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AI-based Prediction of Biochemical Recurrence from Biopsy and Prostatectomy Samples

2026-01-28 · Andrea Camilloni, Chiara Micoli, Nita Mulliqi, Erik Everett Palm, Thorgerdur Palsdottir, Kelvin Szolnoky, Xiaoyi Ji, Sol Erika Boman, Andrea Discacciati, Henrik Grönberg, Lars Egevad, Tobias Nordström, Kimmo Kartasalo, Martin Eklund arxiv

Biochemical recurrence (BCR) after radical prostatectomy (RP) is a surrogate marker for aggressive prostate cancer with adverse outcomes, yet current prognostic tools remain imprecise. We trained an AI-based model on diagnostic prostate biopsy slides from the STHLM3 cohort (n = 676) to predict patient-specific risk of BCR, using foundation models and attention-based multiple instance learning. Generalizability was assessed across three external RP cohorts: LEOPARD (n = 508), CHIMERA (n = 95), and TCGA-PRAD (n = 379). The image-based approach achieved 5-year time-dependent AUCs of 0.64, 0.70, and 0.70, respectively. Integrating clinical variables added complementary prognostic value and enabled statistically significant risk stratification. Compared with guideline-based CAPRA-S, AI incrementally improved postoperative prognostication. These findings suggest biopsy-trained histopathology AI can generalize across specimen types to support preoperative and postoperative decision making, but the added value of AI-based multimodal approaches over simpler predictive models should be critically scrutinized in further studies.

📄 PDF Abstract BibTeX arXiv:2601.21022

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Multiple Instance Learning Decision Making

Biochemical Prostate Cancer Recurrence Prediction: Thinking Fast & Slow

2024-09-03 · Suhang You, Sanyukta Adap, Siddhesh Thakur, Bhakti Baheti 외

Time to biochemical recurrence in prostate cancer is essential for prognostic monitoring of the progression of patients after prostatectomy, which assesses the efficacy of the surgery. In this work, we proposed to levera…

Multiple Instance Learning Prediction

Deep Learning From Routine Histology Improves Risk Stratification for Biochemical Recurrence in Prostate Cancer

2026-03-15 · Clément Grisi, Khrystyna Faryna, Nefise Uysal, Vittorio Agosti 외 arxiv

Accurate prediction of biochemical recurrence (BCR) after radical prostatectomy is critical for guiding adjuvant treatment and surveillance decisions in prostate cancer. However, existing clinicopathological risk models …

PROFUSEme: PROstate Cancer Biochemical Recurrence Prediction via FUSEd Multi-modal Embeddings

2025-09-17 · Suhang You, Carla Pitarch-Abaigar, Sanket Kachole, Sumedh Sonawane 외 arxiv

Almost 30% of prostate cancer (PCa) patients undergoing radical prostatectomy (RP) experience biochemical recurrence (BCR), characterized by increased prostate specific antigen (PSA) and associated with increased mortali…

Efficient AI-Driven Multi-Section Whole Slide Image Analysis for Biochemical Recurrence Prediction in Prostate Cancer

2026-03-17 · Yesung Cho, Dongmyung Shin, Sujeong Hong, Jooyeon Lee 외 arxiv

Prostate cancer is one of the most frequently diagnosed malignancies in men worldwide. However, precise prediction of biochemical recurrence (BCR) after radical prostatectomy remains challenging due to the multifocality …

GD-MIL: Grade-Disentangled Multiple Instance Learning for Multimodal Biochemical Recurrence Prediction in Prostate Cancer

2026-06-08 · Dasari Naga Raju arxiv

Biochemical recurrence (BCR) after radical prostatectomy is a critical endpoint in prostate cancer, yet risk stratification relies almost entirely on variables dominated by Gleason grade. Whether H&E whole slide images (…

Multiple Instance Learning