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. This study aimed to apply spectral analysis to routine fetal MRI to quantitatively assess cortical gyrification, characterize gestational age-related patterns in TD fetuses, and compare gyrification across TD, lissencephaly and polymicrogyria fetuses. Cerebral contours were extracted from coronal slices, transformed into polar coordinates, and analyzed using Fourier transform to derive spectral profiles including five gyrification features based on the overall spectral power: spectral density, entropy, mean frequency, variance, and skewness as well as the first twelve frequencies. Seventy-three TD fetuses and twenty-four with malformations of cortical development (10 lissencephaly, 14 polymicrogyria) 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 in most features and frequencies, corresponding to the sequential folding waves. Fetuses with cortical malformations had lower spectral density and entropy ( p ≤ 0.031), and reduced amplitudes across most of the twelve frequencies, most prominently in frequencies associated with the Sylvian fissure ( p < 0.001) compared with TD fetuses, with significant greater reductions in lissencephaly compared with polymicrogyria. Spectral representation may capture global cortical folding as well as distinct spectral patterns, offering a robust and quantitative biomarker of fetal brain maturation and deviations in cortical development.
Yehuda et al. (Fri,) studied this question.