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.

Effects of the Fasting-Postprandial State on Arterial Spin Labeling MRI-Based Cerebral Perfusion Quantification in Alzheimer's Disease.

BACKGROUND: The fasting-postprandial state remains an underrecognized confounding factor for quantifying cerebral blood flow (CBF) in the cognitive assessment and differential diagnosis of Alzheimer's disease (AD). PURPOSE: To investigate the effects of fasting-postprandial state on arterial spin labeling (ASL)-based CBF in AD patients. STUDY TYPE: Prospective. SUBJECTS: Ninety-two subjects (mean age = 62.5 ± 6.4 years; females 29.3%), including 30 with AD, 32 with mild cognitive impairment (MCI), and 30 healthy controls (HCs). Differential diagnostic models were developed with a 4:1 training to testing set ratio. FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted imaging using gradient echo and pseudocontinuous ASL imaging using turbo spin echo. ASSESSMENT: Two ASL scans were acquired to quantify fasting state and postprandial state regional CBFs based on an automated anatomical labeling atlas. Two-way ANOVA was used to assess the effects of fasting/postprandial state and disease state (AD, MCI, and HC) on regional CBF. Pearson's correlation analysis was conducted between regional CBF and cognitive scores (Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). The diagnostic performances of the fasting state, postprandial state, and mixed state (random mixing of the fasting and postprandial state CBF) in differential diagnosis of AD were conducted using support vector machine and logistic regression models. STATISTICAL TESTS: Two-way ANOVA, Pearson's correlation, and area under the curve (AUC) of diagnostic model were performed. P values <0.05 indicated statistical significance. RESULTS: Fasting-state CBF was correlated with cognitive scores in more brain regions (17 vs. 4 [MMSE] and 15 vs. 9 [MoCA]) and had higher absolute correlation coefficients than postprandial-state CBF. In the differential diagnosis of AD patients from MCI patients and HCs, fasting-state CBF outperformed mixed-state CBF, which itself outperformed postprandial-state CBF. DATA CONCLUSION: Compared with postprandial CBF, fasting-state CBF performed better in terms of cognitive score correlations and in differentiating AD patients from MCI patients and HCs. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology.

PURPOSE: Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease. METHODS: We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting. RESULTS: Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected. CONCLUSION: Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.

Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography.

PURPOSE: Dynamic angiography using arterial spin labeling (ASL) can provide detailed hemodynamic information. However, the long time-resolved readouts require small flip angles to preserve ASL signal for later timepoints, limiting SNR. By using time-encoded ASL to generate temporal information, the readout can be shortened. Here, the SNR improvements from using larger flip angles, made possible by the shorter readout, are quantitatively investigated. METHODS: The SNR of a conventional protocol with nine Look-Locker readouts and a 4 × $$ \times $$ 3 time-encoded protocol with three Look-Locker readouts (giving nine matched timepoints) were compared using simulations and in vivo data. Both protocols were compared using readouts with constant flip angles (CFAs) and variable flip angles (VFAs), where the VFA scheme was designed to produce a consistent ASL signal across readouts. Optimization of the background suppression to minimize physiological noise across readouts was also explored. RESULTS: The time-encoded protocol increased in vivo SNR by 103% and 96% when using CFAs or VFAs, respectively. Use of VFAs improved SNR compared with CFAs by 25% and 21% for the conventional and time-encoded protocols, respectively. The VFA scheme also removed signal discontinuities in the time-encoded data. Preliminary data suggest that optimizing the background suppression could improve in vivo SNR by a further 16%. CONCLUSIONS: Time encoding can be used to generate additional temporal information in ASL angiography. This enables the use of larger flip angles, which can double the SNR compared with a non-time-encoded protocol. The shortened time-encoded readout can also lead to improved background suppression, reducing physiological noise and further improving SNR.

Amide proton transfer imaging in stroke.

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods.

Validation of the estimation of the macrovascular contribution in multi-timepoint arterial spin labeling MRI using a 2-component kinetic model.

PURPOSE: In this paper, the ability to quantify cerebral blood flow by arterial spin labeling (ASL) was studied by investigating the separation of the macrovascular and tissue component using a 2-component model. Underlying assumptions of this model, especially the inclusion of dispersion in the analysis, were studied, as well as the temporal resolution of the ASL datasets. METHODS: Four different datasets were acquired: (1) 4D ASL angiography to characterize the macrovascular component and to study dispersion modeling within this component, (2) high temporal resolution ASL data to investigate the separation of the 2 components and the effect of dispersion modelling on this separation, (3) low temporal resolution ASL dataset to study the effect of the temporal resolution on the separation of the 2 components, and (4) low temporal resolution ASL data with vascular crushing. RESULTS: The model that included a gamma dispersion kernel had the best fit to the 4D ASL angiography. For the high temporal resolution ASL dataset, inclusion of the gamma dispersion kernel led to more signal included in the arterial blood volume map, which resulted in decreased cerebral blood flow values. The arterial blood volume and cerebral blood flow maps showed overall higher arterial blood volume values and lower cerebral blood flow values for the high temporal resolution dataset compared to the low temporal resolution dataset. CONCLUSION: Inclusion of a gamma dispersion kernel resulted in better fitting of the model to the data. The separation of the macrovascular and tissue component is affected by the inclusion of a gamma dispersion kernel and the temporal resolution of the ASL dataset.

Quantitative chemical exchange saturation transfer imaging of nuclear overhauser effects in acute ischemic stroke.

PURPOSE: In chemical exchange saturation transfer imaging, saturation effects between - 2 to - 5 ppm (nuclear Overhauser effects, NOEs) have been shown to exhibit contrast in preclinical stroke models. Our previous work on NOEs in human stroke used an analysis model that combined NOEs and semisolid MT; however their combination might feasibly have reduced sensitivity to changes in NOEs. The aim of this study was to explore the information a 4-pool Bloch-McConnell model provides about the NOE contribution in ischemic stroke, contrasting that with an intentionally approximate 3-pool model. METHODS: MRI data from 12 patients presenting with ischemic stroke were retrospectively analyzed, as well as from six animals induced with an ischemic lesion. Two Bloch-McConnell models (4 pools, and a 3-pool approximation) were compared for their ability to distinguish pathological tissue in acute stroke. The association of NOEs with pH was also explored, using pH phantoms that mimic the intracellular environment of naïve mouse brain. RESULTS: The 4-pool measure of NOEs exhibited a different association with tissue outcome compared to 3-pool approximation in the ischemic core and in tissue that underwent delayed infarction. In the ischemic core, the 4-pool measure was elevated in patient white matter ( 1.20±0.20 ) and in animals ( 1.27±0.20 ). In the naïve brain pH phantoms, significant positive correlation between the NOE and pH was observed. CONCLUSION: Associations of NOEs with tissue pathology were found using the 4-pool metric that were not observed using the 3-pool approximation. The 4-pool model more adequately captured in vivo changes in NOEs and revealed trends depending on tissue pathology in stroke.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors.

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Partial volume correction in arterial spin labeling perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far?

The mismatch in the spatial resolution of Arterial Spin Labeling (ASL) MRI perfusion images and the anatomy of functionally distinct tissues in the brain leads to a partial volume effect (PVE), which in turn confounds the estimation of perfusion into a specific tissue of interest such as gray or white matter. This confound occurs because the image voxels contain a mixture of tissues with disparate perfusion properties, leading to estimated perfusion values that reflect primarily the volume proportions of tissues in the voxel rather than the perfusion of any particular tissue of interest within that volume. It is already recognized that PVE influences studies of brain perfusion, and that its effect might be even more evident in studies where changes in perfusion are co-incident with alterations in brain structure, such as studies involving a comparison between an atrophic patient population vs control subjects, or studies comparing subjects over a wide range of ages. However, the application of PVE correction (PVEc) is currently limited and the employed methodologies remain inconsistent. In this article, we outline the influence of PVE in ASL measurements of perfusion, explain the main principles of PVEc, and provide a critique of the current state of the art for the use of such methods. Furthermore, we examine the current use of PVEc in perfusion studies and whether there is evidence to support its wider adoption. We conclude that there is sound theoretical motivation for the use of PVEc alongside conventional, 'uncorrected', images, and encourage such combined reporting. Methods for PVEc are now available within standard neuroimaging toolboxes, which makes our recommendation straightforward to implement. However, there is still more work to be done to establish the value of PVEc as well as the efficacy and robustness of existing PVEc methods.

Age-related normative changes in cerebral perfusion: Data from The Irish Longitudinal Study on Ageing (TILDA).

OBJECTIVE: To establish normative reference values for total grey matter cerebral blood flow (CBFGM) measured using pseudo-continuous arterial spin labelling (pCASL) MRI in a large cohort of community-dwelling adults aged 54 years and older. BACKGROUND: Quantitative assessment of CBFGM may provide an imaging biomarker for the early detection of those at risk of neurodegenerative diseases, such as Alzheimer's and dementia. However, the use of this method to differentiate normal age-related decline in CBFGM from pathological reduction has been hampered by the lack of reference values for cerebral perfusion. METHODS: The study cohort comprised a subset of wave 3 (2014-2015) participants from The Irish Longitudinal Study on Ageing (TILDA), a large-scale prospective cohort study of individuals aged 50 and over. Of 4309 participants attending for health centre assessment, 578 individuals returned for 3T multi-parametric MRI brain examinations. In total, CBFGM data acquired from 468 subjects using pCASL-MRI were included in this analysis. Normative values were estimated using Generalised Additive Models for Location Shape and Scale (GAMLSS) and are presented as percentiles, means and standard deviations. RESULTS: The mean age of the cohort was 68.2 ± 6.9 years and 51.7% were female. Mean CBFGM for the cohort was 36.5 ± 8.2 ml/100 g/min. CBFGM decreased by 0.2 ml/100 g/min for each year increase in age (95% CI = -0.3, -0.1; p ≤ 0.001) and was 3.1 ml/100 g/min higher in females (95% CI = 1.6, 4.5; p ≤ 0.001). CONCLUSIONS: This study is by far the largest single-site study focused on an elderly community-dwelling cohort to present normative reference values for CBFGM measured at 3T using pCASL-MRI. Significant age- and sex-related differences exist in CBFGM.

Examination of optimized protocols for pCASL: Sensitivity to macrovascular contamination, flow dispersion, and prolonged arterial transit time.

PURPOSE: Previously, multi- post-labeling delays (PLD) pseudo-continuous arterial spin labeling (pCASL) protocols have been optimized for the estimation accuracy of the cerebral blood flow (CBF) with/without the arterial transit time (ATT) under a standard kinetic model and a normal ATT range. This study aims to examine the estimation errors of these protocols under the effects of macrovascular contamination, flow dispersion, and prolonged arrival times, all of which might differ substantially in elderly or pathological groups. METHODS: Simulated data for four protocols with varying degrees of arterial blood volume (aBV), flow dispersion, and ATTs were fitted with different kinetic models, both with and without explicit correction for macrovascular signal contamination (MVC), to obtain CBF and ATT estimates. Sensitivity to MVC was defined and calculated when aBV > 0.5%. A previously acquired dataset was retrospectively analyzed to compare with simulation. RESULTS: All protocols showed underestimation of CBF and ATT in the prolonged ATT range. With MVC, the protocol optimized for CBF only (CBFopt) had the lowest sensitivity value to MVC, 33.47% and 60.21% error per 1% aBV in simulation and in vivo, respectively, among multi-PLD protocols. All multi-PLD protocols showed a significant decrease in estimation error when an extended kinetic model was used. Increasing flow dispersion at short ATTs caused increasing CBF and ATT overestimation in all protocols. CONCLUSION: CBFopt was the least sensitive protocol to prolonged ATT and MVC for CBF estimation while maintaining reasonably good performance in estimating ATT. Explicitly including a macrovascular component in the kinetic model was shown to be a feasible approach in controlling for MVC.

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, HybridT1-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 HybridT1-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.

ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies.

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Substrate and Stereochemical Control of Peptidoglycan Cross-Linking by Transpeptidation by Escherichia coli PBP1B.

Penicillin binding proteins (PBPs) catalyzing transpeptidation reactions that stabilize the peptidoglycan component of the bacterial cell wall are the targets of ß-lactams, the most clinically successful antibiotics to date. However, PBP-transpeptidation enzymology has evaded detailed analysis, because of the historical unavailability of kinetically competent assays with physiologically relevant substrates and the previously unappreciated contribution of protein cofactors to PBP activity. By re-engineering peptidoglycan synthesis, we have constructed a continuous spectrophotometric assay for transpeptidation of native or near native peptidoglycan precursors and fragments by Escherichia coli PBP1B, allowing us to (a) identify recognition elements of transpeptidase substrates, (b) reveal a novel mechanism of stereochemical editing within peptidoglycan transpeptidation, (c) assess the impact of peptidoglycan substrates on ß-lactam targeting of transpeptidation, and (d) demonstrate that both substrates have to be bound before transpeptidation occurs. The results allow characterization of high molecular weight PBPs as enzymes and not merely the targets of ß-lactam acylation.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer.

PURPOSE: Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low-concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements. METHODS: CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two-pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates. RESULTS: When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis. CONCLUSIONS: These results indicate that current practices of simultaneously fitting both CEST and MT effects in model-based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Calibration of arterial spin labeling data-potential pitfalls in post-processing.

PURPOSE: To assess the impact of the different post-processing options in the calibration of arterial spin labeling (ASL) data on perfusion quantification and its reproducibility. THEORY AND METHODS: Absolute quantification of perfusion measurements is one of the promises of ASL techniques. However, it is highly dependent on a calibration procedure that involves a complex processing pipeline for which no standardized procedure has been fully established. In this work, we systematically compare the main ASL calibration methods as well as various post-processing calibration options, using 2 data sets acquired with the most common sequences, pulsed ASL and pseudo-continuous ASL. RESULTS: Significant and sometimes large discrepancies in ASL perfusion quantification were obtained when using different post-processing calibration options. Nevertheless, when using a set of theoretically based and carefully chosen options, only small differences were observed for both reference tissue and voxelwise methods. The voxelwise and white matter reference tissue methods were less sensitive to post-processing options than the cerebrospinal fluid reference tissue method. However, white matter reference tissue calibration also produced poorer reproducibility results. Moreover, it may also not be an appropriate reference in case of white matter pathology. CONCLUSION: Poor post-processing calibration options can lead to large errors in perfusion quantification, and a complete description of the calibration procedure should therefore be reported in ASL studies. Overall, our results further support the voxelwise calibration method proposed by the ASL white paper, particularly given the advantage of being relatively simple to implement and intrinsically correcting for the coil sensitivity profile.

Quantification of cerebral perfusion and cerebrovascular reserve using Turbo-QUASAR arterial spin labeling MRI.

PURPOSE: To compare cerebral blood flow (CBF) and cerebrovascular reserve (CVR) quantification from Turbo-QUASAR (quantitative signal targeting with alternating radiofrequency labeling of arterial regions) arterial spin labeling (ASL) and single post-labeling delay pseudo-continuous ASL (PCASL). METHODS: A model-based method was developed to quantify CBF and arterial transit time (ATT) from Turbo-QUASAR, including a correction for magnetization transfer effects caused by the repeated labeling pulses. Simulations were performed to assess the accuracy of the model-based method. Data from an in vivo experiment conducted on a healthy cohort were retrospectively analyzed to compare the CBF and CVR (induced by acetazolamide) measurement from Turbo-QUASAR and PCASL on the basis of global and regional differences. The quality of the two ASL data sets was examined using the coefficient of variation (CoV). RESULTS: The model-based method for Turbo-QUASAR was accurate for CBF estimation (relative error was 8% for signal-to-noise ratio = 5) in simulations if the bolus duration was known. In the in vivo experiment, the mean global CVR estimated by Turbo-QUASAR and PCASL was between 63% and 64% and not significantly different. Although global CBF values of the two ASL techniques were not significantly different, regional CBF differences were found in deep gray matter in both pre- and postacetazolamide conditions. The CoV of Turbo-QUASAR data was significantly higher than PCASL. CONCLUSION: Both ASL techniques were effective for quantifying CBF and CVR, despite the regional differences observed. Although CBF estimated from Turbo-QUASAR demonstrated a higher variability than PCASL, Turbo-QUASAR offers the advantage of being able to measure and control for variation in ATT.

A mechanistic modelling approach for the determination of the mechanisms of inhibition by cyclosporine on the uptake and metabolism of atorvastatin in rat hepatocytes using a high throughput uptake method.

Determine the inhibition mechanism through which cyclosporine inhibits the uptake and metabolism of atorvastatin in fresh rat hepatocytes using mechanistic models applied to data generated using a high throughput oil spin method.Atorvastatin was incubated in fresh rat hepatocytes (0.05-150 nmol/ml) with or without 20 min pre-incubation with 10 nmol/ml cyclosporine and sampled over 0.25-60 min using a high throughput oil spin method. Micro-rate constant and macro-rate constant mechanistic models were ranked based on goodness of fit values.The best fitting model to the data was a micro-rate constant mechanistic model including non-competitive inhibition of uptake and competitive inhibition of metabolism by cyclosporine (Model 2). The association rate constant for atorvastatin was 150-fold greater than the dissociation rate constant and 10-fold greater than the translocation into the cell. The association and dissociation rate constants for cyclosporine were 7-fold smaller and 10-fold greater, respectively, than atorvastatin. The simulated atorvastatin-transporter-cyclosporine complex derived using the micro-rate constant parameter estimates increased in line with the incubation concentration of atorvastatin.The increased amount of data generated with the high throughput oil spin method, combined with a micro-rate constant mechanistic model helps to explain the inhibition of uptake by cyclosporine following pre-incubation.

Model-based Bayesian inference of brain oxygenation using quantitative BOLD.

Streamlined Quantitative BOLD (sqBOLD) is an MR technique that can non-invasively measure physiological parameters including Oxygen Extraction Fraction (OEF) and deoxygenated blood volume (DBV) in the brain. Current sqBOLD methodology rely on fitting a linear model to log-transformed data acquired using an Asymmetric Spin Echo (ASE) pulse sequence. In this paper, a non-linear model implemented in a Bayesian framework was used to fit physiological parameters to ASE data. This model makes use of the full range of available ASE data, and incorporates the signal contribution from venous blood, which was ignored in previous analyses. Simulated data are used to demonstrate the intrinsic difficulty in estimating OEF and DBV simultaneously, and the benefits of the proposed non-linear model are shown. In vivo data are used to show that this model improves parameter estimation when compared with literature values. The model and analysis framework can be extended in a number of ways, and can incorporate prior information from external sources, so it has the potential to further improve OEF estimation using sqBOLD.

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.