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Abstract #3933

Correlation Tensor Imaging Enhances Histological Differences Between Mouse Glioblastoma Subtypes

Rafael Neto Henriques1, Rui V Simões1,2, Sara Monteiro1,3, Andrada Ianuş1, Tânia Carvalho1, Sune Jespersen4,5, and Noam Shemesh1
1Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal, 2Institute for Research & Innovation in Health (i3S), University of Porto, Porto, Portugal, 3Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal, 4Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, 5Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

Synopsis

Keywords: Diffusion/other diffusion imaging techniques, Diffusion/other diffusion imaging techniquesCorrelation Tensor Imaging (CTI) has been recently proposed as a novel methodology for resolving kurtosis sources without relying on strong multi-gaussian component assumptions. Here, CTI is harnessed to decipher kurtosis sources in two different mouse glioblastoma subtypes. Our results reveal that CTI’s kurtosis source separation resolves the underlying microstructural differences between the glioblastoma subtypes and faithfully represents their specific histopathological features. In comparison to previous diffusion MRI approaches, CTI kurtosis maps present enhanced sensitivity towards tumor differences. These first results show the potential of CTI in providing more sensitive and specific future biomarkers for monitoring tumor progression and therapy outcome.

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