Quantification and discrimination of abnormal sulcal patterns in polymicrogyria

Area of Science:

• Neuroscience
• Developmental Biology
• Medical Imaging

Background:

• Polymicrogyria (PMG) is a cortical malformation often diagnosed qualitatively via imaging.
• Assessing PMG severity and extent has relied on subjective visual inspection.
• Understanding the relationship between PMG, brain structure, and clinical outcomes like language impairment requires objective measures.

Purpose of the Study:

• To develop and apply a quantitative sulcal graph-based analysis for describing abnormal sulcal patterns in polymicrogyria.
• To assess the extent of cortical involvement in PMG using this novel quantitative approach.
• To investigate the association between quantitative sulcal patterns and language development in individuals with PMG.

Main Methods:

• Constructed sulcal graphs from magnetic resonance imaging (MRI) data of 26 typical developing individuals and 18 PMG patients.
• Computed similarities between sulcal graphs using geometric and topological features.
• Compared similarity metrics between typical and PMG groups, and within the PMG cohort based on language status.

Main Results:

• Sulcal graph similarities were significantly lower in the PMG group compared to the typical developing group.
• Quantitative analysis identified more lobar regions as abnormal in PMG patients than suggested by visual inspection.
• In PMG patients, those with intact language showed sulcal patterns more similar to typical individuals, particularly in the left parietal lobe.

Conclusions:

• Sulcal graph analysis offers a quantitative method for assessing the severity and extent of polymicrogyria.
• This approach enhances understanding of polymicrogyria's global effects on cortical folding.
• Quantitative analysis provides insights into genotype-phenotype and clinical-imaging correlations in PMG.