Abstract #4462

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

Umberto Villani^1,2, Erica Silvestri^1,2, Marco Castellaro^1,2, Simona Schiavi³, Mariagiulia Anglani⁴, Silvia Facchini^1,5, Elena Monai^1,5, Domenico Davella^1,5, Alessandro Della Puppa⁶, Diego Cecchin⁷, Maurizio Corbetta^1,5,8, and Alessandra Bertoldo^1,2

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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