Search bioRxiv⌕ Search

Biology subjects

Asllani, I.

Publications and source records attributed to Asllani, I..

2 recordsLinked to original sources

A Double Challenge: Cerebral Blood Flow During Concurrent Breath-Hold and Motor Task

Background/Hypothesis: Challenging the brain with simultaneous global and local demands may reveal functional constraints not apparent with either challenge alone. Here, we combine breath-holding with a motor task to investigate how a global vascular challenge modifies the local neurovascular response. Methods: Fourteen healthy adults underwent arterial spin labelling magnetic resonance imaging during three conditions: finger tapping with normal breathing, 25-second inspiratory breath-holding, and finger tapping during breath-holding. Cerebral blood flow responses were assessed using whole brain voxelwise analyses and motor regions of interest. Results: In the primary motor cortex, the increase in cerebral blood flow relative to baseline was approximately halved during the combined breath-holding and motor task challenge compared with motor task alone (26.5% vs 51.3%; p<0.001). Supplementary motor area responses were also smaller (23.2% vs 41.2%), but the difference was not statistically significant (p=0.092). Regional perfusion reductions were less extensive during the combined challenge than during breath-holding alone. These regional effects occurred without significant global grey- or white-matter perfusion changes from baseline. Conclusion/Interpretation: Combining global and local challenges revealed constraints on task-evoked perfusion increases not apparent during motor activation alone. This approach could help assess whether impaired cerebrovascular reserve compromises the brains capacity to meet local functional demands.

physiology↗

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.

neuroscience↗