Abstract #4822

Quantitative Imaging Habitat Risk Score (HRS) Combined with PI-RADSv2 Improves Predictive Value of Prostate Lesion Identification on mpMRI

Veronica Wallaengen¹, Adrian L Breto¹, Isabella M Kimbel¹, Evangelia I Zacharaki¹, Ahmad Algohary¹, Nachiketh Soodana Prakash², Sandra M Gaston¹, Rosa P Castillo Acosta³, Oleksandr N Kryvenko⁴, Bruno Nahar², Dipen J Parekh², Alan Pollack¹, Sanoj Punnen², and Radka Stoyanova¹

¹Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, United States, ²Department of Urology, University of Miami Miller School of Medicine, Miami, FL, United States, ³Department of Radiology, University of Miami Miller School of Medicine, Miami, FL, United States, ⁴Department of Pathology, University of Miami Miller School of Medicine, Miami, FL, United States

Synopsis

Keywords: Software Tools, Cancer

Motivation: Discrimination between true and false positive targets identified using PI-RADSv2 is needed to avoid unnecessary biopsies.

Goal(s): To investigate how quantitative analysis of prostate mpMRI through Habitat Risk Scoring (HRS) combined with PI-RADS can improve prostate lesion identification compared to using PI-RADS alone.

Approach: In prospective clinical trials lesions identified by PI-RADS and/or HRS were targeted through MRI/ultrasound fusion biopsies.

Results: Using HRS yields 100% NPV in the PI-RADS 3 cohort and increases PPV by 7.4% in the PI-RADS 4-5 cohort with respect to clinically significant cancer. Overall, the NPV and PPV increased by 21.4% and 13.2% respectively.

Impact: We present a quantitative imaging approach to complement the current standard for assessing prostate cancer risk in mpMRI data and demonstrate that the use of HRS strengthens fidelity in both positive and negative detections.

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