Diffusion tensor imaging (DTI) is playing an increasingly important role in assisting clinical and biomedical investigators examine and identify white matter changes that may underly various brain disorders. To localize and quantify such changes, whole brain voxel-based analysis is typically performed, which requires a spatial normalization step that serves to place the shared anatomy of study subjects into spatial alignment. The normalization methods in currently available software for neuroimaging analysis are not optimized for the specialized tensorial nature of DTI data, and, consequently, do not take full advantage of the information encoded in these measurements for more accurate alignment of brain white matter tracts. DTI-TK is a multiplatform software toolkit that has been specifically developed to address this limitation. It consists of a suite of tools that implement image manipulation algorithms specific for DTI data, key among which is a state- of-the-art deformable image registration tool that optimizes full-tensor similarity metrics with explicit tensor reorientation in the transformation formulation. Together, the toolkit provides the most advanced, publicly available spatial normalization software specific for DTI data. DTI-TK has been demonstrated to improve the quality of spatial normalization and enhance the power of statistical inference in clinical studies. It is freely available online and supports a growing number of investigators from institutions across the country. The objective of this proposal is to make DTI-TK accessible to a much wider audience of neuroimaging researchers by making improvements to its interoperability, usability and documentation. Interoperability enhancements include comprehensive support for the NIfTI image format, with a special emphasis on correct interpretation of the transformations between image space and patient space encoded in NIfTI headers, and compatibility support for other popular DTI tools. Proposed usability enhancement includes the implementation of a MATLAB toolbox to support the integration of the DTI-TK spatial normalization routine within SPM5 workflows. Proposed improvements to documentation involve both systematic cataloging of detailed usage instructions for all of the tools and task-oriented tutorials for common usage scenarios that combine DTI-TK with other neuroimaging tools. Toward increasing its accessibility, DTI-TK will leverage the NIH Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) for dissemination. This effort will help expose many more users to the tool and create an environment in which users and developers can interact productively, leading to additional high- impact enhancements to interoperability and usability.
The proposed project aims to improve the interoperability, usability and documentation of DTI-TK, a software toolkit designed to support and improve the analysis of data acquired using diffusion tensor imaging (DTI), a novel magnetic resonance imaging modality that has opened the way to in vivo imaging studies of brain white matter in health and disease. Specifically, the toolkit will give researchers access to state-of-the-art DTI registration and normalization functionality, including the construction of population-specific templates, that will significantly enhance the sensitivity and specificity of group studies of white matter changes. This will multiply the effect of this project with each new user and have a wide influence on the quality and significance of scientific output.
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