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Abstract #3332

Advanced Prostate Cancer Characterization: Enhanced Tissue Compartment Estimation with Extended Grid Sampling and HM-MRI

Abel Lorente Campos1, Aritrick Chatterjee1, Gregory Karczmar1, Batuhan Gundogdu1, Xiaodong Guo1, Aytekin Oto1, Tatjana Antic2, and Milica Medved1
1Radiology, University of Chicago, Chicago, IL, United States, 2Pathology, University of Chicago, Chicago, IL, United States

Synopsis

Keywords: Prostate, Prostate

Motivation: Introduction of Extended Grid Sampling (EGS) to overcome the limitations of Hybrid Multidimensional MRI (HM-MRI) in prostate cancer (PCa) detection.

Goal(s): Our primary goal is to assess the effectiveness of EGS in improving the accuracy of PCa detection and lesion extension using HM-MRI.

Approach: Integrate EGS data with standard HM-MRI, utilizing biexponential fits for short and long T2 component estimation, followed by joint analysis, and risk map generation to enhance the precision of prostate cancer detection and characterization.

Results: EGS integrated with HM-MRI can provide more accurate delineation of prostate tissue compartments, notably improving the detection of prostate cancer lesions.

Impact: By enhancing prostate cancer (PCa) detection accuracy with Extended Grid Sampling (EGS) integrated into Hybrid Multidimensional MRI (HM-MRI), we empower clinicians to make more precise diagnoses and treatment decisions, directly benefiting patients.

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Keywords