Extracapsular extension risk assessment using an artificial intelligence prostate cancer mapping algorithm.

Alan Priester^1,2, Sakina Mohammed Mota¹, Kyla P Grunden², Joshua Shubert¹, Shannon Richardson², Anthony Sisk³, Ely R Felker⁴, James Sayre⁵, Leonard S Marks², Shyam Natarajan^1,2, Wayne G Brisbane²

¹Avenda Health, Inc. United States.

²Department of Urology David Geffen School of Medicine United States.

³Department of Pathology David Geffen School of Medicine United States.

⁴Department of Radiology David Geffen School of Medicine United States.

⁵Department of Radiological Sciences and Biostatistics University of California, Los Angeles United States.

PubMed PMC DOI PDF

Abstract

OBJECTIVE: The objective of this study is to compare detection rates of extracapsular extension (ECE) of prostate cancer (PCa) using artificial intelligence (AI)-generated cancer maps versus MRI and conventional nomograms. MATERIALS AND METHODS: We retrospectively analysed data from 147 patients who received MRI-targeted biopsy and subsequent radical prostatectomy between September 2016 and May 2…

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