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

PurposeTo 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).MethodsA 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).ResultsThe 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.ConclusionBoth 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

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

Variability of physiological brain perfusion in healthy subjects – A systematic review of modifiers. Considerations for multi-center ASL studies

Quantitative measurements of brain perfusion are influenced by perfusion-modifiers. Standardization of measurement conditions and correction for important modifiers is essential to improve accuracy and to facilitate the interpretation of perfusion-derived parameters. An extensive literature search was carried out for factors influencing quantitative measurements of perfusion in the human brain unrelated to medication use. A total of 58 perfusion modifiers were categorized into four groups. Several factors (e.g., caffeine, aging, and blood gases) were found to induce a considerable effect on brain perfusion that was consistent across different studies; for other factors, the modifying effect was found to be debatable, due to contradictory results or lack of evidence. Using the results of this review, we propose a standard operating procedure, based on practices already implemented in several research centers. Also, a theory of ‘deep MRI physiotyping’ is inferred from the combined knowledge of factors influencing brain perfusion as a strategy to reduce variance by taking both personal information and the presence or absence of perfusion modifiers into account. We hypothesize that this will allow to personalize the concept of normality, as well as to reach more rigorous and earlier diagnoses of brain disorders

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. The toolbox adheres to previously defined international standards 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 to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice

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

Haemodynamic MRI in sickle cell disease

Sickle cell disease (SCD) is an inherited form of anaemia, affecting oxygen transport throughout the body. One quarter of patients with SCD suffer ischaemic stroke before age 45. In children with SCD the risk of stroke can be detected and prevented, however, there is no method available for screening stroke risk in adult patients. The aim of the research presented in this thesis was to study imaging biomarkers that may aid in the identification of patients at risk for developing stroke. In one of the clinical observational cohort studies that we conducted, macrovascular haemodynamics were studied with MRI in the large vessels of the circle of Willis. The observed increase in vessel diameters led us to hypothesise that there is a maximum level of dilation that can be reached, also called the cerebrovascular reserve. In a subsequent clinical study we observed markedly reduced cerebrovascular reserve in adults with SCD, which led us to hypothesise that blood flow may be insufficient to maintain oxygen metabolism in the brain. Indeed, in a following study we observed that patients with SCD had reduced cerebral oxygen metabolism, despite adequate oxygen delivery, which was suggestive of cerebral shunting whereby blood travels directly from the arterial to the venous system without delivering oxygen to the tissue. Ultimately, the studies described in these thesis may help us better understand the physiology of SCD. Haemodynamic MRI has a potential clinical role in the assessment of treatment outcomes in future clinical trials for therapies in sickle cell patients

Effects of chronic fluoxetine treatment on neurogenesis and tryptophan hydroxylase expression in adolescent and adult rats

The antidepressant drug fluoxetine (Prozac) has been increasingly prescribed to children and adolescents with depressive disorders despite a lack of thorough understanding of its therapeutic effects in the paediatric population and of its putative neurodevelopmental effects. Within the framework of PRIOMEDCHILD ERA-NET, we investigated; a) effects of chronic fluoxetine treatment on adult hippocampal neurogenesis, a structural readout relevant for antidepressant action and hippocampal development; b) effects on tryptophan hydroxylase (TPH) expression, a measure of serotonin synthesis; c) whether treatment effects during adolescence differed from treatment at an adult age, and d) whether they were subregion-specific. Stereological quantification of the number of proliferating (Ki-67+) cells and of the number of young migratory neurons (doublecortin+), revealed a significant age-by-treatment interaction effect, indicating that fluoxetine affects both proliferation and neurogenesis in adolescent-treated rats differently than it does in adult-treated rats. In terms of subregional differences, fluoxetine enhanced proliferation mainly in the dorsal parts of the hippocampus, and neurogenesis in both the suprapyramidal and infrapyramidal blades of the dentate gyrus in adolescent-treated rats, while no such differences were seen in adult-treated rats. Fluoxetine exerted similar age-by-treatment interaction effects on TPH cells mainly in the ventral portion of the dorsal raphe nucleus. We conclude that fluoxetine exerts divergent effects on structural plasticity and serotonin synthesis in adolescent versus adult-treated rats. These preliminary data indicate a differential sensitivity of the adolescent brain to this drug and thus warrant further research into their behavioural and translational aspects. Together with recent related findings, they further call for caution in prescribing these drugs to the adolescent population