Back to Search
Start Over
ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies
- Source :
- NeuroImage 219(2020), 117031
- Publication Year :
- 2019
- Publisher :
- Cold Spring Harbor Laboratory, 2019.
-
Abstract
- 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.
- Subjects :
- education.field_of_study
Data curation
Computer science
Population
Image processing
Mri studies
computer.software_genre
Pipeline (software)
3. Good health
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Cerebral blood flow
Arterial spin labeling
Data mining
education
Perfusion
computer
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- NeuroImage 219(2020), 117031
- Accession number :
- edsair.doi.dedup.....f926a8ed072e4209af8c761285145e27
- Full Text :
- https://doi.org/10.1101/845842