Cerebral glucose metabolism on positron emission tomography of children

Establishing the normative range of age-dependent fluorodeoxyglucose (FDG) uptake in the developing brain is necessary for understanding regional quantitative analysis of positron emission tomography (PET) brain images in children and also to provide functional information on brain development. We analyzed head sections of FDG PET/computed tomography (CT) images for 115 patients (5 months to 23 years) without central nervous system disease before treatment, as PET studies are not performed on healthy children owing to ethical considerations and the risk of radiation exposure. We investigated the changes in FDG uptake and established age-associated normative ranges of cerebral FDG. Head sections of FDG PET/CT images were registered to a population-based probabilistic atlas of human cortical structures. Gray matter of 56 brain structures was defined on normalized PET images according to the atlas. To avoid individual and experimental confounding factors, the relative standardized uptake value (SUV) over the cerebellum of each structure was calculated. Relative SUVs were analyzed by ANOVA and modeled using generalized estimating equalization analysis with false discovery rate control. Age and structure were significant factors affecting SUVs. Anatomic proximity had little effect on FDG uptake. Linear and quadratic developmental trajectories were observed on absolute and relative SUVs, respectively. An increase from posterior-to-anterior and superior-to-inferior pattern was observed in both absolute SUV increase rate and relative SUV peak age. The SUV of each structure was modeled with respect to age, and these models can serve as baselines for the quantitative analysis of cerebral FDG-PET images of children

Neonatal atlas construction using sparse representation: Neonatal Atlas Construction

Atlas construction generally includes first an image registration step to normalize all images into a common space and then an atlas building step to fuse the information from all the aligned images. Although numerous atlas construction studies have been performed to improve the accuracy of the image registration step, unweighted or simply weighted average is often used in the atlas building step. In this article, we propose a novel patch-based sparse representation method for atlas construction after all images have been registered into the common space. By taking advantage of local sparse representation, more anatomical details can be recovered in the built atlas. To make the anatomical structures spatially smooth in the atlas, the anatomical feature constraints on group structure of representations and also the overlapping of neighboring patches are imposed to ensure the anatomical consistency between neighboring patches. The proposed method has been applied to 73 neonatal MR images with poor spatial resolution and low tissue contrast, for constructing a neonatal brain atlas with sharp anatomical details. Experimental results demonstrate that the proposed method can significantly enhance the quality of the constructed atlas by discovering more anatomical details especially in the highly convoluted cortical regions. The resulting atlas demonstrates superior performance of our atlas when applied to spatially normalizing three different neonatal datasets, compared with other start-of-the-art neonatal brain atlases

Deformable brain atlas validation of the location of subthalamic nucleus using T1-weighted MR images of patients operated on for Parkinson's

[EN] Parkinson¿s disease is a degenerative disease of the central nervous system. One of the most effective treatments is deep brain stimulation. This technique requires the localization of an objective structure: the subthalamic nucleus. Unfortunately this structure is difficult to locate. In this work the creation of a deformable brain atlas that enables the identification of the subthalamic nucleus in T1-weighted magnetic resonance imaging (MRI) in an automatic, precise and fast way is presented. The system has been validated using data from 10 patients (20 nucleus) operated on for Parkinson¿s. Our system offers better results using a Wendland function with an error of 1.8853 ± 0.9959 mm.Ortega Pérez, M.; Juan Lizandra, MC.; Alcañiz Raya, ML.; Gil Gómez, JA.; Monserrat Aranda, C. (2008). Deformable brain atlas validation of the location of subthalamic nucleus using T1-weighted MR images of patients operated on for Parkinson's. Computerized Medical Imaging and Graphics. 32(5):367-378. doi:10.1016/j.compmedimag.2008.02.003S36737832