Abstract #4512

Multi slice MRSI-based generation of nosological images of therapy response using a semi-supervised source extraction approach in preclinical glioblastoma.

Nuria Arias-Ramos^1,2, Silvia Lope-Piedrafita^2,3, Victor Mocioiu^2,4, Margarida Julià-Sapé^1,2,4, Carles Arús^1,2,4, and Ana Paula Candiota^1,2,4

¹Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain, ²Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Cerdanyola del Vallès, Spain, ³Servei de Ressonància Magnètica Nuclear, Universitat Autònoma Barcelona, Cerdanyola del Vallès, Spain, ⁴Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain

Glioblastoma (GBM) is the most common aggressive primary brain tumour in adults and characterization of response to treatment turns out to be crucial for improving patient survival. In this work we obtained 3D-like information, from preclinical GBM under temozolomide (TMZ) treatment, with a multi-slice MRSI approach using source-based nosological images as response biomarker. A “Tumour Response Index” (TRI) was defined as the percentage of responding tumor pixels divided by the total tumour pixels. Heterogeneous response patterns with cyclical longitudinal variations were observed in several mice while responding pixels were mostly seen at the first 2 upper grids.

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