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PEER-TO-PEER CLINICAL CONVERSATIONS |
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| The Future of Prostate Cancer Diagnosis: Combining Non-Invasive Tests for Personalized Care |
Eric Kim, MD
Preston Sprenkle discusses with Eric Kim the integration of MRI and genomic classifiers in prostate cancer management. They explore the potential of artificial intelligence (AI) to enhance diagnostic accuracy and personalization of treatment. |
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Generative Artificial Intelligence in Healthcare "Presentation"
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Inderbir Singh Gill, MD
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| Inderbir Gill presents on the growing importance and applications of artificial intelligence (AI) in urology. He emphasizes AI's transformative role in academic publishing and clinical practice, noting its potential to mitigate physician burnout by automating routine tasks.
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| The Power of Artificial Intelligence in Urology "Presentation" |
| Jodi Maranchie, MD, FACS |
| Jodi Maranchie delivers a presentation on the impact of artificial intelligence (AI) in urologic oncology. She begins by explaining the basics of machine learning and its progression to deep learning, emphasizing how AI excels in pattern recognition, a key aspect of medical diagnosis. |
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| Artificial INtelligence to Support Informed DEcision-Making (INSIDE) for Improved Literature Analysis in Oncology - Beyond the Abstract
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| Arnulf Stenzl, Andrew Armstrong, Andrea Sboner et al.
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| The INSIDE-PC study demonstrates the potential of AI systems in medical literature searches, especially for complex clinical questions like therapy sequencing in prostate cancer (PC). The study shows that INSIDE-PC can outperform traditional search tools like PubMed in relevance for certain therapy sequences and emphasizes the need for clear validation standards and a unified language in therapeutic sequencing. This AI-based platform offers a promising tool for clinicians navigating the rapidly expanding medical literature.
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| Artificial Intelligence and Prostate Cancer: Diagnosis and Grading, mpMRI, and Active Surveillance
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| Zachary Klaassen, MD, MSc, and Rashid Sayyid, MD, MSc
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| Zach Klaassen and Rashid Sayyid review the advancements in artificial intelligence (AI) applications in prostate cancer diagnosis, grading, multiparametric MRI (mpMRI), and active surveillance. AI has improved the accuracy and consistency of prostate cancer grading, demonstrated by high performance in identifying and quantifying Gleason patterns.
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| Variation in Prostate Cancer Genomic Subtypes Across Prostate MRI PI-RADS Scores and Race
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| Nimrod Barashi, MD
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| Nimrod Barashi presents a study on the variation of prostate cancer genomic subtypes across MRI PI-RADS scores and race. Using a diverse cohort of 760 patients, the study found that Decipher genomic classifier scores generally correlated well with PI-RADS scores, indicating more aggressive cancer subtypes in higher PI-RADS lesions. The findings highlight the importance of considering both genomic data and race in prostate cancer risk stratification, with ongoing questions about the roles of genomics and artificial intelligence in improving diagnosis and treatment.
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| Artificial Intelligence: Innovation and Potential for Diagnostic Imaging in Prostate Cancer
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| Stephanie Harmon, Ph.D.
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| Stephanie Harmon highlights the potential and innovation of artificial intelligence (AI) in prostate cancer diagnostic imaging. AI can improve quality control, lesion detection, and treatment planning in prostate imaging, particularly with multiparametric MRI. Despite challenges like site-specific variability and model overfitting, AI has shown promise in enhancing image interpretation and diagnostic accuracy, especially in advanced disease imaging with PSMA PET/CT.
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| Panel Discussion: Artificial Intelligence |
| Andrew Hung, MD, Geoffrey Sonn, MD, Joseph Liao, MD, Prokar Dasgupta, OBE, FRCS |
| This panel led by Andrew Hung discusses the transformative potential of AI in prostate cancer care. Dr. Hung clarified AI terminologies, highlighting distinctions between machine learning and deep learning, and between supervised and unsupervised AI. Dr. Geoffrey Sonn emphasized AI’s impact on medical imaging, noting that its effectiveness depends on high-quality training datasets and unbiased validation through international competitions. Dr. Joseph Liao pointed out AI’s ability to integrate diverse data for comprehensive analysis, while Dr. Prokar Dasgupta stressed the importance of democratizing AI through collaboration among countries, companies, and civil society to ensure ethical and impactful implementation. |
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| Using Artificial Intelligence to Optimize Systemic Therapy for Prostate Cancer |
| Irbaz Riaz, MD, MBBS |
| Irbaz Riaz discusses how artificial intelligence (AI) can optimize systemic therapy for prostate cancer by addressing several challenges in treatment selection. AI can assist healthcare providers by handling complex data, creating living clinical practice guidelines, and integrating multi-modal data to provide individualized treatment effects. Dr. Riaz highlights that AI agents are well-suited to support clinicians, enable dynamic guidelines, and generate novel insights from diverse patient data, advancing personalized care in prostate cancer. |
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