MRI-Based Spectral Analysis of Fetal Brain Gyrification: Applications to Lissencephaly and Polymicrogyria

Cortical gyrification is a key marker of fetal brain development and is typically assessed qualitatively on ultrasound or MRI. While previous quantitative approaches have characterized gestational trajectories in typically developing (TD) fetuses, only a few studies have investigated cortical malformations such as lissencephaly and polymicrogyria. Spectral analysis, which characterizes signals by their frequency content, has been successfully applied to study gyrification in neonates and adults but has not yet been explored prenatally. In this study, we introduce a spectral framework for quantifying fetal cortical folding from routine fetal MRI. Cerebral contours were extracted from coronal slices, transformed into polar coordinates, and analyzed using Fourier Transform to derive spectral profiles and five gyrification features: non-zero spectral density, entropy, mean frequency, variance, and skewness and the first twelve frequencies. Seventy-three TD fetuses and twenty-four with malformations of cortical development (14 polymicrogyria, 10 lissencephaly) were evaluated across gestation. Differences between TD, lissencephaly, or polymicrogyria fetuses were evaluated using linear mixed models and post-hoc t-tests with Benjamini–Hochberg correction. In TD fetuses, spectral features showed gestational-age–related trajectories, with increasing spectral density and variance and decreasing skewness, corresponding to the sequential folding waves. Fetuses with cortical malformations had lower spectral density and entropy ( p  ≤ 0.031), and reduction in most of the twelve frequencies, most prominently in frequencies associated with the Sylvian fissure development ( p  < 0.001). Spectral representation may capture both global and local aspects of cortical folding, offering a robust and quantitative biomarker of fetal brain maturation and deviations in cortical development.