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Abstract #0725

Four Quadrant Vector Mapping of Hybrid Multidimensional MRI data for the diagnosis of prostate cancer

Aritrick Chatterjee1,2, Xiaobing Fan1, Aytekin Oto1, and Gregory Karczmar1
1University of Chicago, CHICAGO, IL, United States, 2Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, Chicago, IL, United States

Synopsis

Keywords: Prostate, CancerThis study introduces a new quantitative mapping technique referred to as “Four Quadrant Vector Mapping” of HM-MRI data, where each image voxel is represented as a vector within a 2D plot with components ‘∆T2/∆b’ and ‘∆ADC/∆TE’ with associated spatial coordinates and quadrant, distance and angle. Measured metrics provides effective cancer markers, with cancers associated with high PQ4, lower PQ2, and higher vector angle, and lower amplitude. Quadrant mapping parameters show promise for determining cancer aggressiveness as they are moderately correlated with Gleason score. Four quadrant mapping could be combined with the compartmental analysis of HM-MRI data to increase diagnostic accuracy.

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Keywords