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Computational Anatomy of Fetal Brain

Final Report Summary - FBRAIN (Computational Anatomy of Fetal Brain)

The purpose of the ERC Fbrain project is to provide new insights into fetal brain maturation and to model this very complex process by building fetal brain development atlases (an “atlas” is a computational way to summarize spatial and temporal anatomical information). The development of the human central nervous system begins in utero and continues until the end of adolescence. The cortex and subcortical grey matter undergo important modifications during fetal period.

Studies about brain maturation aim at providing a better understanding of brain development and links between brain changes and cognitive development. Such studies are of great interest for diagnosis help and clinical course of development and treatment of illnesses. However, working out the development of fetal brain remains an open issue.

The non-invasive nature of magnetic resonance imaging (MRI) provides unique opportunities for in vivo investigation of the developing human brain. MRI is a powerful technique widely used in adult brain studies focusing on brain morphometry and more specifically on the study of cortical thickness, myelination and white matter fibre formation. In the context of fetal brain analysis, MRI is a complementary method to routine ultrasound. Fetal MR imaging is a valuable complement to prenatal sonography to confirm and characterize suspected brain abnormalities.

This project deals with a fairly new research field called computational anatomy which aggregates several research domains such as statistics and computer science in order to obtain a relevant spatio-temporal representation of complex and variable brain structures. One major computational problem in brain mapping concerns the difficulty to compare one brain image with another, or incorporate them in a common reference space. In this research project, we rely on new image processing tools dedicated to computational anatomy issues by combining morphological information provided by T2-weighted MR images and diffusion information (water diffusion and fibre orientation) given by diffusion MR imaging (dMRI). The joint analysis of these anatomical features allows us to stress the generic maturation of normal fetal brain.

The use of mathematical models allows us the reconstruction of high-resolution 3D MR images in order to extract relevant features of brain maturation. Our approach relying on an interdisciplinary research framework have shown that it is now possible to estimate the entire connectome (estimate of a map of the neural connections) of the human fetal brain. This is a major breakthrough that can lead to new discoveries related to the human brain maturation, the way the brain is connected, how the connections evolve in time and the understanding of brain pathologies. In order to model the human brain maturation during the early stages of development, a first attempt has also been done to create a spatiotemporal model from a set of reconstructed MR images of fetal subjects with different gestational ages. Such neuro-informatics tools, that are now freely available for the entire research community, will help to characterize the neuro-anatomical differences between a reference group and the population or the person under investigation.