Rikiya Yamashita

Combining pathology artificial intelligence and genomic biomarkers to refine long-term post-prostatectomy outcome prediction

Matthew R. Cooperberg, Kevin Shee, Janet E. Cowan, Chien‐Kuang Cornelia Ding et autres

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 …

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Image-only and multimodal AI digital pathology biomarkers to demonstrate risk stratification across standard prostate cancer management strategies.

Xinglei Shen, Rana R. McKay, Yi Ren, Xiaoxuan Yang et autres

5023 Background: Reliable risk stratification across standard treatment pathways is essential for the clinical adoption of precision medicine biomarkers in localized prostate cancer. We previously developed and validated a multimodal artificial intelligence (MMAI) model that integrates digitized hematoxylin and eosin (H&E) prostate …

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External validation of a digital pathology-based multimodal artificial intelligence (MMAI)-derived prognostic biomarker in the randomised phase III CHHiP trial.

Sarah Stewart, Elizabeth S. Limb, Holly Tovey, Yi Ren et autres

308 Background: Risk stratification in localised prostate cancer (PCa) based on clinicopathological parameters is inadequate, leading to under- and over-treatment. We used CHHiP trial data to externally validate a previously-developed MMAI prognostic model with potential for cost-effective improved treatment personalisation. Methods: H&E …

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Opening the black box: Biologic pathways underlying multimodal digital-pathology artificial intelligence in metastatic prostate cancer.

Amol Carl Shetty, Yang Song, Adrianna Mendes, Rikiya Yamashita et autres

232 Background: Prostate cancer (PCa) spans indolent localized to lethal metastatic castration-resistant disease, underscoring the need for biologically grounded risk tools. ArteraAI multimodal artificial intelligence (MMAI), one of only two NCCN guideline–supported biomarkers for localized PCa and backed by Simon Level 1B …

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Postoperative Pancreatic Fistula After Pancreatoduodenectomy

Ankur P. Choubey, Joséphine Magnin, Johan Gagnière, Abhishek Midya et autres

OBJECTIVE: Assess the potential added benefit of radiomics to clinical models for predicting postoperative pancreatic fistula (POPF) after pancreatoduodenectomy (PD). SUMMARY OF BACKGROUND DATA: Radiomics extracts quantitative data from medical imaging based on enhancement patterns. Clinical applications of radiomics have been investigated …

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Validation of a Prognostic Multimodal Artificial Intelligence (MMAI) Model in Asian Prostate Cancer (PCa) Patients (pts) from Singapore

Enya H.W. Ong, Boon Hao Hong, Songwan Joun, H.C. Huang et autres

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External validation of a digital pathology-based multimodal artificial intelligence-derived prognostic model in patients with advanced prostate cancer starting long-term androgen deprivation therapy: a post-hoc ancillary biomarker study of four phase 3 randomised controlled trials of the STAMPEDE platform protocol

Charles T.A. Parker, Larissa Sena Teixeira Mendes, Vinnie Y.T. Liu, Emily Grist et autres

BACKGROUND: Effective prognostication improves selection of patients with prostate cancer for treatment combinations. We aimed to evaluate whether a previously developed multimodal artificial intelligence (MMAI) algorithm was prognostic in very advanced prostate cancer using data from four phase 3 trials of the …

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External validation of a pathology-based multimodal artificial intelligence biomarker for predicting prostate cancer outcomes after prostatectomy.

Chien‐Kuang Cornelia Ding, Kevin Shee, Janet E. Cowan, Yi Ren et autres

5106 Background: Radical prostatectomy (RP) improves survival and delays metastasis in localized prostate cancer (PCa) patients (pts), yet 20-40% of men experience biochemical recurrence (BCR) within 10 years, with one-third of these progressing to metastatic disease. Predictive tools for risk stratification and …

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Multimodal artificial intelligence (MMAI) model to identify benefit from 2nd-generation androgen receptor pathway inhibitors (ARPI) in high-risk non-metastatic prostate cancer patients from STAMPEDE.

Charles Thomas Parker, Vinnie YT Liu, Larissa Sena Teixeira Mendes, Emily Grist et autres

5001 Background: The STAMPEDE trials showed that adding abiraterone acetate + prednisolone (AAP) ± enzalutamide (ENZ) to standard of care androgen deprivation therapy (SOC) improves metastasis-free survival (MFS) in high-risk non-metastatic (M0) prostate cancer (PCa) patients (pts). However, variable responses & adverse …

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Assessing Algorithmic Fairness With a Multimodal Artificial Intelligence Model in Men of African and Non-African Origin on NRG Oncology Prostate Cancer Phase III Trials

Mack Roach, Jingbin Zhang, Osama Mohamad, Douwe van der Wal et autres

PURPOSE Artificial intelligence (AI) tools could improve clinical decision making or exacerbate inequities because of bias. African American (AA) men reportedly have a worse prognosis for prostate cancer (PCa) and are underrepresented in the development genomic biomarkers. We assess the generalizability of …

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Development and Validation of an Artificial Intelligence Digital Pathology Biomarker to Predict Benefit of Long-Term Hormonal Therapy and Radiotherapy in Men With High-Risk Prostate Cancer Across Multiple Phase III Trials

Andrew J. Armstrong, Vinnie Y.T. Liu, Ramprasaath R. Selvaraju, Emmalyn Chen et autres

PURPOSE Long-term androgen deprivation therapy (ADT) improves survival in men with high-risk localized prostate cancer (PCa) receiving radiotherapy (RT). Predictive biomarkers are needed to guide ADT duration. METHODS A multimodal artificial intelligence (MMAI)–derived predictive biomarker was trained for long-term (LT) versus short-term …

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IP05-38 PREDICTING LONG TERM OUTCOMES FOLLOWING RADICAL PROSTATECTOMY USING A VALIDATED PATHOLOGY-BASED MULTIMODAL ARTIFICIAL INTELLIGENCE BIOMARKER

Matthew R. Cooperberg, Kevin Shee, Janet E. Cowan, Tamara R. Todorović et autres