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Today my guest is Danielle Brown, a fellow veterinary pathologist, the General Manager at Charles River Laboratories Reno, Nevada, and a pioneer in the use of image analysis for toxicologic pathology. Together, we explored the ever-evolving role of image analysis in preclinical studies and how it enhances, rather than replaces, the expertise of pathologists.

This conversation is a deep dive into the intersection of pathology and technology, showcasing how image analysis is revolutionizing preclinical research. We also discuss the future of this technology and its implications for the industry.

Join us as we navigate the intricacies of image analysis, share insights on the collaborative process between pathologists and image analysis scientists, and look ahead to the exciting advancements on the horizon.

Key Discussion Points:

• [00:00:00] Introduction and Guest Welcome:
  • Introducing Danielle Brown and her significant contributions to the field of toxicologic pathology.
• [00:02:46] The Role of Image Analysis in Preclinical Drug Development:
  • Why image analysis is crucial for accurate and efficient evaluations in preclinical studies.
• [00:03:23] Challenges and Limitations of Visual Analysis:
  • Discussing the limitations of visual analysis and how image analysis overcomes these challenges.
• [00:08:06] Pathologist and Image Analysis Collaboration:
  • The importance of collaboration between pathologists and image analysis scientists to ensure accurate data interpretation.
• [00:13:00] Efficiency and Cost of Image Analysis vs. Pathologist Scoring:
  • Comparing the efficiency, cost, and consistency between image analysis and traditional pathologist scoring methods.
• [00:15:18] Validation and Qualification of Image Analysis Algorithms:
  • The process of validating image analysis algorithms to ensure they meet regulatory standards in a GLP environment.
• [00:19:54] GLP Compliance and Regulatory Considerations:
  • How Charles River ensures GLP compliance in their image analysis processes, making them suitable for regulatory submissions.
• [00:23:27] Method Development for Specific Stains and Techniques:
  • Approaching projects that require new method development or specialized procedures.
• [00:27:46] Future of Image Analysis in Pathology:
  • Danielle’s insights into the future of image analysis and how emerging technologies will shape the field.

This episode is packed with valuable insights and practical advice for anyone involved in preclinical research or interested in the integration of image analysis in pathology. Danielle’s expertise and our discussion provide a roadmap for leveraging image analysis to increase evaluation efficiency and the granularity of your data.

THIS EPISODE'S RESOURCES:

📄 The paper Aleks and Danielle co-authored: "Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology"

📄 Learn more about GLP-compliant tissue image analysis at Charles River Laboratories.

▶️ Watch the full episode here: Image Analysis Enhances Pathology Evaluation of Preclinical Studies, not Replaces it.

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In this episode, we celebrate the 100th edition of the Digital Pathology Podcast!
Thank you so much for being part of this journey!
You are my Digital Pathology Trailblazers and I prepared a Digital Pathology Trailblazer manifesto for us!

This is the 9th edition of DigiPath Digest, and we are attracting more and more people to this series.

I am also working on a new YouTube digital pathology course and am offering the first 100 enrollments for free in exchange for feedback.

During today's episode, we cover several papers including research on AI for predicting post-operative liver metastasis, validation of AI-based breast cancer risk stratification models, AI applications in clinical microbiology, advances in parasitology diagnostics, AI for retinal assessment, and AI models for detecting microsatellite instability in colorectal cancer.

We also unveil a Digital Pathology Trailblazer manifesto emphasizing the ethos and dedication of the community.

Join us to stay current with literature, advancements, and insights from the fascinating world of digital pathology.

00:00 Introduction and Announcements
00:25 Live Podcast Proposal
01:40 Welcome and Audience Interaction
03:05 Updates and Apologies
06:11 YouTube Course Announcement
07:23 Technical Difficulties and Solutions
10:00 Digital Pathology Club and Vendor Sessions
11:28 First Research Paper Discussion
17:38 Second Research Paper Discussion
20:07 ER Positive and HER2 Negative Patient Subgroup Analysis
20:59 Independent Prognostic Value of StratiPath Breast Solution
21:59 Challenges and Benefits of Image-Based Stratification
22:58 Technical Difficulties and Live Stream Interaction
24:22 Introduction to Paper Number Three: AI in Clinical Microbiology
28:07 AI in Parasitology Screening and Diagnosis
29:30 Physics-Informed AI for Retinal Assessment
33:08 AI for Microsatellite Instability Detection in Colorectal Cancer
36:42 YouTube Course Announcement and Digital Pathology Trailblazer Manifesto
42:25 Celebrating the 100th Episode of the Digital Pathology Podcast

THE ABSTRACTS WE COVERED TODAY

📄 A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics.
https://pubmed.ncbi.nlm.nih.gov/39143624/

📄 Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images
https://pubmed.ncbi.nlm.nih.gov/39143539/

📄 Potential roles for artificial intelligence in clinical microbiology from improved diagnostic accuracy to solving the staffing crisis
https://pubmed.ncbi.nlm.nih.gov/39136261/

📄No longer stuck in the past: new advances in artificial intelligence and molecular assays for parasitology screening and diagnosis
https://pubmed.ncbi.nlm.nih.gov/39133581/

📄Physics-informed deep generative learning for quantitative assessment of the retina
https://pubmed.ncbi.nlm.nih.gov/39127778/

📄Artificial Intelligence Models for the Detection of Microsatellite Instability from Whole-Slide Imaging of Colorectal Cancer
https://pubmed.ncbi.nlm.nih.gov/39125481/

▶️ YouTube Version of this Episode
https://www.youtube.com/live/Uwca5rzAtEA?si=Rd8r4LVM1utEKWdt

Support the Show.

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

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In this episode of DigiPath Digest, broadcasting from Poland, we delve into advances in digital pathology, including AI applications in bone marrow evaluation, classification of hematology cells, and the use of synthetic images for data augmentation. Additionally, we review a survey on pathologists' perceptions of ChatGPT and consider the feasibility of GANs for enhancing medical image analysis.

00:00 Welcome and Troubleshooting from Poland
00:21 Live Stream Challenges and Conference Details
02:21 Digital Pathology Podcast Introduction
02:51 Technical Difficulties and Audience Interaction
06:18 Exploring Digital Pathology Papers
06:43 Advances in Bone Marrow Evaluation
09:03 AI in Hematology and Pathology
12:28 Colorectal Cancer Prognostication
19:34 Pan-Cancer Xenograft Repository
25:16 ChatGPT and Pathology Survey
30:55 Synthetic Image Generation in Pathology
36:35 Upcoming Conferences and Courses
42:27 Closing Remarks and Future Plans

THE ABSTRACTS WE COVERED TODAY

📄 Advances in Bone Marrow Evaluation
https://pubmed.ncbi.nlm.nih.gov/39089749/

📄 Digital Imaging and AI Pre-classification in Hematology
https://pubmed.ncbi.nlm.nih.gov/39089746/

📄 Evaluation of CD3 and CD8 T-Cell Immunohistochemistry for Prognostication and Prediction of Benefit From Adjuvant Chemotherapy in Early-Stage Colorectal Cancer Within the QUASAR Trial
https://pubmed.ncbi.nlm.nih.gov/39083705/

📄 A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
A survey analysis of the adoption of large language models among pathologists
https://pubmed.ncbi.nlm.nih.gov/39082680/

📄 Clinical-Grade Validation of an Autofluorescence Virtual Staining System with Human Experts and a Deep Learning System for Prostate Cancer

Support the Show.

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