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Abstract #0782

PET-MR multiparametric imaging biomarkers for differentiating between progression and radionecrosis of brain tumors

Nadya Pyatigorskaya1,2,3, Marc Bertaux4, Brian Sgard4, Lydia Yahia-cherif3, Marine Soret4, Marie-Odile Habert4, Didier Dormont1, Damien Galanaud1, and Aurelie Kas4

1Neuroradiology, Pitié Salpêtrière Hospital, APHP, Paris, France, 2UMR S 1127, CNRS UMR 7225, ICM, UPMC Univ Paris 06, Paris, France, 3Centre de NeuroImagerie de Recherche – CENIR, ICM, Paris, France, 4Nuclear Medecine, Pitié Salpêtrière Hospital, APHP, Paris, France

The aim of this work was evaluating the diagnostic accuracy of PET-MRI in difficult cases of differentiating between tumor progression and radionecrosis in neuro-oncology. For each lesion, PET (SUVmax, SUV mean, SUVpeak) and MRI (ADC, CBV, CBF, pCASL CBF) biomarkers were extracted. The combination of PET and MRI biomarkers allowed to improve the diagnostic accuracy. The logistic regression model has shown that 94% cases were correctly classified using the combination of SUVpeak and pCASL rCBF. Excellent diagnostic accuracy was achieved for both qualitative and quantitative evaluation by means of combined analysis of morphological, functional and metabolic imaging markers.

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