Test-retest reliability of brain morphology estimates.

Area of Science:

• Neuroimaging
• Brain Morphology Analysis
• Quantitative MRI

Background:

• Brain morphology metrics are vital for understanding inter-individual differences.
• Assessing the reliability of these structural measures is crucial for valid research.
• Previous studies highlight the need for robust neuroimaging analysis techniques.

Purpose of the Study:

• To evaluate the intersession reliability of cortical and subcortical brain morphology measures.
• To compare the reliability of different morphological metrics including thickness, gyrification, and fractal dimensionality.
• To identify imaging parameters that enhance the reliability of brain morphology assessments.

Main Methods:

• Utilized two open-access neuroimaging datasets.
• Assessed intersession reliability for cortical measures: thickness, gyrification, and fractal dimensionality.
• Evaluated intersession reliability for subcortical measures: volume and fractal dimensionality.

Main Results:

• Generally good intersession reliability was observed across the assessed brain morphology measures.
• Cortical gyrification and fractal dimensionality demonstrated particularly high reliability.
• One dataset, optimized for brain morphology analysis, exhibited exceptionally high reliability.

Conclusions:

• The reliability of brain morphology measures is generally adequate for research on inter-individual differences.
• Gyrification and fractal dimensionality are robust metrics for quantitative neuroimaging.
• Optimized imaging protocols can significantly improve the reliability of structural brain analyses.