PROJECT SUMMARY/ABSTRACT In the fetal brain, cortical plate (CP) thickness is thought to be related to the number and size of cells within a column, packing density, intracortical myelin, and synapses, and subplate (SP) thickness associated with the number of thalamic and cortical afferents and the amount of cortico-cortical connections. Estimation of cortical thickness postnatally with MRI has contributed greatly to our understanding of human brain development and cognitive function and disease onset and progression in various brain disorders. However, our knowledge and research of human in utero CP and SP thickness remains limited due to the lack of available techniques that automatically measure regional CP and SP thickness from fetal brain MRI. Compared to child or adult brains, fetal brains are much smaller in size and have different image contrast. Fetal brain MRI shows lower effective resolution and suffers from head motion which causes artifacts. Thus, it is challenging to extract accurate CP and SP regions and define geometrically appropriate thickness between the CP and SP surfaces. This study will develop a fully automatic pipeline to extract regional CP and SP thickness using multi-site fetal MRI datasets. We will develop the method for CP and SP segmentation with the identification of sulcal cerebrospinal fluid regions using deep convolutional neural networks. Based on the accurate segmentation, a deformable model method that is optimized and specialized for fetal brains will be developed to extract the CP and SP surfaces. CP and SP thickness will be measured based on vertex-wise correspondence between all CP and SP surfaces. We will perform reliability and sensitivity tests using different imaging subsets within the same subject and artificial data created by moving the CP and SP boundary. We will then define the growth rate of CP and SP thickness in all cortical regions in typically developing (TD) fetuses from 18 to 37 gestational weeks (GW). We hypothesize that the growth rate of CP and SP thickness, the maximum SP thickness, and/or the maximum growth GW of CP thickness will be variable across different cortical areas in TD fetuses. The growth of CP and SP thickness in fetuses with cerebral abnormalities (polymicrogyria and agenesis of corpus callosum) will be statistically compared to the growth of TD fetuses. Malformations of cortical development and cortico-cortical connections may result in altered growth of CP and SP thickness in fetuses with polymicrogyria and agenesis of corpus callosum. This study will lay the foundation for a novel biomarker that can lead to greater insight into the mechanisms of normal and altered in utero brain development. Our methods developed from the proposed study will be publicly distributed using a web-based neuroimage computation platform, which will enable more clinical applications of fetal CP and SP thickness analysis.