Abstract #2256
Tumor classification and prediction using robust multivariate clustering of multiparametric MRI
Alexis Arnaud 1,2 , Florence Forbes 1,2 , Nicolas Coquery 3,4 , Emmanuel L Barbier 3,4 , and Benjamin Lemasson 3,4
1
INRIA, Grenoble, -, France,
2
LJK,
University Grenoble Alpes, Grenoble, -, France,
3
U836,
INSERM, Grenoble, -, France,
4
GIN,
University Grenoble Alpes, Grenoble, -, France
Multiparametric MRI combined with multidimensional
advanced statistical analysis methods may allow a more
efficient brain tumor characterization. We used an
Expectation-Maximization algorithm and Bayesian model
selection on small animal data collected at 4.7T and
using four glioma models (n=37). We first detected and
excluded outlier animals (n=1). Then, we built a
dictionary of tumor signatures. This dictionary
discriminated four tumor models.
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