Abstract
Over the last several years, there has been significant advancement in the molecular characterization of intracranial diseases, particularly cerebral neoplasms. While nuclear medicine technology, including PET/CT, has been at the foreground of exploration, new MR imaging techniques, specifically diffusion-weighted and diffusion tensor imaging, have shown interesting applications towards advancing our understanding of cancer involving the brain. In this paper, we review the fundamentals and basic physics of these techniques, and their applications to patient care for both general diagnostic use and in answering specific questions in selection of patients in terms of expected response to treatment.
Highlights
Diffusion magnetic resonance imaging (MR) utilizes the Brownian motion of molecules to derive images
This article presents an overview of the current state of diffusion-weighted and diffusion tensor MR imaging of the brain in patients with cancer
Tumors such as lymphoma and primitive neuroectodermal tumor (PNET) demonstrate decreasing diffusion, adding valuable information to the radiologist when formulating a differential diagnosis of a cerebral mass lesion
Summary
Diffusion magnetic resonance imaging (MR) utilizes the Brownian motion of molecules to derive images. Movement caused by the random movements of water molecules has endlessly fascinated scientists, even Einstein, who in 1907 speculated that the speed of the particles subject to Brownian motion would be dependent only on temperature, and not on the size and nature of the particle or on its environment [2]. Einstein speculated that this prediction would be impossible to verify experimentally due to the technical challenges involved in taking measurements on extremely short time scales and microscopic spatial scales. A low value for ADC indicates that molecular movement in the sampled tissue is restricted (dark signal), International Journal of Molecular Imaging while a high value for ADC indicates that the tissue has free diffusion (bright signal)
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