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Abstract #3895

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

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

This study introduces a new quantitative mapping technique referred to as Four Quadrant mapping of Hybrid Multi-dimensional MRI data and evaluates its use for diagnosis of prostate cancer. Each image voxel can be represented as a vector in a 2D plot with components ‘∆T2/∆b’ and ‘∆ADC/∆TE’. Cancers contain a significantly higher percentage of voxels in quadrant 4 (PQ4), and a lower percentage of voxels in quadrant 2 (PQ2), smaller amplitude and angle compared to benign tissue. The quadrant analysis metrics resulted in AUC of 0.893 for differentiation of cancer from benign tissue, and showed moderate correlation with Gleason score (|ρ|=0.38-0.61).

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