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Diffusion-weighted MRI: Techniques, applications and challenges in oncology


Hagberg,  G
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Hagberg, G. (2018). Diffusion-weighted MRI: Techniques, applications and challenges in oncology. Talk presented at 2nd European Congress of Medical Physics (ECMP 2018). Copenhagen, Denmark. 2018-08-23 - 2018-08-25.

Diffusion-Weighted MRI (DWI) is a powerful method that exploits Brownian motion of water molecules to explore tissue microstructure. It is made possible through the dependence of the MRI signal from diffusing spins on the direction and strength of applied magnetic field gradients. The signal loss increases with the apparent diffusion constant, and the direction dependency arises through the presence of barriers in the tissue that hinders or restricts the diffusion process. By repeating the measurement with several different gradient directions and strengths, anisotropic diffusion in tissue can be characterized. Several analysis methods, both model-free and based on biophysical diffusion models are available to characterize tissue microstructure, although most available protocols have been developed to characterize white matter fibers in the brain. There is an increasing interest to use DWI in oncology and its use is multi-faceted. For pre-surgical planning of brain tumor resections it can be used to identify essential white matter fibers that should be spared. However its use is not limited to the brain or to the characterization of surrounding tissue. Any soft matter tissue can greatly benefit from this technique, and especially a detailed characterization of tumor tissue can be achieved. For instance, the apparent diffusion coefficient can be helpful for identifying tumor borders, or even for classification and/or grading of tumors in e.g. the breast, prostate and liver. More advanced measures derived from DWI, like for instance kurtosis also hold great promise for the oncology-field. In future studies it will be essential to identify the best combination of efficient imaging protocols and analysis techniques that allow a full characterization at the microstructural level in order to achieve the specific goals for the tumor and organ in question.