Digital Pathology Podcast

Send us a textWhat if the way we quantify pathology is more guesswork than science? In this episode of DigiPath Digest, I take you through the latest research where AI is not just supporting but challenging traditional methods of image analysis in neuropathology, nephrology, hematology, and cytology. From Boston brain banks to Mayo Clinic kidney models, we look at how advanced AI compares to human vision—and where it already outperforms us.Episode Highlights:[00:02:49] Neuropathology image analysis (Boston VA & BU) – Why traditional semiquantitative scoring often fails, and how AI-based density quantification reveals more subtle pathology in CTE.[00:13:16] Chronic kidney changes with AI (Mayo Clinic, Cambridge, Emory, Geneva) – A 20-class AI model trained on 20,500 annotations, showing how multiclass segmentation outperforms human guesswork in renal pathology.[00:21:09] Digital hematology review (University of Pennsylvania) – Current hurdles in AI for blood and bone marrow evaluation: regulatory oversight, data standardization, and resistance to change.[00:25:52] AI in cytology review (Journal of Cytopathology) – From BD FocalPoint to deep learning: two decades of digital cytology, stagnation, and why adoption still lags despite proven benefits.[00:32:09] Neuropathology goes digital – Where digital neuropathology is already routine (Ohio State, Mayo Clinic, Leeds, Granada) and why this specialty is crucial for pushing adoption.[00:34:19] Personal note – Why I believe learning, sharing, and experimenting with AI tools now will shape the way we practice pathology tomorrow.Resources from this EpisodeComparison of quantitative strategies in neuropathologic image analysis – Boston VA / BU Brain Bank study.Multiclass AI model for chronic kidney changes – Mayo Clinic, Cambridge, Emory, Georgia Tech, Geneva collaboration.Review: Digital hematology in the AI era – International Journal of Laboratory Hematology.Review: AI and machine learning in cytology – Journal of the American Society of Cytopathology.Digital Pathology 101 (by me, Dr. Aleksandra Zuraw) – Free PDF & Amazon print edition.Pathology AI Makeover Course – Practical training for AI in pathology workflows.Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textWhat if the AI tools we trust for cancer diagnosis are not always correct? This episode of DigiPath Digest takes on the uncomfortable but critical question: can AI “lie” to us—and how do we verify its performance before adopting it in clinical practice?Highlights:[00:02:00] Foundation models in action: Deployment of a fine-tuned pathology foundation model for EGFR biomarker detection in lung cancer—reducing the need for rapid molecular tests by 43%.[00:08:41] Bone marrow AI misclassifications: Why automated digital morphology still struggles with consistency across leukemia and lymphoma cases.[00:14:45] Lossy DICOM conversion: How file format changes can subtly—but significantly—affect AI model performance.[00:21:45] Federated tumor segmentation challenge: Coordinating 32 international institutions to benchmark healthcare AI fairly across diverse datasets.[00:27:47] AI in gynecologic cytology: Reviewing AI-driven Pap smear screening—promise, limitations, and why rigorous validation remains essential.[00:32:27] Takeaway: Trust but verify—AI tools must be validated before they can support or replace clinical decisions.Resources from this EpisodeNature Medicine – Fine-tuned pathology foundation model for lung cancer EGFR biomarker detection.Scientific Reports (Germany) – Study on how DICOM conversion impacts AI performance in digital pathology.Federated Tumor Segmentation Challenge – Benchmarking AI across 32 global institutions.Acta Cytologica – Review on AI in gynecologic cytology and Pap smear screening.Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textWhat if AI could predict cancer outcomes better than traditional methods—and at a fraction of the cost? In this episode, I explore how multimodal AI is reshaping lung and prostate cancer predictions and why integration challenges still stand in the way.Episode Highlights with Timestamps:[00:02:57] Agentic AI in toxicologic pathology – what it is and how it could orchestrate workflows.[00:05:40] Grandium desktop scanners – making histology studies more accessible and efficient.[00:08:03] Clover framework – a cost-effective multimodal model combining vision + language for pathology.[00:13:40] NSCLC study (Beijing Chest Hospital) – AI predicts progression-free and overall survival with high accuracy.[00:17:58] Prostate cancer prognostic model (Cleveland Clinic & US partners) – validating AI-enabled Pathomic PRA test.[00:23:35] Thyroid neoplasm classification – challenges for AI in distinguishing overlapping histopathological features.[00:34:49] Real-world Belgium case study – AI integration into prostate biopsy workflow reduced IHC testing and turnaround time.[00:41:03] Lessons learned – adoption hurdles, system integration, and why change management is essential for successful digital transformation.Resources from this EpisodeWorld Tumor Registry – A global open-access repository for histopathology images: World Tumor RegistryBeijing Chest Hospital NSCLC AI Prognostic Study – Prognosis prediction using multimodal models.Cleveland Clinic Pathomic PRA Study – Independent validation of AI-enabled prostate cancer risk assessment.Grandium Scanners – Compact desktop scanners for histology slides: Grandium.aiSupport the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a text“AI in Pathology Isn't Coming — It's Already Here. Are You Ready?”From confusion to clarity — that's what this episode is all about. I sat down with Drs. Liron Pantanowitz, Hooman Rashidi, and Matthew Hanna to dissect one of the most important and comprehensive AI-in-pathology resources ever created: the 7-part Modern Pathology series from UPMC's Computational Pathology & AI Center of Excellence (CPAiCE). This isn't just another opinion piece — it's your complete guide to understanding, implementing, and navigating AI in pathology with real-world insights and a global lens.Together, we discuss:Why pathologists and computer scientists are often lost in translationHow AI bias, regulation, and ethics are being addressed — globallyWhat it really takes to operationalize AI in patient care todayIf you've ever asked, “Where do I even start with AI in pathology?” — this is your answer.

Send us a textCan AI Grade Cancer Better Than Us? The Truth About T-Cell Imaging, Biomarkers & Digital Pathology DisruptionYou think Saturday mornings are for coffee? Try diving into bone marrow morphology, organ donor kidney biopsies, and AI-driven metastasis detection at sunrise. That's how I do it—and you're invited to join.Welcome to another data-packed episode of DigiPath Digest, where we explore the latest frontier in digital pathology and AI. This time, I reviewed some of the most exciting recent abstracts spanning cancer grading, T-cell quantification, and AI agents in oncology decision-making.These studies aren't just fascinating—they're redefining what's possible in diagnostics, especially in under-resourced areas where digital pathology can create game-changing access and efficiency.

Send us a textAI Pathology & Genomics: A New Benchmark for Predicting Gene MutationsIf you still think visual quantification is “good enough” in pathology, think again. In this 27th episode of DigiPath Digest, I break down four transformative abstracts that show how AI is shifting our diagnostic landscape—from breast cancer segmentation to fibrosis assessment, and all the way to spatial immunology and the evolving immunoscore.If you're still relying on manual scoring, static staging systems, or single-marker immunohistochemistry, this episode will challenge you to look deeper—literally and algorithmically.

Send us a textIf our visual scoring is still based on gut feeling, how do we scale precision? In this week's DigiPath Digest, I explored four new AI-focused papers that could reshape how we diagnose prostate, bladder, gastroesophageal, and endocrine cancers.From automated IHC scoring to predicting urethral recurrence post-cystectomy, these studies highlight the growing value—and responsibility—of integrating AI into our pathology workflows.And yes, I also reveal where to get my histology-inspired earrings

Send us a textIf we don't learn to work with LLMs now, we might end up competing with them.

Send us a textAI in Pathology: ML-Ops and the Future of DiagnosticsWhat if the most advanced AI models we're building today are doomed to die in the machine learning graveyard?

Send us a textCan We Ever Eliminate Bias in AI for Pathology?Every time we think we've trained a “neutral” algorithm, we discover our own fingerprints all over it. Our biases. Unconscious. Systemic. Data-driven. And if we ignore them, AI won't just fail—it will fail patients.Welcome back, my digital pathology trailblazers! In this sixth episode of our 7-part AI in Pathology series, we tackle one of the most uncomfortable yet necessary conversations: Ethics and Bias in AI and Machine Learning. These are not abstract philosophical concerns—they are critical decisions that affect diagnostic accuracy, fairness, and patient safety.We lean heavily on the brilliant work co-authored by Matthew Hanna, Liam Pantanowitz, and Hooman Rashidi, published in Modern Pathology, which you can read here: Ethics and Bias in AI for Pathology.Let's explore where bias creeps in, how we can mitigate it, and what it means to be a responsible data steward in digital pathology.⏱️ Highlights & Timestamps[00:00:00] Welcome back! Kicking off from Pennsylvania at 6:00 AM and reflecting on USCAP highlights, upcoming podcasts, and a pivotal lawsuit on LDTs. [00:03:00] Defining today's topic: Bias in AI—why it matters, and how pathologists are key players in shaping ethical, trustworthy algorithms. [00:05:00] Who are the “data stewards”? A new term you need to own. We explore the role of healthcare professionals in AI development and deployment. [00:07:00] Ethical principles decoded—autonomy, beneficence, non-maleficence, justice, and accountability—and how they translate to AI and ML. [00:11:00] From voting rights to data rights: A surprising analogy from my U.S. citizenship interview about the evolution of fairness. [00:12:00] 12 types of bias explained—from data bias to feedback loops, representation to confirmation bias—with real pathology examples. [00:22:00] Temporal bias and transfer bias: Why yesterday's data may not apply to today's patients. [00:26:00] Walkthrough of the AI lifecycle and how bias seeps in at every stage—from research to regulatory approval. [00:29:00] Clinical trials & guidelines: Learn the difference between STARD-AI, TRIPOD-AI, QUADAS-AI, and CONSORT-AI. [00:33:00] Visual case study: Gleason score distribution by region shows how biased training data leads to misdiagnosis. [00:37:00] Real-world mitigation: I spotlight Digital Diagnostics Foundation and Big Picture Consortium as proactive models for bias reduction. [00:41:00] Why explainability and introspection are more than buzzwords—they are our tools for ensuring accountability. [00:44:00] FAIR data principles—Findability, Accessibility, Interoperability, and Reusability—and why annotations often fall short. [00:48:00] Practical steps: How to build better algorithms with built-in fairness, bias detectors, and responsible data sharing.

Send us a textThe Most Overlooked Risk in AI for Pathology? It's Not What You Think…Welcome, my trailblazing digital pathologists! In this episode, I dive headfirst into the regulatory maze of Artificial Intelligence (AI) in pathology, covering global frameworks, safety risks, ethics, and the future of software as a medical device. While regulation might not be the flashiest part of AI, ignoring it could cost us innovation—or worse, patient safety.We're on Part 5 of our 7-part AI in Pathology series, and this one's vital for anyone developing, using, or simply curious about AI and machine learning tools in healthcare.If you thought regulation was boring, think again—it's what separates a helpful algorithm from a dangerous black box.

Send us a textIn this episode sponsored by Epredia, Dr. Anil Parwani explores the transformative journey of digital pathology from basic slide scanning to AI-driven diagnostics. He shares real-world implementation experiences and demonstrates how these technologies are addressing critical challenges in pathology practice.Pathology faces increasing demands amid workforce shortages and knowledge explosionDigital pathology provides standardization, objectivity, and automation beyond glass slidesOhio State University has scanned 4.2 million slides representing nearly 500,000 cases since 2016Current AI applications include biomarker quantification, rare event detection, and tumor classificationIntegration challenges remain the primary barrier to seamless adoption of AI toolsFuture technologies include virtual staining, 3D pathology, and large language model integrationArtificial intelligence remains task-oriented while real intelligence is context-aware and knowledge-basedEach institution must navigate their own "digital pathology chasm" based on specific needsDigital tools will augment pathologists' capabilities rather than replace human expertiseThe technology marketplace offers solutions for every stage of the digital transformation journeyThis Episode's ResourcesEpredia Digital Pathology WebsiteThis Episode on YouTubeComing soon!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textYou might be using AI models in pathology without even knowing if they're giving you reliable results. Let that sink in for a second—because today, we're fixing that.In this episode, I walk you through the real statistics that power—and sometimes fail—AI in digital pathology. It's episode 4 of our AI series, and we're demystifying the metrics behind both generative and non-generative AI. Why does this matter? Because accuracy isn't enough. And not every model metric tells you the whole story.If you've ever been impressed by a model's "99% accuracy," you need to hear why that might actually be a red flag. I share personal stories (yes, including my early days in Germany when I didn't even know what a "training set" was), and we break down confusing metrics like perplexity, SSIM, FID, and BLEU scores—so you can truly understand what your models are doing and how to evaluate them correctly.Together, we'll uncover how model evaluation works for:Predictive Analytics (non-generative AI)Generative AI (text/image generating models)Regression vs. Classification use casesWhy confusion matrix metrics like sensitivity and specificity still matter—and when they don't.Whether you're a pathologist, a scientist, or someone leading a digital transformation team—you need this knowledge to avoid misleading data, flawed models, and missed opportunities.

Send us a textWhat if I told you the biggest AI breakthroughs in pathology aren't coming from ChatGPT or generative tools—but from the quiet power of predictive analytics and machine learning?In this episode, I explore the non-generative side of artificial intelligence in pathology. These are the tools that detect tumors, segment tissue, classify images, and make predictions—without generating a single word.It's the third chapter in our guided AI series, and this time we focus on the models you're more likely to use in real-world diagnostics. You'll hear about object detection, segmentation, anomaly detection, and how these models are built using supervised and unsupervised learning—plus the pros and cons of different annotation strategies.We'll also cover why no one model fits all, and how combining simple tools like decision trees with more complex neural networks is often the key to building reliable, usable AI in pathology.Whether you're training your first model, selecting an algorithm for rare disease detection, or just want to understand what “unsupervised clustering” means—you'll find something useful here.

Send us a text❗️Is synthetic data trustworthy enough to train AI for patient care? It just might be—and that's what both excites and terrifies me. ❗️Hey trailblazers! In this episode of the Digital Pathology Podcast, I take you through the second part of our AI in Pathology series—this time, we're focusing on generative AI and how it's revolutionizing diagnostics, education, and workflow in our field.From synthetic H&E slides that could pass for real to multimodal agents that can read your histology images and chat with you about them—yes, really—this is where digital pathology meets the “bleeding edge” of AI development.We'll also look at real use cases, a synthetic biobank you can trust, and the biases, hallucinations, and ethical minefields that come along for the ride.

Send us a textGenerative vs. Non-Generative AI in Pathology: Why the Difference MattersIf we don't start defining what kind of AI we're talking about, we risk letting buzzwords replace real science.

Send us a textWill FDA rules disrupt the way we diagnose diseases? In this episode, I break down a seismic shift in lab medicine: a federal court has vacated the FDA's controversial rule classifying lab-developed tests (LDTs) as medical devices. This change carries serious implications for innovation, digital pathology, AI-based diagnostics, and small labs across the U.S.

Send us a textYou think going digital in pathology just means buying a scanner? Think again. In this episode sponsored by Epredia, I sat down with Ryan Davis, Director of Global Business Strategy at Epredia, to talk about what it really takes to implement digital pathology—and why modularity, cytology support, and AI integration are changing the game. Whether you're starting your digital journey or scaling up with advanced tech, there's something in this conversation for you.

Send us a textIn this episode, I talk with Tiffany Chen, MD, and Ben Cahoon from Techcyte about Fusion, their new digital pathology platform. Fusion integrates clinical and anatomic pathology workflows, AI algorithms, and electronic health records—all into one streamlined experience.We explore how Fusion simplifies case management, improves diagnostic accuracy, and brings AI-powered pathology into routine practice. Plus, we discuss the importance of open standards, partnerships with Mayo Clinic, and why flexible integration is key for healthcare innovation.If you're passionate about digital pathology, AI, and advancing patient care, this is a conversation you don't want to miss!✨ Key Highlights- Introduction of Techcyte's Fusion platform: bridging clinical and anatomic pathology workflows- How Fusion integrates AI, EHRs, and LIS systems using open standards (FHIR, DICOM, HL7)- Collaborations with Mayo Clinic and BD for scalable global deployment- AI marketplace support: Fusion enables the integration of internal, partner, and institutional AI models- Impact of AI on cytology workflows and pathology screening- Flexibility for lab-driven or PACS-driven workflows- Future plans: Subspecialty-focused AI enhancements and smart synoptic reporting integration- The importance of interoperability and data standardization for healthcare AIThis Episode's Resources:Techcyte Fusion Platform: https://techcyte.com/fusion/ Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textWhy do so many digital pathology tools stall before they ever reach patients? In this USCAP 2025 special sponsored by Muse Microscopy, I talk with Esther Abels, founder of SolarisRTC, regulatory strategist, and the force behind the first FDA-cleared whole slide imaging system.We break down what startups and established companies must do from day one to succeedbin getting their devices through the FDA. Hint: regulatory strategy isn't a final step—it's your starting line.

Send us a textCan you still call it “digital transformation” if you're scanning slides and still tethered to glass?This special episode, recorded at USCAP and sponsored by MUSE Microscopy, features Dr. Robert Osamura from Japan. We explore how digital pathology is being implemented across Japanese hospitals, how regulations shape adoption, and where AI and tools like MUSE could fit in a geographically complex healthcare system. We also discuss the real-world utility of direct-to-digital tools for intraoperative diagnostics and how AI is changing confidence, not replacing pathologists.

Send us a textWhy are so many pathologists still afraid of going digital? In this USCAP special episode sponsored by Muse Microscopy, I talk with Dr. Sarah Dry, Chair of Pathology and Laboratory Medicine at UCLA, about real-world adoption, AI fear, and how change is best managed when it's people-led.From her early digital research lab in 2007 to pioneering innovative workflows at UCLA today, Dr. Dry knows how direct-to-digital imaging and AI can enhance, not replace, our work.

Send us a textWhy is digital pathology progressing faster in some parts of the world than others? In this international episode sponsored by Muse Microscopy, I sit down with Junya Fukuoka and Norman Zerbe—presidents of the Asian and European Societies of Digital Pathology—to unpack how cultural, regulatory, and infrastructural forces are shaping progress differently across continents.From direct-to-digital tissue imaging considered an alternative to frozen sections in Asia, to legal hurdles in Europe, we discuss what's advancing adoption—and what's still holding it back.

Send us a textAt the last  Pathology Visions 2024, I sat down with Imogen Fitt of Signify Research and Nick Best from Pathology News for a candid, energetic recap of what's really shaping the future of digital pathology.We discuss how two pathologists drove digital pathology adoption in their lab,  the reality behind radiology partnerships, the cautionary tale of AI burnout, and how the Technology Buyer's Guide helps pathologists navigate endless scanner options. From standardization and DICOM to staffing crises, remote workflows, and even Meta glasses—we covered it all.

Send us a text“It used to take 40 minutes, now it takes 15” - this is what Dr. Alae Kawam said about her AI-powered prostate biopsy evaluation workflow.  In this energizing episode of the Digital Pathology Podcast recorded at PathVisions 2024, Dr. Alae Kawam joins me to reflect on where pathology is headed—from AI-assisted prostate diagnostics to direct-to-digital imaging and beyond. Together, we unpack what's working, what still feels clunky, and why standardization, staffing flexibility, and smarter AI are critical to the next phase of pathology adoption.

Send us a textWhat does it take to build a digital pathology movement across the most diverse region on Earth?In this episode of the Digital Pathology Podcast, I'm joined by Dr. Junya Fukuoka, practicing pathologist, educator, and founder of the Asian Society of Digital Pathology (ASDP). From Japan to India, Saudi Arabia to South Korea, Asia's digital pathology adoption is growing rapidly—and Dr. Fukuoka is helping lead the charge.We talk about why digital access, multilingual support, and patient advocacy are central to pathology adoption across Asia's diverse regions. We also explore what it means to “skip” a step in tech, and why static images and direct-to-digital imaging may be Asia's most powerful tools.

Send us a textIn this episode, I'm joined by Dr. Hamid Tizhoosh, professor of biomedical informatics at the Mayo Clinic, to unravel what's truly holding back AI in healthcare, especially pathology. From the myths of general-purpose foundation models to the missing link of data availability, this conversation explores the technical and ethical realities of deploying AI that's accurate, consistent, lean, fast, and robust.

Send us a textIn this episode of the Digital Pathology Podcast, I sit down with Dr. Yuri Nikiforov, founder of the World Tumor Registry, to explore how this global, open-access whole slide image platform contributes to cancer diagnostics, education, and research.We talk about how the registry allows pathologists, researchers, and patients to view curated whole-slide images from around the world, starting with thyroid tumors and expanding into other cancers like breast and lung. Learn how AI, molecular diagnostics, and editorial curation come together to build a truly global pathology tool that's free for everyone, forever.

Send us a textIn this episode of the Digital Pathology Podcast, I explore the ethical and bias considerations in AI and machine learning through the lens of pathology. This is part six of our special seven-part series based on the landmark Modern Pathology review co-authored by the UPMC group, including Matthew Hanna, Liam Pantanowitz, and Hooman Rashidi.From data bias and algorithmic bias to labeling, sampling, and representation issues, I break down where biases in AI can arise—and what we, as medical data stewards, must do to recognize, mitigate, and avoid them.

Send us a textUSCAP 2025 Daily Update – Day 4 with Dr. Aleksandra ZurawIt's the final day of USCAP 2025, and in this episode of the Digital Pathology Podcast, I'm sharing personal moments, spontaneous tech wins (and fails), and meaningful conversations with some of the most forward-thinking voices in digital pathology.From running around with mics and misplaced tripods to interviewing Dr. Dry and Dr. Ozumura, this episode captures both the spirit of innovation and the real-world challenges of advancing digital workflows—especially in environments where regulations still lag behind.

Send us a textUSCAP 2025 Daily Update – Day 3 Recap with Dr. Aleksandra ZurawIn this episode of the Digital Pathology Podcast, I bring you Day 3 insights live from USCAP 2025—from moderating the MUSE panel on slide-free imaging to exploring regulatory strategies, tech innovations, and collaborations across the digital pathology community.Get an inside look at how direct-to-digital pathology is transforming workflows, how companies like Techcyte are streamlining AI applications, and why regulatory strategy is as crucial as your scanning tech.

Send us a textUSCAP 2025 Daily Update – Day 2 with Dr. Aleksandra ZurawWelcome back to the Digital Pathology Podcast live from USCAP 2025! On Day 2, I dive into the momentum building across the conference—covering major trends, tech insights, and how digital pathology is no longer just a topic, but a critical tool used to deliver sessions and share knowledge.From vendor-driven presentations to real-world applications of AI and slide-free technology, this episode explores how digital workflows are being integrated into education, diagnostics, and collaboration on a global scale.

Send us a textUSCAP 2025 Daily Update – Day 1 Highlights from Dr. Aleksandra ZurawWelcome to the first live daily update from USCAP 2025, recorded straight from the conference floor by Dr. Aleksandra Zuraw, your host at Digital Pathology Place. In this episode, Aleks shares behind-the-scenes moments, exciting vendor previews, and key updates as the world's largest pathology meeting kicks off.

Send us a textIn this episode of the Digital Pathology Podcast, I sit down with Matthew Nuñez, CEO of MUSE Microscopy, to discuss the groundbreaking advancements in direct-to-digital imaging in pathology. Traditional pathology workflows rely on glass slides, formalin fixation, and time-consuming processing steps. But what if we could skip the slide entirely and go straight to digital?

Send us a textHow Can Digital Pathology Workflows Stay Compliant and Efficient?In this episode of the Digital Pathology Podcast, I sit down with Scott Randall, Senior Application Specialist at Hamamatsu (Hamamatsu NanoZoomer), and Amanda Coble, Senior Director of Product for Proscia (Proscia's Website), to discuss the critical role of compliance, interoperability, and efficiency in digital pathology workflows.

Send us a textWhat if we could skip glass slides altogether and go straight from fresh tissue to digital image? Muse Microscopy's SmartPath device aims to do just that, capturing diagnostic-quality images directly from fresh tissue. In this episode brought to you by Muse Microscopy, I sit down with Dr. Rao and Dr. Edwards to discuss the insights, challenges, and future of this groundbreaking technology. We explore its regulatory ramifications, change management in veterinary and human pathology, and financial feasibility. Tune in to learn why SmartPath could be a game-changer for both pathologists and patients.00:00 Introduction to SmartPath Technology00:54 Meet the Experts: Dr. Rao and Dr. Edwards01:08 FDA Approval and Implementation Plans01:35 Change Management in Pathology01:56 Training Pathologists for SmartPath03:48 Translational Tissue Banking and Clinical Applications04:29 Impact on Breast Pathology05:49 Pathologists' Reception and Adoption14:33 Financial Viability and ROI19:44 Conclusion and Future ProspectsLinks and Resources:This episode on YouTubeMuse Microscopy WebsiteSmartPath Device Demo VideoSupport the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textTransforming Pathology: A Deep Dive into the Muse SystemThis 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 Pathology00:18 The Hurdle of Digitizing Analog Pathology00:26 Direct to Digital Pathology: A Game Changer01:46 Introduction to Muse Microscopy02:32 How Direct to Digital Pathology Works03:10 Advantages of Direct to Digital Pathology04:13 Understanding Muse Technology05:26 The Digital Pathology Workflow with Muse14:15 Challenges and Misconceptions15:38 The Future of Pathology16:31 Frequently Asked Questions18:07 Conclusion and Additional Resources18:54 Behind the Scenes and Final ThoughtsLinks and Resources:Original blog post on Digital Pathology Place  Website and LinkedInYouTube playlist with more information about MUSESmartPath Product presentation from CAP 2024Video showing the SmartPath device at the conference boothUSCAP in Boston - Muse Microscopy booth #528Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textIn 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.

Send us a textIn 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.

Send us a textIn 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.

Send us a textWelcome 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:Subscribe to Digital Pathology Podcast on YouTubeFree E-book "Pathology 101"YouTube (unedited) version of this episodeTry Perplexity with my referral linkMy new page built with PerplexityHistoColAI Github PagePublications Discussed Today:

Send us a textIn 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. IYou 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 Digest00:53 Introduction and New Year Greetings01:41 Diving into DigiPath Digest01:44 AI in Respiratory Cytology06:11 The Role of AI in Pathology09:49 Multi-Omics and AI11:28 Radiomics and Pathomics14:44 Live Q&A and Future Plans20:09 Prostate Cancer Tsunami22:34 Thyroid Cytology and Live AI-Assistant demo31:07 Conclusion and the option to send texts :)Links and Resources:Subscribe to Digital Pathology Podcast on YouTubeFree E-book "Pathology 101"YouTube (unedited) version of this episodeTry Perplexity with my referral linkMy new page built with PerplexityPublications Discussed Today:

Send us a textIn 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!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textLeveraging AI for Deep Insights into Tertiary Lymphoid Structures in Colorectal CancerIn 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 Introduction00:45 Introducing the New AI Tool: Notebook LM by Google01:11 Experimental Series: "Aleks + AI"02:06 Deep Dive into Tertiary Lymphoid Structures (TLS)03:18 Understanding TLS and Their Role in Colorectal Cancer04:20 Quantification Methods and Key Findings05:02 Implications for Personalized Medicine09:02 AI in TLS Analysis and Future Prospects11:00 CMS Classification and TLS Density12:08 Study Limitations and Future Directions15:40 Final Thoughts and Wrap-Up16:28 Feedback and Future PlansTHIS EPISODE'S RESOURCES116: DigiPath Digest #18 | Federated Learning in Pathology. Developing AI Models While Preserving PrivacyPUBLICATION DISCUSSED TODAY

Send us a textIn 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 Greetings00:18 Today's Topic: Federated Learning00:57 AI Tools and Updates04:39 Federated Learning in Detail08:03 Challenges and Benefits of Federated Learning11:21 Exploring More Papers and Future Plans22:53 Wrapping Up and Final ThoughtsLinks and Resources:Subscribe to Digital Pathology Podcast on YouTubeFree E-book "Pathology 101"YouTube (unedited) version of this episodeTry Perplexity with my referral linkMy new page built with PerplexityPublications Discussed Today:

Send us a textThis 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 TodayDiscussing the pathologist shortage, delayed diagnoses, and how AI can address these issues.[00:03:00] A Pathologist's Dual PerspectiveDr. 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 PathologyInsights into how clinician-centric AI tools like Aiforia are designed to improve diagnostic workflows and outcomes.[00:14:00] Addressing Challenges in AI IntegrationStrategies for overcoming hurdles like algorithm aversion, skill retention, and fostering trust in AI systems.[00:22:00] Preparing Future PathologistsThe importance of incorporating AI training into residency programs and creating a digitally savvy workforce.[00:44:00] How to Implement AI EffectivelyPractical 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 101Contact Dr. Richard Doughty: richard.doughty@aiforia.comWatch more videos created together with Aiforia: VIDEO PLAYLISTThis episode is supported by Aiforia Technologies, leaders in AI-powered solutions for digital pathology.Do you know someone who should listen to this episode? Share it with them!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textIn this episode, I sit down with Dr. Nina Kottler, Associate Chief Medical Officer of Clinical AI at Radiology Partners, to dive into the evolving role of AI in radiology and how it can shape the future of digital pathology. Dr. Kottler shares her unique journey, expertise, and practical frameworks for implementing AI that enhance patient care and streamline diagnostic workflows.Episode Highlights and Key Moments:[00:00:45] Introduction to Dr. Nina KottlerDr. Kottler discusses her background in applied mathematics, her journey into medicine, and her work at Radiology Partners, where she combines clinical practice with AI innovation.[00:04:30] Breaking Down Complex Problems in AINina explains her approach to tackling large clinical challenges by breaking them down into manageable parts, a method that's essential for developing and optimizing AI solutions.[00:08:15] The Role of Data OrchestrationWe dig into “data orchestration” and how ensuring data is aligned with the right AI model is key to producing accurate and reliable clinical outcomes.[00:11:45] Life Cycle of an Exam in RadiologyNina takes us through each step in the radiology workflow—from the initial patient consultation to reporting—and highlights how AI can streamline and enhance each phase.[00:17:00] Evolution of AI Models in HealthcareWe explore how AI has evolved, from early CAD systems to today's multimodal and transformer models, and the exciting possibilities they bring to both radiology and pathology.[00:23:20] Addressing the Lag in AI Adoption in HealthcareWe discuss the challenge of keeping up with AI advancements while balancing patient safety, regulatory standards, and the need for reliability in clinical settings.[00:27:50] Frameworks for Reducing Variability and Improving AccuracyNina shares actionable frameworks that Radiology Partners uses to reduce variability and improve diagnostic precision—strategies that pathology can learn from.[00:32:40] AI in Workflow Optimization: Where It Has Real ImpactWe discuss specific use cases in clinical workflows that show where AI can bring the greatest value, especially in enhancing patient care through optimized processes.[00:36:50] The Power of Multimodal AI and Vision-Language ModelsCombining large language models with computer vision is moving diagnostics closer to comprehensive, AI-driven care—a promising development we explore in depth.[00:42:15] The Future of Agents in AIWe dive into the concept of “agents” in AI and how these systems may soon coordinate multiple models for more complex and precise clinical analyses.[00:48:10] Where to Learn More about Dr. Nina Kottler's WorkNina shares where you can catch her upcoming talks and presentations, plus resources for staying updated on the latest in AI for radiology and digital pathology.If you're a pathologist, radiologist, or healthcare professional curious about AI's impact on diagnostics, this episode is packed with practical guidance on integrating AI into clinical workflows. Join us as we explore how AI is shaping the future of radiology and pathology!Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textWelcome back to the DigiPath Digest, fresh from PathVision! In this episode we will dive into the latest updates from the PathVision conference, covering trends in AI-driven diagnostics, the expansion of digital pathology into primary care, and the exciting new frontier of glassless pathology.Join me as I recap the highlights of PathVision and the latest updates from the digital pathology literature, including discussions on:AI Integration in Pathology: Learn how AI is advancing breast cancer diagnostics with tools like Ki-67 scoring models and multi-label AI for mammography, aimed at reducing unnecessary biopsies.Global Health & Digital Microscopy: Hear about innovative projects from Sweden and Finland focused on AI-supported digital microscopy in primary healthcare labs, bringing accessible diagnostics to underserved areas.Glassless Pathology with MUSE: Discover how glassless pathology is changing tissue imaging with MUSE (Microscopy with UV Surface Excitation), enabling diagnostics without the need for traditional glass slides. Dr. Zuraw breaks down what this means for future pathology workflows.Plus, a shout-out to the vendors and partners making these advancements possible, and insights from Dr. Zuraw's conversations with digital pathology trailblazers from around the globe, including new developments from Asia in digital pathology education and technology.Timestamps:[0:00] PathVision Highlights & Global Attendees[5:15] AI in Diagnostic Workflows: Dr. Anil Parwani's “Pathology Train Ride”[12:30] Moving Beyond Narrow AI: Multimodal and Foundational Models[18:45] Glassless Pathology: A New Frontier with MUSE Microscopy[25:10] Integrating Digital Microscopy in Global Health Labs[32:00] Breast Cancer Month: New Advances in AI for Diagnostics[42:00] One Health & AI for Disease Detection in Primary Care[48:30] Special Interviews: Jun Fukuoka and Asian Society of Digital PathologyLinks and Resources:Subscribe to Digital Pathology Podcast on YouTubePathology News Signify Research Monthly RecapYouTube version of this episodePublications Discussed Today:

Send us a textIn this episode, I meet with Adam Cole, MD, and Jason Camilletti about how digital pathology transforms the field. Adam, the CEO of TruCore Pathology, and Jason, the CEO of PathNet Labs, share their unique journeys from the military to becoming digital pathology leaders. We explore their experiences, challenges, and innovations in integrating AI and digital tools into their practices.Key Topics Discussed:[00:00:00] Introduction to AI in Pathology[00:01:00] Adam and Jason's Military Backgrounds[00:05:00] Adam's Story of Becoming a Mobile Pathologist[00:10:00] The Move to Fully Digital Pathology[00:14:30] AI's Role in Pathology[00:20:00] Challenges in Implementing Digital Pathology[00:25:00] Improving Patient Outcomes with Digital Tools[00:29:00] Digital Pathology's Impact on Patient Care[00:38:00] Using AI for Quantifying Tumor Volume[00:40:00] The Role of AI in Enhancing DiagnosticsAdam and Jason emphasize the immense potential of AI in pathology, but also the need for thoughtful integration. The future of pathology lies in using digital tools to provide faster, more accurate diagnoses while maintaining the critical human element. Tune in to learn how AI is reshaping the field and what it means for both pathologists and patients.THIS EPISODE'S RESOURCES:TruCore websitePathNet WebsiteOTHER EPISODES YOU MIGHT LIKE:The Evolution of Digital Pathology – from Improved Histology Quality to Fair Use of Pathology Data w/ Matthew O. Leavitt, DDx FoundationAchieving work-life balance in medicine as a pathologist with digital pathology w/ Todd Randolph, MD Support the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textWhat does the FDA jurisdiction for LDTs mean for the labs? Do they need to worry? How do they need to change the way they operate?In this episode, I talk with Dr. Thomas Nifong, a clinical pathologist and VP of CDX operations at Acrovan Therapeutics, about the recent FDA ruling on laboratory-developed tests (LDTs) issued on May 6th, 2024. We discuss the implications of considering LDTs as medical devices, requiring regulation, and explore the authority of FDA versus CLIA. The conversation also covers historical contexts, practical implications of regulatory changes, and the roles of organizations like CAP, ACLA, and AMP in legal challenges against the FDA. We dive into the differences in requirements between CLIA and FDA, New York's alternative approval route, and potential impacts on lab operations and compliance. Join us for an insightful conversation filled with essential information for those in the field of molecular pathology.00:00 Introduction and Special Guest Announcement00:24 FDA's New Rule on Laboratory Developed Tests (LDTs)01:58 Recording the Podcast: A Casual Lunch Conversation03:47 Understanding FDA's Authority Over Medical Devices08:07 Disputes and Legal Challenges12:03 Practical Implications and Industry Reactions12:47 Understanding FDA's Focus: Safety and Efficacy14:11 The Role of CMS and Medical Necessity14:48 Congressional Involvement and Legal Authority16:06 Impact on Labs and Future LDTs18:33 Quality Systems and Compliance20:16 Modifications and Software Updates21:16 Conclusion and Next StepsSupport the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!

Send us a textIn this episode, I had a fascinating conversation with Candice Chu, DVM, PhD, DACVP, about how artificial intelligence (AI) is reshaping veterinary diagnostics and education. Candice, a clinical pathologist and educator at Texas A&M, is using AI tools like ChatGPT to improve efficiency in clinical workflows and academic processes. We explored the practical applications of AI, ethical concerns, and its future impact on veterinary medicine.Key Topics Discussed:[00:00:00] Introduction to AI in Veterinary Education and DiagnosticsI ask Candice how AI is changing veterinary education and diagnostics, and she explains how AI is boosting efficiency in both areas.[00:01:00] Candice's Journey in Veterinary MedicineCandice shares her journey from Taiwan to the U.S., her career in veterinary pathology, and becoming an educator at Texas A&M.[00:05:00] Custom GPT Model for Clinical PathologyCandice describes the development of her custom GPT model for clinical pathology and its role in improving diagnostic efficiency.[00:10:00] AI Tools for Academic and Clinical EfficiencyWe talk about how AI tools reduce repetitive tasks, giving professionals more time for critical thinking and decision-making.[00:14:30] Ethical Concerns When Using AI in Veterinary MedicineCandice emphasizes the ethical responsibility of using AI, highlighting the importance of human judgment in AI-assisted diagnostics.[00:20:00] How Veterinary Students Can Leverage AICandice shares tips on how students can use AI to enhance learning, from simplifying research to generating case questions.[00:29:00] AI's Role in Academic Writing and Veterinary PracticeWe discuss how AI tools streamline academic writing and research, and how AI will continue shaping veterinary practice in the future.[00:39:00] Critical Thinking and AI in Veterinary MedicineCandice and I conclude by discussing how critical thinking and professional responsibility are essential when using AI tools.Candice highlighted the transformative role AI can play in both veterinary education and diagnostics, improving efficiency while requiring responsible use. While AI tools like ChatGPT offer many benefits, the human element—our critical thinking and judgment—remains crucial in ensuring accurate results and ethical practices.This episode provides practical insights on how veterinary professionals, educators, and students can harness AI to streamline workflows and improve diagnostic accuracy. Be sure to listen to the full conversation for actionable tips on integrating AI into your practice!EPISODE RESOURCES:About Dr. Candice Chu (Including her social media and achievements)Candice's PaperUndermind AIYoutube Episode of this EpisodeSupport the showBecome a Digital Pathology Trailblazer get the "Digital Pathology 101" FREE E-book and join us!