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
U836, INSERM, Grenoble, France, France,
of neuroradiology and MRI, CHU de Grenoble, France,
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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