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 aim of this project is to assess the usefulness of diffusion tensor imaging (DTI) to diagnose brain tumors. While conventional MRI techniques have been playing crucial roles, there are several important questions that cannot be answered by them. These include information about the boundary of tumor and their properties of growth. For example, it is important to know whether a tumor is growing discretely or infiltrating into neighboring tissues and, if it is infiltrating, what is the orientation of the infiltration. As a preliminary study, the DTI was applied to two patients with astrocytoma. The tumors showed low diffusion anisotropy and high diffusion constant. Compared to conventional T2-weighted images, the images obtained from the DTI are not superior to identify and delineate the boundary of the tumors because the diffusion anisotropy of the tumors is similar to that of normal gray matter. On the other hand, the DTI could reveal detailed anatomy of nearby white matter tracts, which were deformed by growth of the tumor. The results clearly showed that the tumor in one of the patients was growing discretely inducing a large amount of anatomical deformation while the tumor in the other patient did not induce significant white matter deformation, indicating the infiltrating tumor. The orientation of the infiltration coincided with the trajectory of a major association tract, called superior longitudinal fasciculus. This preliminary study suggests that the DTI is a promising technique to precisely delineate deformed neuroanatomy of brain tumor patients. The information is expected to be used for surgical planning to avoid injuring critical white matter tracts and for treatment design by predicting the orientation of the tumor spreading. The result was published in Annals of Neurology (51, 377, 2002).
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