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Abstract #2574

Comparison of Radiomics and Quantitative ADC Measurements of Prostate PI-RADS v2 Lesions to Prospective Radiologist Performance

David Bonekamp1, Simon Kohl1, Manuel Wiesenfarth1, Patrick Schelb1, Jan-Philipp Radtke2, Michael Götz1, Philipp Kickingereder2, Kaneschka Yaqubi1, Bertram Hitthaler2, Nils Gählert1, Tristan Anselm Kuder1, Fenja Deister1, Martin Freitag1, Markus Hohenfellner2, Boris Hadaschik3, Heinz-Peter Schlemmer1, and Klaus Maier-Hein1

1German Cancer Research Center, Heidelberg, Germany, 2University Hospital Heidelberg, Heidelberg, Germany, 3University Hospital Essen, Essen, Germany

Multiparametric MRI (mpMRI) has recently seen further standardization by introduction of the PI-RADS version 2 system. mpMRI/transrectal ultrasound (TRUS)-guided fusion biopsies have demonstrated ability to closely match the histopathology seen after radical prostatectomy. Radiomics is a novel approach to extract a large number of quantitative features from medical imaging and combination with machine learning has demonstrated potential in the classification of mpMRI of the prostate. Here, we aim to compare state of the art radiomics and machine learning with ADC measurements,and prospective radiologist assessment using PI-RADS version 2 (PIRADSv2) in the evaluation of cancer suspicious lesions of the prostate.

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