ASAP (Automatic Software for ASL Processing): A toolbox for processing Arterial Spin Labeling images.

Area of Science:

• Neuroimaging
• Medical Imaging Analysis
• Biomedical Engineering

Background:

• Arterial Spin Labeling (ASL) is a non-invasive functional imaging technique for measuring cerebral blood flow.
• Current ASL data processing lacks standardized commercial software and normalization methods.
• Automated processing is crucial for reliable ASL data analysis and clinical application.

Purpose of the Study:

• To introduce Automated Software for ASL Processing (ASAP), a novel automated tool for ASL data.
• To provide a comprehensive solution for ASL image pre-processing, including quantification and normalization.
• To validate ASAP's utility in identifying hypoperfusion in individuals at risk for Alzheimer's disease.

Main Methods:

• ASAP integrates functions for quantification, skull-stripping, co-registration, partial volume correction, and spatial normalization.
• The software was evaluated using ASL datasets from healthy subjects at risk of Alzheimer's disease.
• ASAP requires minimal user input, enhancing reproducibility and reducing errors.

Main Results:

• ASAP successfully processed multiple ASL datasets, generating high-quality cerebral blood flow maps.
• The software demonstrated excellent spatial normalization capabilities.
• The study identified hypoperfusion in regions consistent with Alzheimer's disease progression, validating ASAP's performance.

Conclusions:

• ASAP offers an automated, user-friendly solution for ASL data processing and analysis.
• The software produces reliable cerebral blood flow maps suitable for statistical group analysis.
• ASAP facilitates the study of neurodegenerative diseases like Alzheimer's by enabling accurate non-invasive perfusion assessment.