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Abstract #4462

Precision and goodness of fit of diffusion-based microstructure models in brain tumours: an integrated information theory approach

Umberto Villani1,2, Erica Silvestri1,2, Marco Castellaro1,2, Simona Schiavi3, Mariagiulia Anglani4, Silvia Facchini1,5, Elena Monai1,5, Domenico Davella1,5, Alessandro Della Puppa6, Diego Cecchin7, Maurizio Corbetta1,5,8, and Alessandra Bertoldo1,2
1Padova Neuroscience Center, University of Padova, Padova, Italy, 2Department of Information Engineering, University of Padova, Padova, Italy, 3Department of Computer Science, University of Verona, Verona, Italy, 4Neuroradiology Unit, University of Padova, Padova, Italy, 5Department of Neuroscience, University of Padova, Padova, Italy, 6Departments of Neurosurgery, Neuroscience, Psychology, Pharmacology, and Child Health, University of Firenze, Firenze, Italy, 7Department of Medicine, Unit of Nuclear Medicine, University of Padova, Padova, Italy, 8Departments of Neurology, Radiology, Neuroscience, Washington University School of Medicine, St.Louis, MO, United States

Diffusion-based microstructure modeling techniques potentially provide significant biomarkers to characterize the tumoral architecture in the human brain. While clinical studies focus on the application of these technique, not enough care is being devoted to understand whether the employed models provide precise and reliable parameter estimates when fitted on the cancerous tissues. The present works tackles these issues on a cohorts of 11 patients diagnosed with different types of brain tumours by quantifying the variance of parameter estimates and the goodness-of-fit in an integrated view borrowing concepts from information theory.

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