ExploreASL

ExploreASL performs standardized processing and statistical analysis of arterial spin labeling (ASL) perfusion MRI data to quantify cerebral blood flow (CBF) and enable reproducible multi-center ASL studies.

Key Features:

• Standardized ASL processing and statistics: Provides end-to-end processing and statistical analysis tailored to ASL perfusion MRI for consistent CBF quantification.
• Scanner-specific processing techniques: Implements adjustments specific to different MRI scanners to reduce inter-scanner variability.
• Artifact reduction strategies: Incorporates methods to address artifacts inherent to different pulse sequences.
• Quantification of CBF: Performs cerebral blood flow quantification from ASL data.
• Modular architecture: Includes Import, Structural, ASL, and Population modules for data curation, structural processing and QC, ASL processing, and preparation for statistical analysis.
• MATLAB implementation with SPM: Implemented in MATLAB and leverages Statistical Parametric Mapping (SPM) for processing steps.
• Standards and provenance: Adheres to established recommendations concerning data structure, provenance, and best practices for analysis.
• Support for multiple pulse sequences: Validated processing applicable to various ASL pulse sequences.
• Large-scale validation: Tested on over 10,000 ASL scans from diverse clinical populations.
• Cross-operating-system compatibility: Ensures compatibility across various operating systems and MATLAB versions.

Scientific Applications:

• Multi-center harmonization: Enables pooling and harmonization of ASL data across cohorts and centers to increase statistical power.
• Cerebral perfusion studies: Supports quantification and comparison of CBF in clinical studies and trials.
• Group-level statistical analysis: Prepares data for single-subject and group-level statistical analyses to detect perfusion differences between cohorts.
• Clinical research cohorts: Applied to studies including perinatally HIV-infected children, healthy adult cohorts, and elderly individuals at risk for neurodegenerative disease.

Methodology:

Implemented in MATLAB using SPM, the workflow comprises Import (data curation), Structural (structural processing and quality control), ASL (ASL-specific processing, artifact reduction, and CBF quantification), and Population (preparation for single-subject and group statistical analysis), with scanner-specific processing adjustments.