AUTOMATED SEGMENTATION AND SHAPE ANALYSIS IN PEDIATRIC BRAIN TUMOR SURVIVORS

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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. In the Division of Translational Imaging Research, a branch of St. Jude Children's Research Hospital Radiological Sciences department, we are currently focused on the characterization of therapy-induced brain damage, neurostructural organization and integrity, and neurocognitive performance in pediatric cancer survivors. Within this framework, several of our ongoing projects pursue the design of image processing algorithms that quantitatively analyze different structures of the patients developing brain. The central idea of our project is to develop an atlas-based automatic method in which manual delineations of healthy volunteers brain structures support the accurate segmentation of analog structures in our patients MR scans. These segmented structures are then processed to study shape changes attributable either to normal development, disease, or treatment, providing in this way a reference to test hypotheses that longitudinally correlate volumetric and local shape changes to the patients neurocognitive evaluations. Being a statistical approach that heavily relies on the manual segmentation of brain structures of a normal healthy population, our study would greatly benefit from the broadest base of normal 3-D MR scans, which would allow us to relate a particular patient to a set of normal individuals within an close age range, or properly classified in terms of sex, and/or laterality. Our highest expectation is that the methodology proposed in our study, provides valuable scientific criteria that can support treatment planning and ultimately be incorporated in our hospital's treatment protocols.