Diffusion tensor imaging based network analysis detects alterations of neuroconnectivity in patients with clinically...

Area of Science:

• Neuroimaging
• Neurology
• Biomedical Engineering

Background:

• Conventional MRI (cMRI) has limitations in correlating with clinical findings, prognosis, and disease severity in multiple sclerosis (MS).
• Diffusion tensor imaging (DTI) with neuroconnectivity analysis shows promise for improved MS assessment.
• Early relapsing-remitting MS (RRMS) requires advanced imaging techniques for accurate evaluation.

Purpose of the Study:

• To pilot the use of DTI-based neuroconnectivity analysis for assessing early RRMS.
• To evaluate network communicability and average path length in RRMS patients compared to controls.
• To identify correlations between neuroconnectivity measures and clinical assessments.

Main Methods:

• Neuroconnectivity analysis was performed on 24 early RRMS patients and 30 healthy controls.
• Network communicability, measuring direct and indirect connections, was adopted to account for MS lesions.
• Brain network communicability and average path length were computed for anatomical areas.

Main Results:

• Statistically significant loss of communicability was observed in RRMS patients, particularly in frontal, hippocampal/parahippocampal, motor strip, and occipital regions.
• Correlations were found between communicability measures and the 25-foot Walk test in specific brain regions.
• Increased communicability was noted between deep gray matter structures and white matter tracts, suggesting compensatory changes.

Conclusions:

• DTI-based neuroconnectivity analysis demonstrates quantifiable, structurally relevant alterations in early RRMS.
• This method provides a promising approach for assessing disease severity and potentially predicting prognosis.
• Further longitudinal studies with larger cohorts are warranted to validate these findings.