A cortical shape-adaptive approach to local gyrification index

Area of Science:

• Neuroscience
• Medical Imaging
• Computational Anatomy

Background:

• Cortical folding (gyrification) measurement is crucial for understanding brain development and function.
• Conventional methods using fixed kernels can blur local gyrification details by spanning unrelated cortical regions.

Purpose of the Study:

• To propose a novel, spatially varying kernel for accurate local quantification of cortical gyrification.
• To enhance the reproducibility and detail of gyrification measurements, particularly in developing brains.

Main Methods:

• Adapted wavefront propagation using anisotropic Hamilton-Jacobi partial differential equations to create adaptive kernel shapes.
• The kernel adaptively elongates along gyral crowns and sulcal fundi, maintaining uniformity over sulcal banks.
• Local gyrification measured using the proposed spatially varying kernel.

Main Results:

• The proposed kernel-based gyrification measure demonstrated higher reproducibility in multi-scan datasets compared to conventional methods.
• Analysis of early brain development revealed both positive and negative associations of gyrification with age, unlike conventional methods capturing only positive trends.
• The method produced sharper statistical maps linking cortical folding to sex and gestational age.

Conclusions:

• The novel adaptive kernel offers a more precise and reproducible method for quantifying local cortical gyrification.
• This approach provides a more nuanced understanding of gyrification changes during early brain development and its associations with demographic factors.