Analysis of local gyrification index using a novel shape-adaptive kernel and the standard FreeSurfer spherical kernel : evidence from chronic schizophrenia outpatients

Schizophrenia can be considered a brain disconnectivity condition related to aberrant neurodevelopment that causes alterations in the brain structure, including gyrification of the cortex. Literature findings on cortical folding are incoherent: they report hypogyria in the frontal, superior-parietal and temporal cortices, but also frontal hypergyria. This discrepancy in local gyrification index (LGI) results could be due to the commonly used spherical kernel (Freesurfer), which is a method of analysis that is still not spatially precise enough. In this study we would like to test the spatial accuracy of a novel method based on a shape-adaptive kernel (Cmorph). The analysis of differences in gyrification between chronic schizophrenia outpatients (n = 30) and healthy controls (n = 30) was conducted with two methods: Freesurfer LGI and Cmorph LGI. Widespread differences in the LGI between schizophrenia outpatients and healthy controls were found using both methods. Freesurfer showed hypogyria in the superior temporal gyrus and the right temporal pole; it also showed hypergyria in the rostral-middle-frontal cortex in schizophrenia outpatients. In comparison, Cmorph revealed that hypergyria is equally represented as hypogyria in orbitofrontal and central brain regions. The clusters from Cmorph were smaller and distributed more broadly, covering all lobes of the brain. The presented evidence from disrupted cortical folding in schizophrenia indicates that the shape-adaptive kernel approach has a potential to improve the knowledge on the disrupted cortical folding in schizophrenia; therefore, it could be a valuable tool for further investigation on big sample size

Morphology And Mechanics Of Cortical Folding Associated With Auditory Deprivation

Hearing loss is increasingly becoming a common disabling condition that affects the global population. Functional and structural changes occur in the developing auditory cortex after the onset of auditory deprivation. This study aims at measuring and modeling these changes, which can help understand the pathology of hearing loss and support research on treatment. Specifically, it describes a pipeline of automatically extracting inner and outer cortical surfaces from MRI images and measuring morphological metrics. Then, a two-component finite element mechanical model mimicking gray matter and white matter is used to investigate the causes of measured structural differences between cats with normal hearing and hearing loss. Mechanical parameters, such as shear and bulk modulus, are varied with a view to studying their influence on cortical folding patterns. Compared to hearing cats, cats with hearing loss have decreased cortical curvature and folding index, and increased thickness. By varying the shear modulus and bulk modulus of the gray and white matter at different locations, the mechanical model reveals distinct stable folding patterns. Specific combinations of parameters and locations lead to changes in curvature, folding index, and thickness. The methods used in this study can also be extended to examine cortical morphological characteristics associated with other abnormalities in the developing brain

A cortical shape-adaptive approach to local gyrification index

The amount of cortical folding, or gyrification, is typically measured within local cortical regions covered by an equidistant geodesic or nearest neighborhood-ring kernel. However, without careful design, such a kernel can easily cover multiple sulcal and gyral regions that may not be functionally related. Furthermore, this can result in smoothing out details of cortical folding, which consequently blurs local gyrification measurements. In this paper, we propose a novel kernel shape to locally quantify cortical gyrification within sulcal and gyral regions. We adapt wavefront propagation to generate a spatially varying kernel shape that encodes cortical folding patterns: neighboring gyral crowns, sulcal fundi, and sulcal banks. For this purpose, we perform anisotropic wavefront propagation that runs fast along gyral crowns and sulcal fundi by solving a static Hamilton-Jacobi partial differential equation. The resulting kernel adaptively elongates along gyral crowns and sulcal fundi, while keeping a uniform shape over flat regions like sulcal banks. We then measure local gyrification within the proposed spatially varying kernel. The experimental results show that the proposed kernel-based gyrification measure achieves a higher reproducibility than the conventional method in a multi-scan dataset. We further apply the proposed kernel to a brain development study in the early postnatal phase from neonate to 2 years of age. In this study we find that our kernel yields both positive and negative associations of gyrification with age, whereas the conventional method only captures positive associations. In general, our method yields sharper and more detailed statistical maps that associate cortical folding with sex and gestational age. (C) 2018 Elsevier B.V. All rights reserved