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Abstract #4168

3D Parametric Histogram Analysis of Extravascular Extracellular Space for Identifying Subpopulations of Glioblastoma Related to Survival

Ka-Loh Li1, Natale Quartuccio1, Xiaoping Zhu1, Samantha Mills, and Alan Jackson1

1Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, United Kingdom

Histogram Analysis of ve was used for quantification of heterogeneity in glioblastomas and to study whether heterogeneity is related to survival. 27 patients with GBM were imaged. ve histograms were processed by using a 4-mixture Gaussian distribution. Patients with short survival show an increasing proportion of the third Gaussian distribution. The mean of the 2nd Gaussian component, μ2, (p = 0.00015) and the weight of the 3rd components, w3 (p = 0.0066) were the most predictive for survival. The identification of tissue components, characterized by Gaussian fitting of ve values suggests that these represent, in some way, separate tissue subpopulations.

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