Three-dimensional brain fiber tracking modeling in diffusion tensor imaging

This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^

What Google Maps can do for Biomedical Data Dissemination: Examples and a Design Study

Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

Fiber Pathways for Language in the Developing Brain: A Diffusion Tensor Imaging (DTI) Study

The present study characterized two fiber pathways important for language, the superior longitudinal fasciculus/arcuate fasciculus (SLF/AF) and the frontal aslant tract (FAT), and related these tracts to speech, language, and literacy skill in children five to eight years old. We used Diffusion Tensor Imaging (DTI) to characterize the fiber pathways and administered several language assessments. The FAT was identified for the first time in children. Results showed no age-related change in integrity of the FAT, but did show age-related change in the left (but not right) SLF/AF. Moreover, only the integrity of the right FAT was related to phonology but not audiovisual speech perception, articulation, language, or literacy. Both the left and right SLF/AF related to language measures, specifically receptive and expressive language, and language content. These findings are important for understanding the neurobiology of language in the developing brain, and can be incorporated within contemporary dorsal-ventral-motor models for language.

Origin, transport and fate of organic matter in Florida Bay: A biomarker record of historical environmental changes

The Everglades are undergoing the world largest wetland restoration project with the aim of returning this system to hydrological conditions in place prior to anthropogenic modifications. Therefore, it is essential to know what these pristine conditions were. In this work, molecular marker (biomarker) distributions and carbon stable isotopic signatures in sediment samples were employed to assess historical environmental changes in Florida Bay over approximately the last 4000 years. Two biomarkers of terrestrial plants, particularly for mangroves (taraxerol and C29 n-alkane), combined with two seagrass proxies (the Paq and the C25/C 27 n-alkan-2-one ratio) revealed a sedimentary environmental shift from freshwater marshes to mangrove swamps and then to seagrass dominated marine ecosystems, likely as a result of sea-level rise in Florida Bay since the Holocene. The maximum values for the Paq and the C 25/C27 n-alkan-2-ones occurred during the 20th century, suggesting that the greatest abundance of seagrass cover is a recent rather than a historical, long-term phenomenon. The greater oscillation in frequency and amplitude for the biomarkers after 1900 potentially reflects an ecosystem under increasing anthropogenic stress. Several algal biomarkers such as C20 highly branched isoprenoids (HBIs), C 25 HBIs and dinosterol indicative of cyanobacteria, diatom and dinoflagellate organic matter inputs respectively, increased dramatically in the latter part of the 20th century and were attributed to recent anthropogenic changes in Florida Bay. ^ The highlight of this work is the development of HBIs as paleo-proxies. As biomarkers of diatoms, the C25 HBIs in the core from the central bay displayed the highest concentration at mid depth, reflecting strong historical inputs of diatom-derived sedimentary OM during that period. In fact, the depth profile of C25 HBIs coincided quite well with historical variations in diatom abundance and variations in diatom species composition in central Florida Bay based on the results of fossil diatom species analysis by microscopy. This study provides evidence that some C25 HBIs can be applied as biomarkers for certain diatom inputs in paleoenvironmental studies. The sources of C20 and C30 HBIs and their potential applicability as paleo-proxies were also investigated and their sources assessed based on their δ13C distributions. ^