Clinical connectomics: Mapping structural brain networks in disease

Area of Science:

• Neuroscience
• Medical Imaging
• Systems Biology

Background:

• The human connectome offers insights into brain disorders.
• Current connectome mapping methods are often validated on healthy subjects, limiting their clinical applicability.
• Brain pathologies introduce complexities in accurate connectome analysis.

Purpose of the Study:

• To address the challenges of structural connectome mapping in the presence of brain pathology.
• To establish best practices for reliable and biologically meaningful clinical connectome mapping.
• To guide applications in neurology, psychiatry, and neurosurgery.

Main Methods:

• Classification of connectome abnormalities and their relation to white-matter microstructure.
• Quantification of structural connectivity alterations using measures like streamline counts and microstructure-informed tractography.
• Evaluation of connectome-mapping pipelines and algorithmic choices for clinical settings.

Main Results:

• Structural connectivity measures can effectively quantify the impact of white-matter pathology on the macroscale connectome.
• Specific methods, including tract-averaged metrics and structural similarity, are discussed for pathological conditions.
• Consideration of algorithmic choices is crucial for reliable clinical connectome mapping.

Conclusions:

• Reliable structural connectome mapping in the presence of pathology is feasible with appropriate methodologies.
• Standardized approaches are needed to enhance the clinical utility of connectome analysis in neurological and psychiatric disorders.
• This work provides a framework for best practices in clinical connectome mapping.