Automatic Measurement of Extra-Axial CSF from Infant MRI Data

Area of Science:

• Neuroimaging
• Developmental Neuroscience
• Computational Biology

Background:

• Cerebrospinal fluid (CSF) quantification is vital for understanding early brain development.
• Extra-axial CSF (EA-CSF) shows potential as a biomarker for neurodevelopmental disorders, including Autism Spectrum Disorder (ASD).
• Current neuroimaging software lacks support for non-ventricular CSF quantification, particularly EA-CSF, hindering research.

Purpose of the Study:

• To develop a user-friendly, open-source software tool for automatic quantification of extra-axial CSF volume.
• To overcome the limitations of existing neuroimaging software in measuring EA-CSF.
• To facilitate wider research into the role of EA-CSF in brain development.

Main Methods:

• Development of a novel, open-source, cross-platform software tool named Auto-EACSF.
• Implementation of a user-friendly graphical user interface (GUI) for automated EA-CSF computation.
• Utilized a previously established quantitative protocol adapted into a pipeline workflow.

Main Results:

• Successful development of the Auto-EACSF software tool.
• Auto-EACSF provides automatic and user-friendly computation of extra-axial CSF volume.
• The tool is designed for broad applicability across diverse neuroimaging studies and research labs.

Conclusions:

• Auto-EACSF addresses the need for accessible EA-CSF quantification in neuroimaging research.
• This tool will enable broader investigation of EA-CSF's role in both typical and atypical brain development.
• Facilitating EA-CSF measurement can advance early detection and understanding of neurodevelopmental disorders.