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What 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 Announcement
00:24 FDA's New Rule on Laboratory Developed Tests (LDTs)
01:58 Recording the Podcast: A Casual Lunch Conversation
03:47 Understanding FDA's Authority Over Medical Devices
08:07 Disputes and Legal Challenges
12:03 Practical Implications and Industry Reactions
12:47 Understanding FDA's Focus: Safety and Efficacy
14:11 The Role of CMS and Medical Necessity
14:48 Congressional Involvement and Legal Authority
16:06 Impact on Labs and Future LDTs
18:33 Quality Systems and Compliance
20:16 Modifications and Software Updates
21:16 Conclusion and Next Steps

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In 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 Diagnostics
  I 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 Medicine
  Candice 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 Pathology
  Candice 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 Efficiency
  We 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 Medicine
  Candice 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 AI
  Candice 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 Practice
  We 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 Medicine
  Candice 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 Paper
• Undermind AI
• Youtube Episode of this Episode

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In this episode, Dr. Richard Fox shares how AI is transforming veterinary diagnostics. From his early career to the world of AI, Dr. Fox offers practical insights into the challenges, opportunities, and innovations that AI brings to pathology. Tune in to learn how AI is enhancing workflow efficiency, diagnostic precision, and the future direction of veterinary pathology.

[00:00] Introduction – Introduction to Dr. Richard Fox and his expertise in veterinary pathology and AI.

[03:00] Dr. Fox’s Career Journey – His shift from veterinary practice to pathology and AI.

[08:00] Entering the AI Space – How Dr. Fox became involved in AI, including his work with Aiforia.

[15:00] AI in Diagnostics – AI’s impact on diagnostic workflows and speeding up tasks.

[22:00] Quality Control in AI Models – Ensuring AI model accuracy and the importance of data consistency.

[28:00] AI Model Validation Challenges – Overcoming issues with model validation and retraining.

[35:00] Integrating AI into Workflows – How AI fits into veterinary pathology workflows and practical considerations.

[40:00] Future of AI in Pathology – Predictions on the future trends in AI and on-premises diagnostics.

[50:00] Common Questions About AI – Addressing concerns like AI replacing pathologists and optimizing workflows.

[58:00] Conclusion – Key takeaways and how to get started with AI in veterinary diagnostics.

The Episodes Resources:
Contact Aiforia
Richard Fox's LinkedIn Profile
Richard Fox's Email

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In this 14th episode of DigiPath Digest, I introduce a new course on AI in pathology, designed to help pathologists understand and confidently navigate AI technologies.

The episode focuses on various research studies that highlight the integration and effectiveness of AI in pathology, particularly in colorectal biopsies and kidney transplant biopsies, emphasizing the importance of seamless workflow integration.

You will also learn about challenges in manual assessment of tumor-infiltrating lymphocytes and HER2 expression in breast cancer. I advocate for more consistent and precise AI-driven approaches.

And there an opportunity for a discounted beta test of the new AI course.

00:00 Welcome to DigiPath Digest #14

00:24 New AI Course Announcement

01:51 Deep Learning in Colorectal Biopsies

09:17 AI in Kidney Biopsy Evaluation

16:12 Automated Scoring of Tumor Infiltrating Lymphocytes

24:22 AI for HER2 Expression in Breast Cancer

31:13 Conclusion and Course Details

THIS EPISODE'S RESOURCES

📰 A deep learning approach to case prioritisation of colorectal biopsies
🔗 https://pubmed.ncbi.nlm.nih.gov/39360579/


📰 Galileo-an Artificial Intelligence tool for evaluating pre-implantation kidney biopsies
🔗 https://pubmed.ncbi.nlm.nih.gov/39356416/


📰 Automated scoring methods for quantitative interpretation of Tumour infiltrating lymphocytes (TILs) in breast cancer: a systematic review
🔗 https://pubmed.ncbi.nlm.nih.gov/39350098/


📰 Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer
🔗 https://pubmed.ncbi.nlm.nih.gov/39350085/


▶️ YouTube Version of this Episode:
🔗 https://www.youtube.com/live/jkT8dTxelt4?si=xT6MNH7O4HuUnAN6

📕 Digital Pathology 101 E-book
🔗https://digitalpathology.club/digital-pathology-beginners-guide-notification

🤖 "Pathology's AI Makeover" Online Course 50% OFF
🔗 Let me know that you are interested in LinkedIn (just 10 spots available)

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Good morning, digital pathology trailblazers! Welcome to another exciting exploration of digital pathology and AI. I’m thrilled to have our global community here with us today from so many different time zones. Before we dive into today's content, a quick note: my equipment is being a bit finicky, but that’s life in the digital world!

Integrating Image Analysis with AI

Let's kick off with a recap of some recent updates. Yesterday, I had the privilege of presenting to a mixed group at Cincinnati Children’s Hospital. We discussed AI in image analysis, an essential tool bridging radiology and pathology as these fields rapidly evolve with new technologies like foundation models and large language models. A diverse audience—ranging from radiologists to pathologists—prompted me to adapt my presentation style on the spot. It was a dynamic discussion about the advancements in healthcare that shared perspectives from both sides.

Lymphovascular Invasion: A Case Study

Our first paper today focuses on a deep learning model for identifying lymphovascular invasion (LVI) in lung adenocarcinoma. This significant prognostic factor is crucial for advancing diagnostic consistency and reliability. Unlike broad foundation models, this work engages with dedicated image analysis applications targeting specific diagnostic challenges. The study demonstrated reduced pathologist evaluation time by nearly 17% and even more in complex cases, aligning with previous findings that AI enhances efficiency by around 21%.

AI Collaborations: Human and Veterinary Pathology

Next, we delve into a collaborative effort between human and veterinary pathologists, emphasizing the promise of AI integration in telepathology and digital pathology. These fields are converging to enhance information exchange, teaching, and research. I’m particularly excited about this paper due to my own veterinary pathology background and the potential it offers for both educational and clinical practices.

Spatial Profiling and Immuno-Oncology

We then journey into the intricate landscape of immuno-oncology with a study on PD-1 and PD-L1 in osteosarcoma microenvironments. Utilizing deep learning and multiplex fluorescence immunohistochemistry, researchers highlighted the spatial orchestration of these markers, providing insights into potential immunotherapeutic strategies. This work is an exemplar of how AI can illuminate complex biological landscapes, offering a path for future therapies.

Conclusion

Thank you all for joining this vibrant discussion. Whether you’re tuning in from early morning in Atlanta or late at night in Algeria, your engagement enriches our learning experience. Keep an eye out for more content and upcoming courses designed to unpack these groundbreaking developments in AI and digital pathology.

Until next time, keep blazing trails in digital pathology!

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The episode explores the concept of blind review, a process designed to eliminate hindsight bias by allowing medical experts to evaluate cases without knowing the outcome or the hiring party.

Stephanie Franckewitz, JD, MBA, founder of Blind Review, discusses its application in legal cases, particularly for digital pathology and radiology. By providing an unbiased expert opinion, blind review aids the defense and plaintiff parties in court, increasing the chances of a favorable verdict.

Stephanie outlines her journey from a medical malpractice defense lawyer to starting Blind Review and highlights the potential for digital pathology to revolutionize the legal process, reduce bias, and improve case outcomes.

Collaboration with platforms like PathPresenter enables pathology slides to be reviewed efficiently and effectively within a legal context. This approach benefits both defendants and plaintiffs by ensuring objective evaluations and enhancing the credibility of expert testimonies in trials.

00:00 Introduction to Blind Review
01:19 The Role of Digital Pathology in Legal Cases
02:16 Stephanie Franke Reid's Journey
07:19 Challenges in Traditional Expert Reviews
10:09 Implementing Blind Review in Pathology
18:16 Collaboration with PathPresenter
25:43 Streamlining the Legal Process with Digital Pathology
26:51 Collaborative Tools for Legal Experts
27:20 Path Presenter: A Game Changer for Attorneys
28:17 Understanding Pathology for Juries
29:20 Streamlining Case Preparation with Path Presenter
31:54 Setting Up a Blind Review Process
35:38 The Gold Standard of Blind Review
41:53 Impact of Blind Review on Legal Outcomes
49:49 Empowering Legal and Medical Professionals
54:50 Conclusion and Call to Action - contact Stephanie

THIS EPISODE'S RESOURCES

• Stephanie's LinkedIn Profile
• The Blind Review Website

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In this episode, I celebrate another milestone of the Digital Pathology Place YouTube channel that was achieved thanks to you, my digital pathology trailblazer, reflecting on its journey since its inception in 2019.

I delve into the developments in digital pathology, focusing on the first video I ever published on YouTube about AI in pathology, highlighting trends, tools, and challenges in the field.

The video was based on a presentation I gave on the day I got engaged, so if you want to know the whole story listen in.

I explain key concepts like
- artificial intelligence,
- machine learning, and
- deep learning, and discuss
- How could AI eventually support pathology practice despite current challenges?

00:00 Welcome and AI Co-Host Feedback
00:19 YouTube Monetization Milestone
01:18 Reflecting on the First Video
02:47 Special Day and Personal Story
05:06 Introduction to AI in Pathology
07:26 AI Terminology and Concepts
13:17 Current Status of AI in Pathology
17:33 Challenges and Future of AI in Pathology
22:42 Conclusion and Call to Action
23:30 Updates and Future Plans

THIS EPISODE'S RESOURCES

• The YouTube version of "AI in Pathology" first video
• The updated "Artificial Intelligence in Pathology" video (coming soon in podcast version)

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In this episode of DigiPath Digest you will learn about the development of AI models for glaucoma screening using fundus images, the use of AI in detecting metastatic deposits in colorectal cancer, and leveraging immunofluorescence data to reduce pathologist annotation requirements.

Dr. Aleks also invited two AI Co-hosts and shared personal reflections on AI's role in the industry and invites feedback from listeners on AI-generated content.

00:00 Introduction to the Livestream Disaster
00:24 AI to the Rescue: Enhancing Audio Quality
00:38 Meet the AI Co-Hosts
01:04 Welcome to the Digital Pathology Podcast
01:30 Technical Difficulties and Audience Interaction
02:49 Exploring AI in Veterinary Medicine
04:34 Hybrid Convolutional Neural Network for Glaucoma Screening
07:49 Model for Detecting Metastatic Deposits in Lymph Nodes
11:23 Leveraging Immunofluorescence Data for Lung Tumor Segmentation
18:05 AI-Generated Content and Future Plans
21:37 AI Co-Hosts Take Over
32:42 Conclusion and Audience Feedback

TODAY'S EPISODES RESOURCES
📰 Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images
🔗https://pubmed.ncbi.nlm.nih.gov/39301801/

📰 Automatic segmentation of esophageal cancer, metastatic lymph nodes and their adjacent structures in CTA images based on the UperNet Swin network
🔗https://pubmed.ncbi.nlm.nih.gov/39300922/

📰 Retrosynthetic analysis via deep learning to improve pilomatricoma diagnoses
🔗https://pubmed.ncbi.nlm.nih.gov/39298885/

📰 Obesity-Associated Breast Cancer: Analysis of Risk Factors and Current Clinical Evaluation
🔗 https://pubmed.ncbi.nlm.nih.gov/39287872/

📰 Model for detecting metastatic deposits in lymph nodes of colorectal carcinoma on digital/ non-WSI images
🔗 https://pubmed.ncbi.nlm.nih.gov/39285483/

📰 Leveraging immuno-fluorescence data to reduce pathologist annotation requirements in lung tumor segmentation using deep learning
🔗 https://pubmed.ncbi.nlm.nih.gov/39284813/

📰 Bayesian Landmark-based Shape Analysis of Tumor Pathology Images
🔗 https://pubmed.ncbi.nlm.nih.gov/39280355/

📰 Globalization of a telepathology network with artificial intelligence applications in Colombia: The GLORIA program study protocol
🔗 https://pubmed.ncbi.nlm.nih.gov/39280257/

📰 Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy
🔗 https://pubmed.ncbi.nlm.nih.gov/39277586/

📰 Sex differences in sociodemographic, clinical, and laboratory variables in childhood asthma: A birth cohort study
🔗 https://pubmed.ncbi.nlm.nih.gov/39019434/

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