Radiomics signature from multiparametric MRI as early in-vivo biomarkers for pseudoprogression in recurrent glioblastoma patients.
Lucie Piram1, Acquitter Clément2, Julia Gilhodes3, Umberto Sabatini4, Elizabeth Cohen-Jonathan Moyal1,5, Benjamin Lemasson2, and Soleakhena Ken5,6,7
1Department of Radiotherapy, Institut Universitaire du Cancer de Toulouse - Oncopole, Toulouse, France, 2Grenoble Institut des Neurosciences, Grenoble, France, 3Department of Clinical Trials, Institut Universitaire du Cancer de Toulouse - Oncopole, Toulouse, France, 4Dipartimento di Scienze Mediche e Chirurgiche, Università Magna Graecia, Catanzaro, Italy, 5U1037, RADOPT Team, Cancer Research Center of Toulouse, Toulouse, France, 6Department of Engineering and Medical Physics, Institut Universitaire du Cancer de Toulouse - Oncopole, Toulouse, France, 7MINDS Team UMR 5505, Institut de Recherche en Informatique de Toulouse, Toulouse, France
Radiomic features computed from multiparametric MRI were found to be relevant as early in-vivo biomarkers for pseudoprogression evaluation in recurrent glioblastoma patients. At baseline, predictive biomarker for pseudoprogression outcome was related to kurtosis parameter of FLAIR histogram plotted from abnormal hyper-intense signal area. When considering variation between baseline and first event (either pseudoprogression or true progression), four early biomarkers were found for entropy of T1-weighted, T1-weighted-post-contrast morphological MRI and Apparent Diffusion Coefficient maps derived from diffusion-weighted MRI.
Such early in-vivo biomarkers easily computed from automatic segmentation and first order radiomics analysis could be useful for the assessment of treatment response.
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