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Transforming Pathology: A Deep Dive into the Muse System

This episode is sponsored by Muse Microscopy. 

In this episode, we explore the primary challenge of implementing digital pathology globally—digitizing the analog. 

A potential solution is direct-to-digital pathology, exemplified by the MUSE system by Muse Microscopy. This technology eliminates the need for glass slides and manual staining, offering rapid, non-destructive imaging of intact tissue samples. 

You will learn about the advantages of Muse, including faster diagnostics, improved data fidelity, and broader accessibility, particularly in remote areas.

 Detailed insights into the Muse workflow, imaging techniques, and potential applications in human and veterinary medicine are provided. 

Challenges like adoption barriers and regulatory hurdles are also addressed. Join us as we explore how the Muse system is redefining diagnostic workflows and enhancing patient outcomes.

00:00 Introduction to Digital Pathology
00:18 The Hurdle of Digitizing Analog Pathology
00:26 Direct to Digital Pathology: A Game Changer
01:46 Introduction to Muse Microscopy
02:32 How Direct to Digital Pathology Works
03:10 Advantages of Direct to Digital Pathology
04:13 Understanding Muse Technology
05:26 The Digital Pathology Workflow with Muse
14:15 Challenges and Misconceptions
15:38 The Future of Pathology
16:31 Frequently Asked Questions
18:07 Conclusion and Additional Resources
18:54 Behind the Scenes and Final Thoughts

Links and Resources:

• Original blog post on Digital Pathology Place  Website and LinkedIn
• YouTube playlist with more information about MUSE
• SmartPath Product presentation from CAP 2024
• Video showing the SmartPath device at the conference booth
• USCAP in Boston - Muse Microscopy booth #528

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In this episode of the Digital Pathology Podcast, I take a deeper dive into Generative AI in Pathology, following the AI in Pathology series published by USCAP. AI has already begun transforming medical diagnostics, but what does Generative AI mean for digital pathology? From synthetic data generation to multimodal AI models, this episode explores the cutting edge of AI’s role in pathology and how it’s evolving to enhance efficiency, accuracy, and patient care.

🔬 Key Topics Covered:

• [00:00:00] Introduction – The Evolution of AI in Pathology
• [00:02:00] Acknowledging the Authors Behind the AI Review Series
• [00:04:00] What Is Generative AI and Why Is It a Game-Changer?
• [00:06:00] The Cambrian Explosion of Generative AI in Medicine
• [00:08:00] Understanding Transformer Architectures and Cloud Computing
• [00:12:00] ChatGPT, DALLE, and Multi-Modal AI: What’s Next?
• [00:18:00] Synthetic Data Generation: A New Era for Pathology Training
• [00:24:00] How AI Can Pass Medical Exams and Assist Pathologists
• [00:30:00] Reducing Bias and Ethical Concerns in AI-Based Diagnostics
• [00:38:00] Real-World Use Cases of AI-Generated Pathology Reports
• [00:45:00] The Future of Generative AI in Digital Pathology

🩺 Why This Episode Matters:
Generative AI is no longer just a concept—it’s already being used to train models, generate high-fidelity pathology images, and assist with diagnostic decision-making. However, challenges remain, from bias in AI models to the need for domain-specific training data. Understanding these factors is essential for pathologists and medical professionals who want to leverage AI responsibly in clinical practice.

🚀 What’s Next?
This episode discusses not just what Generative AI is but how it can reshape pathology workflows and where we’re headed next. If you’re interested in how AI can improve efficiency and accuracy in diagnostics, this is a conversation you don’t want to miss.

🎧 Listen now to explore the future of Generative AI in pathology!

👉 Watch or listen here: https://www.youtube.com/live/hRv9GmMWSjk?si=OEg8gafqRA2M_zlx

#DigitalPathology #AIinHealthcare #PathologyInnovation #GenerativeAI

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In this episode of the Digital Pathology Podcast, I explore the evolving role of Generative vs. Non-Generative AI in Medical Diagnostics. As AI continues to transform the medical field, understanding the differences between these two approaches is essential for pathologists, researchers, and healthcare professionals.

We break down the key concepts behind generative AI models (like ChatGPT and image-generation tools) and non-generative AI models (such as traditional machine learning for diagnostic support). I also highlight a groundbreaking seven-part AI review series published in Modern Pathology, which serves as a crucial reference for integrating AI into pathology.

🔬 Key Topics Covered:

• [00:00:00] Introduction and Technical Adjustments
• [00:02:00] Why AI Education in Pathology Is More Important Than Ever
• [00:04:00] Overview of the Modern Pathology AI Review Series
• [00:06:00] Generative vs. Non-Generative AI: What’s the Difference?
• [00:08:00] AI in Pathology: Current Applications and Future Potential
• [00:12:00] Addressing Bias and Ethical Concerns in AI Models
• [00:16:00] How AI Can Improve Accuracy in Medical Imaging
• [00:20:00] The Role of Large Language Models (LLMs) in Pathology
• [00:25:00] Multi-Modal AI: The Future of Integrating Imaging and Text Data
• [00:30:00] Real-World Use Cases and AI-Driven Diagnostics

🩺 Why This Episode Matters:
AI is no longer a futuristic concept—it’s here, and it’s shaping the future of digital pathology and medical diagnostics. In this episode, I break down how AI can enhance accuracy, improve workflow efficiency, and make diagnostic insights more accessible. However, AI models also come with risks, such as bias and interpretability challenges, which we need to address responsibly.

🚀 Take Action:
AI in pathology isn’t just a passing trend—it’s a paradigm shift. Whether you're a pathologist, researcher, or lab professional, this episode will give you the knowledge you need to stay ahead in the era of AI-driven diagnostics.

🎧 Listen now and explore the future of AI in pathology!

👉 Watch it here: https://www.youtube.com/live/Mq4Xwxoq_ok?si=o7bA90BlZff9iI_A

#DigitalPathology #AIinHealthcare #PathologyInnovation #GenerativeAI

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In this episode of the Digital Pathology Podcast, I sit down with Dr. Lija Joseph, a pathologist who is redefining patient care by making pathology more accessible and understandable. Traditionally, pathology has been a “behind-the-scenes” specialty, but Dr. Joseph is changing that by directly engaging with patients, showing them their pathology slides, and empowering them with knowledge about their diagnoses.

🔬 Key Topics Covered:

• [00:00:00] Introduction to Patient-Centric Pathology
• [00:01:00] Meet Dr. Lija Joseph: Her Background and Journey
• [00:05:00] The Patient Who Inspired a New Approach
• [00:10:00] Why Patients Need to See Their Pathology Images
• [00:15:00] The Power of Knowledge: How Patient Awareness Improves Care
• [00:20:00] Overcoming Barriers to Patient-Pathologist Communication
• [00:25:00] How Digital Pathology Can Make This Scalable
• [00:30:00] The Role of Technology in Breaking Down Access Barriers
• [00:35:00] Convincing Healthcare Leadership to Support This Initiative
• [00:40:00] How Digital Pathology Can Transform Patient Outcomes

🩺 Why This Matters:
Most patients never meet their pathologists—but should they? Dr. Joseph believes so. She shares powerful stories of how patients who see their own slides gain a deeper understanding of their disease, make better treatment decisions, and experience greater peace of mind.

🚀 How Digital Pathology Can Change the Future:
Dr. Joseph’s approach is innovative, but digital pathology can take it even further. Imagine a world where patients don’t have to visit a hospital to see their biopsy results but can access them remotely through secure digital platforms. This technology has the potential to bridge the gap between patients and their pathologists, improving care and trust.

🎧 Tune in now to learn how pathology can become more patient-focused!

#DigitalPathology #PatientCenteredCare #PathologyInnovation #AIinHealthcare

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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 #21
01:22 PSMA PET in Prostate Cancer
06:49 HistoColAI: Collaborative Digital Histology
12:34 AI in Mammogram Analysis
17:21 Blood-Brain Barrier Organoids for Drug Testing
22:02 Trustworthy AI in Lung Cancer Diagnosis
30:09 QuPath for Nephropathology
35:30 AI Predicts Endocrine Response in Breast Cancer
40:04 Comprehensive Classification of Renal Histologic Types
45:02 Conclusion and Viewer Engagement

Links and Resources:

• Subscribe to Digital Pathology Podcast on YouTube
• Free E-book "Pathology 101"
• YouTube (unedited) version of this episode
• Try Perplexity with my referral link
• My new page built with Perplexity
• 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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In this episode of the Digital Pathology Podcast, you will learn about cytology's entrance into the digital pathology space, including successful AI and scanner implementations.

We cover AI's role in rapid on-site evaluation for lung cancer and share insights on a looming prostate cancer surge and how digital pathology and AI can help. I

You will also listen to a live demo of me using an AI assistant to decode a scientific paper in real-time. Tune in to stay on top of the digital pathology research in 2025!

00:00 Welcome to DigiPath Digest
00:53 Introduction and New Year Greetings
01:41 Diving into DigiPath Digest
01:44 AI in Respiratory Cytology
06:11 The Role of AI in Pathology
09:49 Multi-Omics and AI
11:28 Radiomics and Pathomics
14:44 Live Q&A and Future Plans
20:09 Prostate Cancer Tsunami
22:34 Thyroid Cytology and Live AI-Assistant demo
31:07 Conclusion and the option to send texts :)

Links and Resources:

• Subscribe to Digital Pathology Podcast on YouTube
• Free E-book "Pathology 101"
• YouTube (unedited) version of this episode
• Try Perplexity with my referral link
• My new page built with Perplexity

Publications Discussed Today:

📝 Evaluation of an enhanced ResNet-18 classification model for rapid On-site diagnosis in respiratory cytology

📝 Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization

📝 A machine learning approach to predict HPV positivity of oropharyngeal squamous cell carcinoma

📝 The uropathologist of the future: getting ready with intelligence for the prostate cancer tsunami

📝 Artificial Intelligence and Whole Slide Imaging Assist in Thyroid Indeterminate Cytology: A Systematic Review

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In this episode, I’m joined by Dr. Giovanni Lujan, Nick Best, and Dr. Alae Kawam to explore a topic that hits close to home for many of us in digital pathology: why do so few pathologists attend digital pathology conferences? We delve into the barriers, opportunities, and actionable solutions that can help bridge this gap and drive the adoption of digital pathology across the profession.

What You’ll Hear in This Episode:

• Startling Observations (00:02:00): Only 10% of attendees at some digital pathology conferences are pathologists. Why is this the case, and what does it mean for the future of the field?
• Barriers to Adoption (00:04:00): From time constraints to a lack of institutional support, we unpack the key challenges stopping pathologists from going digital.
• Mentorship and Collaboration (00:09:00): How mentorship programs can connect seasoned professionals with early-career pathologists to share knowledge and drive adoption.
• The Role of the Next Generation (00:15:00): Insights into how young pathologists can lead the way with their enthusiasm and fresh perspectives.
• Engaging the Skeptics (00:07:00): Strategies to introduce hesitant or resistant pathologists to the transformative power of digital tools.
• Global Comparisons (00:10:00): What can the U.S. learn from Europe and Asia about accelerating digital pathology adoption?
• Leveraging Leadership and Advocacy (00:19:00): How young pathologists can work with leadership to introduce digital pathology as a standard practice in their organizations.
• The Impact of Digital Pathology on Work-Life Balance (00:20:00): Exploring how remote sign-outs and shorter turnaround times can enhance both patient care and pathologists’ quality of life.
• Making Digital Pathology the Norm (00:24:00): Ideas for shifting digital pathology from a secondary option to the standard of care, addressing common fears and misconceptions.
• Future Plans and Next Steps (00:28:00): A look at actionable steps for advancing digital pathology through podcasts, mentorship, and departmental advocacy.

Key Takeaways:
This conversation isn’t just about identifying challenges—it’s about solutions. We discuss how collaboration, leadership, and individual responsibility can drive meaningful change in digital pathology. Whether you’re a seasoned pathologist or just starting your career, this episode offers inspiration and actionable ideas to make digital pathology a core part of the profession.

Connect With Us:
Share your thoughts on why more pathologists aren’t attending these conferences. What’s holding them back, and what changes would you like to see in your department? Let’s keep this important conversation going!

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Become a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

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Leveraging AI for Deep Insights into Tertiary Lymphoid Structures in Colorectal Cancer

In this episode of the Digital Pathology Podcast, I introduce 'Aleks + AI,' a new experimental series leveraging Google's Notebook LM to delve deeper into scientific literature.

Today's focus is on tertiary lymphoid structures (TLS) and their potential to predict colorectal cancer prognosis. We discuss a study published in the October 2024 issue of Precision Clinical Medicine, exploring different methods of quantifying TLS using digital pathology and AI. 

The paper title is: "Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study"

The findings highlight TLS density as a reliable predictor of survival and its correlation with immune responses and microsatellite instability. We also touch upon the potential for AI to streamline TLS analysis in clinical settings and the broader implications for personalized medicine. Join us as we dive into the intersection of digital pathology and computer science, featuring insights and commentary from my AI co-hosts, Hema and Toxy.

00:00 Welcome and Introduction
00:45 Introducing the New AI Tool: Notebook LM by Google
01:11 Experimental Series: "Aleks + AI"
02:06 Deep Dive into Tertiary Lymphoid Structures (TLS)
03:18 Understanding TLS and Their Role in Colorectal Cancer
04:20 Quantification Methods and Key Findings
05:02 Implications for Personalized Medicine
09:02 AI in TLS Analysis and Future Prospects
11:00 CMS Classification and TLS Density
12:08 Study Limitations and Future Directions
15:40 Final Thoughts and Wrap-Up
16:28 Feedback and Future Plans

THIS EPISODE'S RESOURCES

• 116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving Privacy

PUBLICATION DISCUSSED TODAY

📝 Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study
🔗https://academic.oup.com/pcm/article/7/4/pbae030/7826772

📱 Send us a text

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In today's DigiPath Digest, we delve into federated learning, a decentralized approach to AI training that preserves data privacy.

I discuss recent papers from PubMed and share my experiences experimenting with AI tools like Perplexity and Gemini for research efficiency.

You will also get updates on upcoming plans, including leveraging AI to share more podcasts with you.

Did I mention that this is the last livestream of the year as I head to Poland for Christmas? No More DigiPath Digests. We got to number 18 (I overestimated it a bit in the podcast), and you have been instrumental in continuing this series!

Big THANK YOU to all the digital Pathology #TRLBLZRS showing up every Friday morning for this!

Join me as we tackle the nuances of federated learning and its impact on healthcare and pathology.

00:00 Introduction and Greetings
00:18 Today's Topic: Federated Learning
00:57 AI Tools and Updates
04:39 Federated Learning in Detail
08:03 Challenges and Benefits of Federated Learning
11:21 Exploring More Papers and Future Plans
22:53 Wrapping Up and Final Thoughts

Links and Resources:

• Subscribe to Digital Pathology Podcast on YouTube
• Free E-book "Pathology 101"
• YouTube (unedited) version of this episode
• Try Perplexity with my referral link
• My new page built with Perplexity

Publications Discussed Today:

📝 Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine
🔗https://pubmed.ncbi.nlm.nih.gov/39610333/

📝 A review on federated learning in computational pathology
🔗https://pubmed.ncbi.nlm.nih.gov/39582895/


If you enjoyed this episode, please subscribe and leave a review on your podcast listening App!

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This episode features a conversation with Dr. Richard Doughty, Senior Medical Advisor at Aiforia Technologies, whose dual training in veterinary and medical pathology offers a unique perspective on the intersections of these fields. Together, we explore the challenges, opportunities, and innovations shaping digital pathology today.

What You’ll Learn in This Episode:

• [00:00:00] Challenges in Pathology Today
  Discussing the pathologist shortage, delayed diagnoses, and how AI can address these issues.
• [00:03:00] A Pathologist’s Dual Perspective
  Dr. Doughty shares his journey of becoming both a veterinary and medical pathologist, and what this means for pathology innovation.
• [00:08:00] AI’s Role in Pathology
  Insights into how clinician-centric AI tools like Aiforia are designed to improve diagnostic workflows and outcomes.
• [00:14:00] Addressing Challenges in AI Integration
  Strategies for overcoming hurdles like algorithm aversion, skill retention, and fostering trust in AI systems.
• [00:22:00] Preparing Future Pathologists
  The importance of incorporating AI training into residency programs and creating a digitally savvy workforce.
• [00:44:00] How to Implement AI Effectively
  Practical advice on selecting tools, collaborating with providers, and setting realistic goals for AI adoption in practice.

Resources and Links Mentioned:

• Learn More About Aiforia: https://www.aiforia.com/
• Download Digital Pathology 101
• Contact Dr. Richard Doughty: [email protected]
• Watch more videos created together with Aiforia: VIDEO PLAYLIST

This episode is supported by Aiforia Technologies, leaders in AI-powered solutions for digital pathology.

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