Peer-Reviewed Publication
J Natl Cancer Inst2026July 10, 2026Journal Article
Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction.
Matthew R Cooperberg1,2, Kevin Shee1, Janet E Cowan1, Chien-Kuang C Ding1,3, Tamara Todorovic4, Imelda Tenggara1, Siyi Tang4, Rikiya Yamashita4, Trevor Royce4, Emmalyn Chen4, Meghan Tierney4, Xiao Ma4, Yi Ren4, Huei-Chung Huang4, Danielle C Croucher4, Jeffry P Simko1,3, Felix Y Feng1,5, Timothy Showalter4, Peter R Carroll1
1Department of Urology, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
2Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.
3Department of Pathology, University of California, San Francisco, CA, USA.
4Artera AI, Inc, Los Altos, CA, USA.
5Department of Radiation Oncology, University of California, San Francisco, CA, USA.
Abstract
BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation. The MMAI has been explored to an extent for prostatectomy patients and has not yet been examined in relation to established genomic scores.
METHODS: We applied the MMAI biopsy model to a tissue microarray (TMA) of 424 prostatectomy cases with long…
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