Based on our fetal cortical parcellation and labeling and regional analysis techinques, we perform sulcus- and vertex-wise cortical analysis. We also examine sulcal pit and pattern development using our sulcal graph matching and comparison technique. 

We used a statistical approach to quantitatively measure the timing of sulcal emergence and its variations. After automatic sulcal labeling, we binarized absence and presence of each sulcus and modeled the timing and variation of sulcal emergence using a logistic regression analysis.

We have published vertex-based regional sulcal depth analysis in fetuses with Down syndrome. Significant decreases in sulcal depth were found in bilateral Sylvian fissures and right central and parieto-occipital sulci. On the other hand, significantly increased sulcal depth was shown in the left superior temporal sulcus, which is related to atypical hemispheric asymmetry of cortical folding. Regional sulcal depth is a sensitive marker for detecting alterations of cortical development in DS during fetal life, which may be associated with later neurocognitive impairment (Yun et al., Cereb Cortex 2020).

Our graph-based sulcal pattern method has been applied to fetal brains and revealed early differences of sulcal pattern in fetuses with brain abnormalities. Each individual fetal brain was quantitatively compared with the normal template brains and the sulcal pattern similarities to the templates were measured. Significantly reduced sulcal pattern similarities were found in fetuses with brain malformations (polymicrogyria, Chiari II) compared to healthy fetuses. Some abnormal brains, initially misjudged to have normal sulcal folding in qualitative visual fetal MRI assessment (false- negative), was assessed to be abnormal in our quantitative analysis (true-positive) (Im et al., AJNR 2017). We examined another brain malformation, “isolated” agenesis of corpus callosum (ACC). Most of the ACC fetal brains were determined to have disorganized patterns of sulcal positions (Tarui et al., Cereb Cortex 2018). Our method is highly sensitive to alterations in early cortical development. 

The goal of this project is to examine sulcal patterns and regional cortical growth (thickness and surface area) to indicate the effects of genetic variants and altered cerebral hemodynamics in fetuses with congenital heart disease (CHD) using a large dataset of longitudinal MRIs. This study also aims to create the model that predicts postnatal preoperative brain abnormalities using deep learning techniques.

We recently revealed significantly lower sulcal pattern similarity to the normal templates in CHD compared to control fetuses. CHD sulcal pattern features appeared to be lower than the normal range in early fetal stage before the third trimester. It was of particular interest that sulcal patterns of the Sylvian fissure and early emerging sulci were significantly atypical in CHD fetuses (Ortinau et al., Cereb Cortex 2019).