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Abstract #0529

Analysis of multiparametric microvascular MRI in tumor patients using a model-based cluster approach.

Julien Bouvier 1 , Nicolas Coquery 1 , Sylvie Grand 2 , Thomas Perret 1 , David Chechin 3 , Irene Tropres 1 , Alexandre Krainik 1 , and Emmanuel L Barbier 1

1 U836, INSERM, Grenoble, France, France, 2 Department of neuroradiology and MRI, CHU de Grenoble, France, France, 3 Philips Healthcare, Suresnes, France, France

In clinical monitoring of brain tumors, Perfusion Weighted Imaging (PWI) contributes to tumor grading and to assess the response to treatment. Beyond tumor perfusion, tumor hypoxia determines the response of various therapeutic approaches including radiotherapy. All these parameters may be mapped with MRI. However, the integration of several MRI maps is difficult. This wealth of information is however difficult to interpret. Moreover, there are tight physiological links between these parameters. It should thus be possible to define clusters of pixels with similar physiological characteristics. In this study, multiparametric MRI data collected on tumor patient were analyzed with a model-based cluster approach.

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