification and the in-slice ATT variations ignored, regional cerebral blood flow could be significantly different from the positron emission tomography measures. ATT also decreased with focal activation by the same amount for both visual and motor tasks (approximately 80 ms). These results provide a quantitative relationship between ATT and the ASL imaging geometry and yield an assessment of the assumptions commonly used in ASL imaging. These findings should be considered in the interpretation of, and comparisons between, different ASL-based cerebral blood flow studies. The results also provide spatially specific ATT data that may aid in optimizing the ASL imaging parameters.

Bayesian optimization of perfusion and transit time estimation in PASL-MRI

Pulsed Arterial Spin Labeling (PASL) techniques potentially allow the absolute, non-invasive quantification of brain perfusion and arterial transit time. This can be achieved by fitting a kinetic model to the data acquired at a number of inversion time points (TI). The intrinsically low SNR of PASL data, together with the uncertainty in the model parameters, can hinder the estimation of the parameters of interest. Here, a two-compartment kinetic model is used to estimate perfusion and transit time, based on a Maximum a Posteriori (MAP) criterion. A priori information concerning the physiological variation of the multiple model parameters is used to guide the solution. Monte Carlo simulations are performed to compare the accuracy of our proposed Bayesian estimation method with a conventional Least Squares (LS) approach, using four different sets of TI points. Each set is obtained either with a uniform distribution or an optimal sampling strategy designed based on the same MAP criterion. We show that the estimation errors are minimized when our proposed Bayesian estimation method is employed in combination with an optimal set of sampling points. In conclusion, our results indicate that PASL perfusion and transit time measurements would benefit from a Bayesian approach for the optimization of both the sampling strategy and the estimation algorithm, whereby prior information on the parameters is used.

Arterial spin-label imaging in patients with normal bolus perfusion-weighted MR imaging findings: pilot identification of the borderzone sign

PURPOSE

To determine whether perfusion abnormalities are depicted on arterial spin-labeling (ASL) images obtained in patients with normal bolus perfusion-weighted (PW) magnetic resonance (MR) imaging findings.

MATERIALS AND METHODS

Institutional review board approval and written informed patient consent were obtained. This study was HIPAA compliant. Consecutive patients suspected or known to have cerebrovascular disease underwent 1.5-T brain MR imaging, including MR angiography, gradient-echo PW imaging, and pseudocontinuous ASL imaging, between October 2007 and January 2008. Patients with normal bolus PW imaging findings were retrospectively identified, and two neuroradiologists subsequently evaluated the ASL images for focal abnormalities. The severity of the borderzone sign-that is, bilateral ASL signal dropout with surrounding cortical areas of hyperintensity in the middle cerebral artery borderzone regions-was classified by using a four-point scale. For each group, the ASL-measured mean mixed cortical cerebral blood flow (CBF) at the level of the centrum semiovale was evaluated by using the Jonckheere-Terpstra test.

RESULTS

One hundred thirty-nine patients met the study inclusion criteria, and 41 (30%) of them had normal bolus PW imaging findings. Twenty-three (56%) of these 41 patients also had normal ASL imaging findings. The remaining 18 (44%) patients had the ASL borderzone sign; these patients were older (mean age, 71 years +/- 11 [standard deviation] vs 57 years +/- 16; P < .005) and had lower mean CBF (30 mL/100 g/min +/- 12 vs 46 mL/100 g/min +/- 12, P < .003) compared with the patients who had normal ASL imaging findings. Five patients had additional focal ASL findings that were related to either slow blood flow in a vascular structure or postsurgical perfusion defects and were not visible on the PW images.

CONCLUSION

Approximately half of the patients with normal bolus PW imaging findings had abnormal ASL findings-most commonly the borderzone sign. Results of this pilot study suggest that ASL imaging in patients who have this sign and are suspected of having cerebrovascular disease yields additional and complementary hemodynamic information.