Abstract #1369

Impact of semi-automatic delineation of hotspots of contrast enhancing region in predicting the outcome of GBM patients after brain surgery

Adrian Ion-Margineanu^1,2, Sofie Van Cauter^3,4, Diana M Sima^1,2, Frederik Maes^2,5, Stefan Sunaert³, Stefaan Van Gool⁶, Uwe Himmelreich⁷, and Sabine Van Huffel^1,2

¹ESAT - STADIUS, KU Leuven, Leuven, Belgium, ²Medical IT, iMinds, Leuven, Belgium, ³Department of Radiology, University Hospitals of Leuven, Leuven, Belgium, ⁴ZOL - Ziekenhuis Oost-Limburg, Genk, Belgium, ⁵ESAT - PSI, KU Leuven, Leuven, Belgium, ⁶Department of Pedriatic Neuro-Oncology, University Hospitals of Leuven, Leuven, Belgium, ⁷Department of Imaging and Pathology, Biomedical MRI / MoSAIC, Leuven, Belgium

Delineating contrast enhancing (CE) tissue is an integral part of the RANO criteria for therapy response assessment in high-grade gliomas. We propose a semi-automatic delineation of hotspots of CE (HCE) in brain tumour follow-up of 29 glioblastoma multiforme patients after surgery. Based on multi-parametric magnetic resonance data we predict the post-operative evolution of the brain tumour by labelling each patient at each time point as responsive or progressive. The results obtained with our semi-automatic method are better in most of the cases than the results obtained with the original manual delineations. Moreover, our method can efficiently impute missing data.

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