Abstract

Magnetic resonance (MR) diffusion imaging is one of the more recent imaging techniques that have been added to the palette of routinely applied techniques for diagnostic MR imaging of the brain. This chapter discusses the added value of diffusion imaging in diagnostic imaging of brain tumors. First, the most basic and most commonly utilized approach to diffusion imaging is discussed. This approach provides images of tissue-specific, single diffusion coefficients that reflect the aggregate random motion of intra- and extracellular water. Such measurement of the water diffusion coefficient within the tumor permits an approximate categorization of tumor type and, for some tumor types, even definitive diagnosis. These tumor-specific diffusion coefficients are compared with diffusion coefficients of normal brain tissues, secondary changes, stroke, abscess, and fluid-filled cysts. Furthermore, it is discussed how serially obtained diffusion data are useful to document and even predict response to drug or radiation therapy within different areas of a tumor. Then, it is described how the monoparametric description of the MR diffusion signal with a single diffusion coefficient is incomplete and how additional diffusion parameters derived from the analysis of highly diffusion-weighted image data can contribute to the characterization of tumor tissue. Finally, it is reviewed how diffusion tensor imaging, which can measure the orientational dependence of restricted diffusion in white matter, can be gainfully applied to determine white matter integrity in brain tumor patients. Nerve fiber tract visualization based on diffusion tensor data promises to become indispensable for therapy planning and for intraoperative monitoring of surgical procedures. While diffusion imaging provides truly new and different information, it is plagued by low signal-to-noise ratio, coarse spatial resolution, and sometimes geometric deformation. More advanced applications are limited by extraordinarily long scan times.

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