This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The overall goal of the developmental neuro-informatics (DNI) core is to invent new and enhanced neuro-imaging analysis technologies that enable the investigation of structural and functional brain development in neonates. The non-invasive techniques developed by our group will be used to investigate brain maturation and its disruption in term newborn infants, premature infants, and infants with perinatal brain injury. Improving our understanding of the association between brain structure and behavioral consequences is of specific importance to the clinical environment of our group. Volumetric MRI and DTI are key modalities that can provide data to facilitate our understanding of structural brain maturation. Quantification of these structural data requires new post-acquisition image processing approaches. The objective of the proposed research is to develop algorithms that enable characterization of the spatial and temporal development of the structures of the brain of premature and term newborn infants. We will develop these algorithms by constructing statistical atlases from MRI scans of newborn infants grouped by post-menstrual age (PMA) and then quantifying the location, volume, and shape of these brain structures. The process of human brain development during the last trimester of pregnancy and the impact of perinatal brain injury upon the normal developmental course are poorly understood. Three-dimensional volumetric MRI and DTI-MRI offer the possibility of expanding the current knowledge base concerning the fundamental processes of brain development. Furthermore, MRI affords the opportunity to gain insight into local brain changes associated with perinatal brain injury. Following these infants over a period of clinical intervention will also permit quantitative monitoring and assessment of potential treatments or therapeutic trials upon which guidelines for clinical intervention can be developed. Ultimately, we expect this work to have a direct and significant impact on the treatment and management of large numbers of newborn infants. The local and international investigators proposing this research have worked together for several years and have pioneered the use of quantitative MRI to probe the structure of the neonate brain. Each of the collaborative sites is currently using quantitative image analysis algorithms and software developed by the NAC, underscoring not only the impact of our technology but also the effectiveness of our dissemination program. To date, our work in this area has focused on whole-brain tissue quantification. In the course of these activities, we have developed algorithms that can be extended or refined to permit regional quantification. Using whole-brain analysis techniques, for example, it has been determined that dexamethasone treatment in pre-term newborns can be correlated with an overall decrease in cerebrocortical gray matter. Regional quantification will help us determine the functional consequences of that reduction. The end product of our proposed research will be a fully automatic image-processing pipeline capable of processing MRI scans of multiple subjects. The output will include segmentation, parcellation, and DT-MRI analysis. This effort requires the development of new analysis tools that are stable, validated for the special implementation of neonate imaging, and accessible for clinical collaboration.
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