NEOCIVET: Towards accurate morphometry of neonatal gyrification and clinical applications in preterm newborns

Abstract

Cerebral cortical folding becomes dramatically more complex in the fetal brain during the 3rd trimester of gestation; the process continues in a similar fashion in children who are born prematurely. To quantify this morphological development, it is necessary to extract the interface between gray matter and white matter, which is particularly challenging due to changing tissue contrast during brain maturation. We employed the well-established CIVET pipeline to extract this cortical surface, with point correspondence across subjects, using a surface-based spherical registration. We then developed a variant of the pipeline, called NEOCIVET, that quantified cortical folding using mean curvature and sulcal depth while addressing the well-known problems of poor and temporally-varying gray/white contrast as well as motion artifact in neonatal MRI. NEOCIVET includes: i) a tissue classification technique that analyzed multi-atlas texture patches using the nonlocal mean estimator and subsequently applied a label fusion approach based on a joint probability between templates, ii) neonatal template construction based on age-specific sub-groups, and iii) masking of non-interesting structures using label-fusion approaches. These techniques replaced modules that might be suboptimal for regional analysis of poor-contrast neonatal cortex. The proposed segmentation method showed more accurate results in subjects with various ages and with various degrees of motion compared to state-of-the-art methods. In the analysis of 158 preterm-born neonates, many with multiple scans (n = 231; 26–40 weeks postmenstrual age at scan), NEOCIVET identified increases in cortical folding over time in numerous cortical regions (mean curvature:+0.003/week; sulcal depth:+0.04 mm/week) while folding did not change in major sulci that are known to develop early (corrected p < 0.05). The proposed pipeline successfully mapped cortical structural development, supporting current models of cerebral morphogenesis, and furthermore, revealed impairment of cortical folding in extremely preterm newborns relative to relatively late preterm newborns, demonstrating its potential to provide biomarkers of prematurity-related developmental outcome.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

“…This includes the development of specialised tools for tissue segmentation that address the difficulties in resolving tissue boundaries blurred through the presence of low resolution and partial volume. A variety of techniques have been proposed for tissue segmentation of the neonatal brain in recent years: unsupervised techniques (Gui et al, 2012), atlas fusion techniques (Weisenfeld and Warfield, 2009;Gousias et al, 2013;Kim et al, 2016), parametric techniques (Prastawa et al, 2005;Song et al, 2007;Xue et al, 2007;Shi et al, 2010;Cardoso et al, 2013;Makropoulos et al, 2012;Wang et al, 2012;Wu and Avants, 2012;Beare et al, 2016;Liu et al, 2016), classification techniques (Anbeek et al, 2008;Srhoj-Egekher et al, 2012;Chiţȃ et al, 2013;Wang et al, 2015;Sanroma et al, 2016;Moeskops et al, 2016) and deformable models (Wang et al, 2011;Dai et al, 2013;Wang et al, 2013Wang et al, , 2014. A review of neonatal segmentation methods can be found in Devi et al (2015); Makropoulos et al (2017).…”

“…Once segmentations are extracted, surface mesh modelling approaches are, to an extent, agnostic of the origin of the data; allowing, in principle, the application of a wide variety of cortical mesh modelling approaches to neonatal data, including those provided within the FreeSurfer (Dale et al, 1999;Fischl, 2012), BrainSuite (Shattuck and Leahy, 2002), BrainVISA (Rivière et al, 2009), andCIVET (MacDonald et al, 2000;Kim et al, 2005Kim et al, , 2016 packages. In general, these methods fit surfaces to boundaries of tissue segmentation masks, which, allowing for some need for topological correction, relies on the accuracy of the segmentation.…”

Studying neuroanatomy using MRI

“…T1 and T2) throughout the first 24 months of life. Image processing algorithms thus have to adapt to these changing contrasts 173 . Lastly, preterm and very preterm born subjects are also providing new insights into early brain development without the constraints of in-utero acquisitions 174 .…”

A computational method for longitudinal mapping of orientation-specific expansion of cortical surface in infants

“…The cerebral cortex of the human brain is a highly convoluted, sheet-like structure of gray matter, with the cortical folds formed during late gestation (Chi et al, 1977; Dubois et al, 2007; Habas et al, 2011; Kim et al, 2016; Zilles et al, 2013). At term birth, although all primary and secondary cortical folds, as well as many tertiary cortical folds, are well established, both brain volume and cortical surface area are only one-third of those of adults (Dubois et al, 2007; Hill et al, 2010; Li et al, 2014a).…”