120: DigPath Digest #21 | AI's Role in Prostate & Breast Cancer Diagnosis and Collaborative Annotation Tools
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Welcome to the 21st edition of DigiPath Digest! In this episode, together with Dr. Aleksandra Zuraw you will review the latest digital pathology abstracts and gain insights into emerging trends in the field. Discover the promising results of the PSMA PET study for prostate cancer imaging, explore the collaborative open-source platform HistioColAI for enhancing histology image annotation, and learn about AI's role in improving breast cancer detection. Dive into topics such as the role of AI in renal histology classification, the innovative TrueCam framework for trustworthy AI in pathology, and the latest advancements in digital tools like QuPath for nephropathology. Stay tuned to elevate your digital pathology game with cutting-edge research and practical applications.

00:00 Introduction to DigiPath Digest #2101:22 PSMA PET in Prostate Cancer06:49 HistoColAI: Collaborative Digital Histology12:34 AI in Mammogram Analysis17:21 Blood-Brain Barrier Organoids for Drug Testing22:02 Trustworthy AI in Lung Cancer Diagnosis30:09 QuPath for Nephropathology35:30 AI Predicts Endocrine Response in Breast Cancer40:04 Comprehensive Classification of Renal Histologic Types45:02 Conclusion and Viewer EngagementLinks and Resources:

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• HistoColAI Github Page)

Publications Discussed Today:📰 Can PSMA PET detect intratumour heterogeneity in histological PSMA expression of primary prostate cancer? Analysis of [68Ga]Ga-PSMA-11 and [18F]PSMA-1007)

📰 HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration)

📰 Advanced tissue technologies of blood-brain barrier organoids as high throughput toxicity readouts in drug development)

📰 Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images)

📰 GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning)

📰 Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer)

📰 Leveraging explainable AI and large-scale datasets for comprehensiv)

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