Podcasts about Histopathology

En este episodio de Hemispherics hablamos sobre el daño axonal difuso tras un traumatismo craneoencefálico, una de las formas de lesión cerebral más frecuentes y, al mismo tiempo, más difíciles de comprender desde la clínica y la neuroimagen convencional. A lo largo del episodio revisamos cómo las fuerzas de aceleración y rotación pueden producir una lesión de desconexión en las redes cerebrales, profundizando en conceptos como la axotomía secundaria, la neuroinflamación, la vía del SARM1 o la lesión axonal traumática. También abordamos qué sabemos actualmente sobre resonancia magnética, tensor de difusión y biomarcadores como GFAP, UCH-L1 o neurofilamento ligero. Más allá de la biología, el episodio intenta trasladar todo esto a la realidad clínica y terapéutica. Hablamos de las expresiones cognitivas, conductuales y motoras que pueden aparecer en estos pacientes, de las limitaciones actuales del pronóstico y de cómo entender el daño axonal difuso no como una única lesión focal, sino como una alteración dinámica de redes cerebrales. Referencias del episodio: 1. Adams, J. H., Doyle, D., Ford, I., Gennarelli, T. A., Graham, D. I., & McLellan, D. R. (1989). Diffuse axonal injury in head injury: definition, diagnosis and grading. Histopathology, 15(1), 49–59. https://doi.org/10.1111/j.1365-2559.1989.tb03040.x (https://pubmed.ncbi.nlm.nih.gov/2767623/). 2. Bayley, M. T., Janzen, S., Harnett, A., Teasell, R., Patsakos, E., Marshall, S., Bragge, P., Velikonja, D., Kua, A., Douglas, J., Togher, L., Ponsford, J., & McIntyre, A. (2023). INCOG 2.0 Guidelines for Cognitive Rehabilitation Following Traumatic Brain Injury: Methods, Overview, and Principles. The Journal of head trauma rehabilitation, 38(1), 7–23. https://doi.org/10.1097/HTR.0000000000000838 (https://pubmed.ncbi.nlm.nih.gov/36594856/). 3. Castaño-Leon, A. M., Sánchez Carabias, C., Hilario, A., Ramos, A., Navarro-Main, B., Paredes, I., Munarriz, P. M., Panero, I., Eiriz Fernández, C., García-Pérez, D., Moreno-Gomez, L. M., Esteban-Sinovas, O., Garcia Posadas, G., Gomez, P. A., & Lagares, A. (2022). Serum assessment of traumatic axonal injury: the correlation of GFAP, t-Tau, UCH-L1, and NfL levels with diffusion tensor imaging metrics and its prognosis utility. Journal of neurosurgery, 138(2), 454–464. https://doi.org/10.3171/2022.5.JNS22638 (https://pubmed.ncbi.nlm.nih.gov/35901687/). 4. Frati, A., Cerretani, D., Fiaschi, A. I., Frati, P., Gatto, V., La Russa, R., Pesce, A., Pinchi, E., Santurro, A., Fraschetti, F., & Fineschi, V. (2017). Diffuse Axonal Injury and Oxidative Stress: A Comprehensive Review. International journal of molecular sciences, 18(12), 2600. https://doi.org/10.3390/ijms18122600 (https://pubmed.ncbi.nlm.nih.gov/29207487/). 5. Geiger, P., Gmeiner, R., Schön, V., Petr, O., Thomé, C., & Pinggera, D. (2025). Timing of Magnetic Resonance Imaging (MRI) in Moderate and Severe TBI: A Systematic Review. Journal of clinical medicine, 14(12), 4078. https://doi.org/10.3390/jcm14124078 (https://pubmed.ncbi.nlm.nih.gov/40565823/). 6. Henninger, N., Bouley, J., Sikoglu, E. M., An, J., Moore, C. M., King, J. A., Bowser, R., Freeman, M. R., & Brown, R. H., Jr (2016). Attenuated traumatic axonal injury and improved functional outcome after traumatic brain injury in mice lacking Sarm1. Brain : a journal of neurology, 139(Pt 4), 1094–1105. https://doi.org/10.1093/brain/aww001 (https://pubmed.ncbi.nlm.nih.gov/26912636/). 7. Johnson, V. E., Stewart, W., & Smith, D. H. (2013). Axonal pathology in traumatic brain injury. Experimental neurology, 246, 35–43. https://doi.org/10.1016/j.expneurol.2012.01.013 (https://pubmed.ncbi.nlm.nih.gov/22285252/). 8. Lagares, A., de la Cruz, J., Terrisse, H., Mejan, O., Pavlov, V., Vermorel, C., Payen, J. F., & of the BRAINI participants and investigators (2024). An automated blood test for glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) to predict the absence of intracranial lesions on head CT in adult patients with mild traumatic brain injury: BRAINI, a multicentre observational study in Europe. EBioMedicine, 110, 105477. https://doi.org/10.1016/j.ebiom.2024.105477 (https://pmc.ncbi.nlm.nih.gov/articles/PMC11647500/). 9. Mac Donald, C. L., Dikranian, K., Song, S. K., Bayly, P. V., Holtzman, D. M., & Brody, D. L. (2007). Detection of traumatic axonal injury with diffusion tensor imaging in a mouse model of traumatic brain injury. Experimental neurology, 205(1), 116–131. https://doi.org/10.1016/j.expneurol.2007.01.035 (https://pubmed.ncbi.nlm.nih.gov/17368446/). 10. Mac Donald, C. L., Yuh, E. L., Vande Vyvere, T., Edlow, B. L., Li, L. M., Mayer, A. R., Mukherjee, P., Newcombe, V. F. J., Wilde, E. A., Koerte, I. K., Yurgelun-Todd, D., Wu, Y. C., Duhaime, A. C., Awwad, H. O., Dams-O'Connor, K., Doperalski, A., Maas, A. I. R., McCrea, M. A., Umoh, N., & Manley, G. T. (2025). Neuroimaging Characterization of Acute Traumatic Brain Injury with Focus on Frontline Clinicians: Recommendations from the 2024 National Institute of Neurological Disorders and Stroke Traumatic Brain Injury Classification and Nomenclature Initiative Imaging Working Group. Journal of neurotrauma, 42(13-14), 1056–1064. https://doi.org/10.1089/neu.2025.0079 (https://pubmed.ncbi.nlm.nih.gov/40393517/). 11. Muehlschlegel, S., Rajajee, V., Wartenberg, K. E., Alexander, S. A., Busl, K. M., Creutzfeldt, C. J., Fontaine, G. V., Hocker, S. E., Hwang, D. Y., Kim, K. S., Madzar, D., Mahanes, D., Mainali, S., Meixensberger, J., Sakowitz, O. W., Varelas, P. N., Weimar, C., & Westermaier, T. (2024). Guidelines for Neuroprognostication in Critically Ill Adults with Moderate-Severe Traumatic Brain Injury. Neurocritical care, 40(2), 448–476. https://doi.org/10.1007/s12028-023-01902-2 (https://pubmed.ncbi.nlm.nih.gov/38366277/). 12. Ponsford, J. L., Downing, M. G., Olver, J., Ponsford, M., Acher, R., Carty, M., & Spitz, G. (2014). Longitudinal follow-up of patients with traumatic brain injury: outcome at two, five, and ten years post-injury. Journal of neurotrauma, 31(1), 64–77. https://doi.org/10.1089/neu.2013.2997 (https://pubmed.ncbi.nlm.nih.gov/23889321/). 13. Sassani, M., Ghafari, T., Arachchige, P. R. W., Idrees, I., Gao, Y., Waitt, A., Weaver, S. R. C., Mazaheri, A., Lyons, H. S., Grech, O., Thaller, M., Witton, C., Bagshaw, A. P., Wilson, M., Park, H., Brookes, M., Novak, J., Mollan, S. P., Hill, L. J., Lucas, S. J. E., … Fernández-Espejo, D. (2025). Current and prospective roles of magnetic resonance imaging in mild traumatic brain injury. Brain communications, 7(2), fcaf120. https://doi.org/10.1093/braincomms/fcaf120 (https://pubmed.ncbi.nlm.nih.gov/40241788/). 14. Siedler, D. G., Chuah, M. I., Kirkcaldie, M. T., Vickers, J. C., & King, A. E. (2014). Diffuse axonal injury in brain trauma: insights from alterations in neurofilaments. Frontiers in cellular neuroscience, 8, 429. https://doi.org/10.3389/fncel.2014.00429 (https://pubmed.ncbi.nlm.nih.gov/25565963/). 15. Smith, D. H., Hicks, R., & Povlishock, J. T. (2013). Therapy development for diffuse axonal injury. Journal of neurotrauma, 30(5), 307–323. https://doi.org/10.1089/neu.2012.2825 (https://pubmed.ncbi.nlm.nih.gov/23252624/). 16. Wofford, K. L., Loane, D. J., & Cullen, D. K. (2019). Acute drivers of neuroinflammation in traumatic brain injury. Neural regeneration research, 14(9), 1481–1489. https://doi.org/10.4103/1673-5374.255958 (https://pmc.ncbi.nlm.nih.gov/articles/PMC6557091/).

Send us Fan MailPaper Discussed in this Episode:The Performance of Artificial Intelligence in Classifying Molecular Markers in Adult-Type Gliomas Using Histopathological Images: Systematic Review. Almaabreh O, Al-Dafi R, Tabassum A, Othman A, Abd-alrazaq A. J Med Internet Res 2026; 28: e78377.Episode Summary: In this deep dive of the Digital Pathology Podcast, we explore the intersection of human limitations and computational power. Following the 2021 World Health Organization mandate requiring molecular data to diagnose adult-type gliomas, pathology has faced a massive bottleneck. Can artificial intelligence look at a standard pink-and-purple tissue slide and accurately predict hidden genetic mutations to serve as a diagnostic shortcut? We unpack a massive 2026 systematic review that evaluates the architectures, the "data diets," and the structural hurdles of using AI to "see the invisible".In This Episode, We Cover:• The 2021 WHO Diagnostic Shakeup: How the World Health Organization shifted glioma diagnosis from pure visual morphology (judging a book by its cover) to requiring precise genetic spelling (finding a typo on page 42), making the diagnostic process incredibly slow and expensive.• The Targets - IDH vs. 1p/19q: Why AI models are highly proficient at spotting the metaphorical "canyon" carved by early metabolic IDH mutations, but struggle to find the subtle visual clues of 1p/19q chromosomal codeletions.• The AI Toolkit - CNNs, MIL, and Transformers: ◦ CNNs (like DenseNet121): The heavy lifters of medical imaging, analyzing local cell structures and edges by constantly reusing foundational visual features. ◦ Multiple Instance Learning (MIL): The brilliant algorithmic solution to the excruciating human labor of pixel-by-pixel tumor annotation, allowing the AI to mathematically figure out what cancer looks like using only slide-level labels. ◦ Hybrid Models: By combining the microscopic focus of CNNs with the zoomed-out, global contextual awareness of Transformers, these models achieved the highest average accuracy at 92.80%.• The "Data Diet" and Domain Shift: The critical danger of training AI exclusively on single, homogeneous databases like the TCGA. We discuss why an algorithm that performs perfectly in a pristine "test kitchen" completely panics and drops in performance when faced with the varied stains, slice thicknesses, and scans of real-world community hospitals.• Multimodal Medicine: The revelation that AI models perform vastly better when fed diverse data streams, such as combining slide images with MRI scans and clinical notes. Implementing this necessitates a monumental structural integration between historically siloed hospital departments like radiology and pathology.Key Takeaway: AI is not replacing pathologists tomorrow; it is stepping into the co-pilot seat. While hybrid models show immense promise, their true standalone clinical adoption depends on breaking free from narrow training data, overcoming domain shift, and fundamentally restructuring our hospitals to feed these algorithms the multimodal context they need to thriveSupport the showGet the "Digital Pathology 101" FREE E-book and join us!

Podcast Family, in our immediate past episode we tackled the discrepancy that is often found between a clinical diagnosis of intra-amniotic infection/chorioamnionitis and histological chorioamnionitis. From that episode, we received a fantastic question from one of our podcast family members: Can a patient have IAI without fever? That question is really deep and highlights a gap in the current diagnostic scheme/ criteria from the ACOG. Listen in for details!1. ACOG CO 7122. Sukumaran S, Pereira V, Mallur S, Chandraharan E. Cardiotocograph (CTG) Changes and Maternal and Neonatal Outcomes in Chorioamnionitis and/­or Funisitis Confirmed on Histopathology. European Journal of Obstetrics, Gynecology, and Reproductive Biology. 2021. C3. Romero R, Chaemsaithong P, Korzeniewski SJ, et al. Clinical Chorioamnionitis at Term III: How Well Do Clinical Criteria Perform in the Identification of Proven Intra-Amniotic Infection? Journal of Perinatal Medicine. 2015.

In this episode of the Pediatric and Developmental Pathology, our hosts Dr. Mike Arnold (@MArnold_PedPath) and Dr. Jason Wang speak with Professor Matthew J. Murray of the Department of Pathology and the Department of Paediatric Haematology and Oncology at the University of Cambridge, Cambridge, UK; Consultant Pediatric Pathologist Claire Trayers of the Department of Histopathology at Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; and Consultant Pediatric Oncologist Charlotte Burns of the Department of Paediatric Haematology and Oncology at Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. Hear about how persistence and a serum biomarker for a miRNA helped identify a NUT carcinoma as we talk about their work and their article in Pediatric and Developmental Pathology: Mediastinal NUT Carcinoma With Raised Serum Alpha-Fetoprotein Mimicking a Malignant Germ Cell Tumor: Suspicion Raised Due to Negative Serum miR-371a-3p Levels   Featured public domain music: Summer Pride by Loyalty Freak

Take the next step in your veterinary dentistry journey — discover how you can join Dr. Beckman's elite training community! https://ivdi.org/inv ---------------------------------------------------------------------- Host: Dr. Brett Beckman, DVM, FAVD, DAVDC, DAAPM In this episode of The Vet Dental Show, Dr. Brett Beckman, DVM, FAVD, DAVDC, DAAPM, answers common questions and shares expert insights on oral pathology. Learn how to differentiate feline gingival stomatitis from other oral inflammations, which lab is best for histopathology, and when to refer cases to a board-certified veterinary dentist. ---------------------------------------------------------------------- Questions Answered: What are the best labs for veterinary oral histopathology? How can I differentiate stomatitis from feline gingival stomatitis? When should I biopsy a stomatitis case? Who should I refer to for oral masses or fracture repair? What You'll Learn:  ✅ Discover the best lab for oral histopathology in dogs and cats.  ✅ Understand the key differences between stomatitis and feline gingival stomatitis.  ✅ Master the nuances of diagnosing oral inflammation in cats.  ✅ Simplify your approach to biopsies in stomatitis cases.  ✅ Apply solo catheter placement techniques in your practice.  ✅ Recognize when to refer cases to a board-certified veterinary dentist. Key Takeaways:  ✅ Dr. Cindy Bell at SOP for Animals is the top choice for oral pathology. ✅ Caudal oral mucosal inflammation is the key differentiator for feline gingival stomatitis.  ✅ For oral masses and fracture repairs, board-certified veterinary dentists are generally the best choice. ---------------------------------------------------------------------- Transform your dental practice today — request your invite to the Veterinary Dental Practitioner Program: https://ivdi.org/inv Explore Dr. Beckman's complete library of veterinary dentistry courses and CE resources! https://veterinarydentistry.net/ ---------------------------------------------------------------------- Questions? Leave a comment below with your thoughts, experiences, or cases related to veterinary dentistry! ---------------------------------------------------------------------- KEYWORDS: Veterinary Dentistry, IVDI, Brett Beckman, Dog Dental Care, Cat Dental Care, VetTech Tips, Animal Health, Veterinary Education, Veterinary Dental Practitioner Program, Vet Dental Show, Oral Pathology, Stomatitis, Feline Gingival Stomatitis, Histopathology, Veterinary CE

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This episode of the podcast welcomes Dr. Kelly Keating, DACVP, DACVD. Dr. Keating sees clinical dermatology cases in Las Vegas and reviews dermatopathology. So, she has experience collecting the biopsy samples herself and reading them!Dr. Keating provides insight on how to maximize your histopathology findings and work with your dermatopathologist to get a diagnosis. Nobody wants to get back non-specific inflammation!You can go to https://www.animaldermatology.com/dermatopathology-services if you are interested in submitting to Animal Dermatopathology Services!TIMESTAMPS00:00 Intro01:13 Most common mistakes you see with submissions to skin biopsy?04:46 How much does having a submission of history help you when you do get a sample?09:21 Tips for general practitioners who are submitting biopsies12:04 Tips for mass removals14:46 Site selection18:28 Biopsy an ulcer20:14 Preferred withdrawal time24:25 How often do you see infections covering up what you need to see?27:40 What are special stains?30:05 Tissue Culture explanation 33:18 Biopsy Ear Tips35:10 Where people can send Dr. Keating samples36:47 Outro

Following the 2024 Marginal Zone Lymphoma (MZL) Workshop, CancerNetwork® spoke with multiple attending clinicians about insights they shared regarding the disease state, covering the significance of the workshop and its contribution to advancing research in areas such as prognostic factors and managing adverse events (AEs) related to the disease. Thomas Habermann, MD, professor of Medicine at the Mayo Clinic in Rochester, Minnesota, member of the Lymphoma Research Foundation's Scientific Advisory Board, and MZL Workshop co-chair, spoke about the significance of the MZL Workshop. He highlighted the complexity of these types of diseases, which he believed warranted the establishment of the group. According to Habermann, MZL is a “heterogenous group of disorders” that most contemporaries in the field “don't quite appreciate.” Next, Julie M. Vose, MD, MBA, George and Peggy Payne chair in oncology and chief of Hematology and Oncology at the University of Nebraska Medical Center, and co-editor-in-chief of ONCOLOGY®, spoke about how the MZL Workshop contributes to advancing research and improving outcomes for patients with MZL. She emphasized a need to be more inclusive when enrolling patients with MZL in clinical trials. Then, James R. Cerhan, MD, PhD, professor of Epidemiology at the Mayo Clinic College of Medicine and Science, and Ralph S. and Beverly Caulkins Professor of Cancer Research, spoke about addressing research questions in MZL epidemiology to further disease understanding. He emphasized a need to further study newly identified risk factors of the disease, as well as identifying new treatment targets for patients with MZL. Additionally, Alexandar Tzankov, MD, surgical pathologist and head of the Department of Histopathology and Autopsy at the Institute of Medical Genetics and Pathology at University Hospital Basel, and chair for the European Bone Marrow Working Group, discussed how prognostic factors for MZL may influence treatment. He described how the limited number of studies done with relatively small subsets of patients makes prognoses challenging, as prognostic factors have not been sufficiently explored. Finally, Andrew D. Zelenetz, MD, PhD, medical director of Quality Informatics at Memorial Sloan Kettering Cancer Center, outlined challenges related to AE management of treatments for MZL. He emphasized that safety management practices for MZL are comparable with other B-cell lymphomas, suggesting that use of bridging therapy for CAR T cells and step-up dosing for bispecific antibodies may help with mitigating AEs.

In this episode of SEE HEAR FEEL, Dr. Rosalie Elenitsas from the University of Pennsylvania shares her extensive experience in dermatopathology. She discusses her career journey, the importance of daily consensus conferences, learning from junior colleagues, and managing work-life balance. Dr. Elenitsas also offers valuable advice on building a support system, continuous learning, dealing with errors, and the significance of simple yet effective practices in both professional and personal life.00:00 Introduction and Guest Introduction01:12 Personal Anecdote: Learning to Ride a Bike02:08 Advice for a Successful Career05:15 Work-Life Balance and Support Systems08:52 Dealing with Errors and Continuous Improvement13:08 Conclusion and Final ThoughtsDr. Rosalie Elenitsas, MD is the Herman Beerman Professor of Dermatology and Pathology and the Director of the Penn Cutaneous Pathology Services since 1999 at the Perelman School of Medicine at the University of Pennsylvania. Dr. Elenitsas has been a faculty member at Penn since 1991 and has been director of the Dermatopathology Fellowship Program since 1998; she recently transferred the directorship to Emily Chu just this year. She has published more than 200 manuscripts/chapters, and has given more than 100 invited lectures. She is associate editor of Lever's Histopathology of the Skin and the past president of the Pennsylvania Academy of Dermatology and past president of the American Society of Dermatopathology (ASDP). She received the Nickel Award for teaching in Dermatopathology by the ASDP, and has also been elected to the Academy of Master Clinicians at Penn Medicine, a coveted honor for practicing physicians in the Penn health system. 

Summary In this episode of the Vet Dental Show, Dr. Brett Beckman, Board Certified Veterinary Dentist, answers listener questions about managing gingival hyperplasia in boxers and other brachycephalic breeds. Dr. Beckman discusses the importance of radiographs before treatment, when to refer complex cases, and the nuances of dealing with epulides. Tune in for expert advice and practical tips to enhance your veterinary dental practice. Guest, Cast, and Crew Information Host: Dr. Brett Beckman, Board Certified Veterinary Dentist Sponsor: Veterinary Dental Practitioner Program Main Talking Points Introduction: Overview of the episode and sponsorship details. Listener Question: Mandy's question on treating gingival hyperplasia in boxers. Radiographs Importance: The necessity of taking radiographs before treatment. Treatment Approach: Steps to handle gingival hyperplasia and epulides. When to Refer: Guidance on referring complex brachycephalic cases. Histopathology: The importance of submitting tissue for histopathology. Maintenance and Follow-Up: Managing recurrent gingival hyperplasia. Interesting Quotes "You do not want to go in and start removing tissue without first taking radiographs." "Brachycephalic breeds often have dense cortical bone, making extractions more challenging." "Gingival hyperplasia will come back and requires maintenance every 6 to 18 months." Timestamps 00:00 - 00:30: Introduction 00:31 - 02:00: Listener Question from Mandy 02:01 - 04:00: Importance of Radiographs 04:01 - 06:00: Treatment Approach for Gingival Hyperplasia 06:01 - 08:00: When to Refer Complex Cases 08:01 - 10:00: Histopathology and Tissue Submission 10:01 - 11:30: Maintenance and Follow-Up 11:31 - 13:00: Summary and Conclusion [Veterinary dentistry, gingival hyperplasia, brachycephalic breeds, radiographs, dental extractions, epulides, histopathology, veterinary dental training, Dr. Brett Beckman] Key Points Summary Radiographs Importance: Always take full mouth radiographs before treating gingival hyperplasia. Treatment Approach: Remove affected teeth and contour tissue for closure. Referral Guidance: Refer complex brachycephalic cases to specialists. Histopathology: Submit all excised tissue for pathology to ensure an accurate diagnosis. Maintenance: Regular follow-up and maintenance are necessary for managing recurrent gingival hyperplasia. Affiliate & Sponsor Links IVDI.org/inv - Submit your request for an invitation to the Veterinary Dental Practitioner Program.  

Do you feel comfortable with skin biopsies? For such a small sample, it is easy to mess up. Check out this week's episode of The Derm Vet podcast regarding prepping (don't!), sampling and submitting to maximize your results!TIMESTAMPSIntro 00:00Get More Than One Sample (Tip #1) 03:20User A Bigger Punch (Tip #2) 05:02Do Not Prep Them (Tip #3) 06:48Use A Dermatopathologist (Tip #4) 08:16Rock Your Skin Biopsies (Tip #5) 10:10Outro 11:54

Drs. Alicia Morgans and Jonathan Rosenberg share their insights into some interesting abstracts from the 2024 ASCO GU symposium: one covering a model to help predict response to neoadjuvant chemotherapy in patients with muscle invasive UC, and another regarding results from the PemCab study of pembrolizumab and cabozantinib in first‑line advanced UC.

Pictorlabs is a California-based startup developing a cloud-based platform that uses artificial intelligence to improve tissue sample analysis through virtual histological staining.In Episode #34 of the Speed to Data Podcast, Key Tech's Andy Rogers speaks with Pictorlabs Chief Product Officer Raymond Kozikowski about his company's all-digital approach to tissue sample testing.Need to know·       Histopathology — The visual analysis of stained tissue samples to diagnose cancer and other conditions.·       Tests have long turnaround times — Selection, preparation, and imaging can take as long as a day to return one test's results to the physician.·       Tests are requested sequentially — The results of one test determine the next test in the decision tree, so physicians can't order all the tests simultaneously.·       Cancer patients must wait — On average, there is a forty-day gap between biopsy and first treatment.The nitty-grittyAs Dr. Kozikowski explains, “Histopathology has traditionally been a chemistry-based testing paradigm. Every cancer case starts with a biopsy, and those tissues are transformed into data that inform the diagnosis and therapeutic options.”Pictorlabs' solution uses one tissue sample to create a virtual stain that simultaneously generates results for dozens of tests within minutes. “What we're doing is teaching AI algorithms the relationship between validated test results and the underlying signature from that unstained piece of tissue,” Dr. Kozikowski said. “From a single patient sample, you're no longer limited to running one chemical-based test. You can run ten, twenty, thirty AI-based tests.”Although the company thought it faced a long march toward the clinical market, Pictorlabs found an opportunity in a different market.“There's a really robust cancer research market, both the academic medical centers and the pharma companies. Where we really got traction wasn't necessarily as a replacement [technology] but a complement to other kinds of tests.”Dr. Kozikowski cites spatial biology as an example. Cells express their genes and RNA differently depending on their location in tissue. Understanding this spatial relationship could yield new, more targeted therapies.“A challenge with interrogating RNA targets,” Dr. Kozikowski explains, “is that you often can't also run traditional staining-based tests. With virtual staining, we're actually able to complement those RNA-based tests with a pseudo-staining result. This is perfectly fit for purpose in those workflows.”Data that made the difference:The importance of data to AI development isn't surprising, but Pictorlabs needs more than quantity.“There's also a lot of nuance in the design of that dataset and making sure it's fit for purpose,” Dr. Kozikowski says. “Has it seen the diversity of human disease in that training dataset to really make sure that it generalizes accurately and robustly?”Partnerships with the research community have helped refine Pictorlab's technology. One of these relationships is with Dr. Michael Kallen, a pathologist at the University of Maryland's School of Medicine.“Diagnosing lymphoma or leukemia can be very, very complex. You have the challenge of managing a complex workflow in the lab and the complexity of making sense of all those test results spread over weeks or maybe even a month.”“[Dr. Kallen] saw the opportunity. We've been partnered with that department for a while now, exchanging data to help train algorithms and get feedback from pathologists. We've just received an innovation grant to deploy our technology side-by-side with their existing workflows to look at the value.”Watch the full video below to learn more about Pictorlabs' virtual staining solution and to hear Dr. Kozikowski's advice to product managers and entrepreneurs.

Prof. Hamid Tizhoosh explores the applications of artificial intelligence (AI) in medicine, particularly in medical image analysis and cross relations to other patient data such as molecular, laboratory and textual data. His research is currently focused on search and matching in archives of patient data. Foundation Models for Histopathology—Fanfare or Flair Creating an atlas of normal tissue for pruning WSI patching through anomaly detection

Surfing the MASH Tsunami continues its 2023 wrap-up conversations with HistoIndex Chief Scientific Officer Dean Tai, along with co-hosts Jörn Schattenberg and Roger Green. The conversation focuses on growth in the use of AI in Steatotic Liver Disease and some of the insights the profession is developing as a result. The conversation starts with Dean Tai and Jörn Schattenberg discussing the many promising advances in artificial intelligence over the past year. The two leaders agree both that the advances are providing exceptional new insights already, and will provide even greater insight when we can link AI to outcomes. Roger Green also notes how important it is that we improve the insights we develop from biopsy and, at the same time, the quality of non-invasive tests and suggests that AI has the ability to help on both issues. Finally, from the patient perspective, Louise Campbell suggests that anything that reduces the number of patients we biopsy or the number of biopsies per patient is a significant advance. To be more specific, Dean points out that some of the newer clinical trials are yielding decreases of 30-70% in liver fat density, along with significant decreases in liver volume. Since these measures reduce faster than fibrosis, AI is now giving us the ability to learn more about the process of fibrosis reduction in the aftermath of density and volume declines. Jörn notes that one important issue here involves differences in how pathologists and AI read changes in fibrosis. Specifically, we sometimes overread fibrosis levels in the presence of fast liver fat reductions. He also notes that we can combine these findings with direct fibrosis measures to learn even more and faster. Louise anticipates that this will provide additional benefits if we can fit patient quality-of-life metrics with this data to pinpoint when in the disease treatment process patients begin actually to feel better. Dean goes on to a second point. AI allows researchers to explore reductions in different regions of the liver in terms of how different regions relate to outcomes. He also points out that in Steatotic Liver Diseases, we see that fibrosis continues in parallel with fibrolysis, which researchers now need to consider in the context of overall disease. Roger mentions two items: that Dean has said in private conversation that in AI-based studies, placebo response usually occurs in ~1/3 of patients and, separately, that bariatric studies suggest that one level of regression might require five years. Dean responds by saying that AI allows us to determine when underlying disease is resolving even if the pathologist considers the patient as presenting with regressive disease. Roger asks whether AI can be used to assure patients how thoroughly we have studied these drugs and how much we have learned and, separately, to demonstrate more value to payers than we believe using "naked eye" data. Dean suggests the keys will be to simplify the data we present and also to generate a joint statement from the entire community on these issues. Looking at 2024, Dean anticipates more and richer data than we have. He also cautions that we should shift from biopsy to NITs in clinical trials before we have developed deeper knowledge on how the liver works and what NITs must capture. In this process, he envisions 2024 as a "proof-of-concept" year before we can move to totally non-invasive monitoring in 2025 or 2026. Jörn, who had dropped off the conversation for a few moments, suggested that AI will improve clinical practice over time as well. In closing, Dean states his concern for 2024 is that we shift too quickly from biopsy to NITs. Louise comments that we cannot discredit biopsy (at least, not yet) and that providers can explain to patients why it is necessary.

Dr. Christine Limonte summarizes the main findings from her study "Associations of Biomarkers of Tubular Injury and Inflammation with Biopsy Features in Type 1 Diabetes," on behalf of her colleagues.

Dr. Patrick Emanuel is a dermatopathologist based in Lima, Peru. He also consults for IGENZ molecular laboratory, Pathlab Bay of Plenty, and the Skin Institute (all based in New Zealand). He is an Honorary Associate Professor at the University of Auckland and Adjunct Assistant Professor at the Icahn Mount Sinai School of Medicine in New York. Patrick's academic interests include cutaneous squamous cell carcinoma, margin control surgery, and the application of molecular techniques to cutaneous tumours.In this episode, we discuss his journey from Dunedin, to Nelson, to America, then to Peru. We talk about his pathway into dermatopathology, the training involved, the daily routines, and the pay disparity for residency in US. We discuss his work-life balance, practicing medicine in a second language, and the capacity for remote work as a pathologist.Book 'Margin Control Surgery of the Skin: Concepts, Histopathology, and Applications' mentioned ://www.mhprofessional.com/margin-control-surgery-of-the-skin-concepts-histopathology-and-applications-9781264285990-usa#tab-label-product-description-titleDermnet: https://dermnetnz.org/Support the showAs always, if you have any feedback or queries, or if you would like to get in touch with the speaker, feel free to get in touch at doctornos@pm.me. Audio credit:Bliss by Luke Bergs https://soundcloud.com/bergscloudCreative Commons — Attribution-ShareAlike 3.0 Unported — CC BY-SA 3.0Free Download / Stream: https://bit.ly/33DJFs9Music promoted by Audio Library https://youtu.be/e9aXhBQDT9Y

Learn new strategies and tactics to slow the greying of hair and prevent hair loss as you age. Support your Workout Sessions and Healthy Hydration with the Electrolyte + Creatine Combo by MYOXCIENCE : https://bit.ly/electrolyte-stix  Use code podcast to save 15% Link to study: https://bit.ly/3PHGxVp References: Fernandez‐Flores, A., Saeb‐Lima, M. & Cassarino, D. S. Histopathology of aging of the hair follicle. J. Cutan. Pathol. 46, 508–519 (2019).   Papaccio, F., D′Arino, A., Caputo, S. & Bellei, B. Focus on the Contribution of Oxidative Stress in Skin Aging. Antioxidants 11, 1121 (2022).   Williams, R., Pawlus, A. D. & Thornton, M. J. Getting under the skin of hair aging: the impact of the hair follicle environment. Exp. Dermatol. 29, 588–597 (2020). Show Notes: 01:00 We may slow hair graying and hair loss by decreasing chronic inflammation. 02:00 By age 50, 50% of us will have 50% of our hair gray. 02:00 Over 1 year you lose .25% of your hair follicles. 03:00 post-menopausal women have a dramatic increase in follicle loss. 03:30 Oxidative stress can influence gray hair. 04:20 UV stress can affect the hair bulb. 04:40 There is a correlation between graying of hair, facial wrinkling, and crown top baldness and myocardial infarction in men. 08:00 With age, hairs are reduced in diameter and experience follicle miniaturization. 08:55 Chronic inflammation increases damage to DNA proteins and lipids within the hair follicle environment. 10:05 Collagen may be effective in preventing premature wrinkling of the skin and hair loss. 10:55 Bone mineral density correlates with hair loss and hair graying. 11:20 Slowing senescence and purging senescent cells happen with fasting and exercise. 12:25 Minimize exposure to pollution. Avoid excessive sun exposure. Avoid nutrition deficiencies. 13:30 Insulin resistance and PCOS can exacerbate hair loss. 14:00 Sometimes graying from environmental factors may be reversed. 14:30 52% of post-menopausal women experience hair loss. 14:40 Micronized progesterone can help women preserve the integrity of skin and hair follicle. 15:20 Lack of estrogen accelerates changes in hair follicle and skin aging. 17:45 Some shampoos can accelerate graying and hair loss. 18:35 Men with high levels of DHT, consider a ketoconazole shampoo.  

Commentary by Dr. Candice Silversides

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.02.17.529024v1?rss=1 Authors: Rios-Carrillo, R., Ramirez-Manzanares, A., Luna-Munguia, H., Regalado, M., Concha, L. Abstract: Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is a non-invasive technique that is sensitive to microstructural geometry in neural tissue and is useful for the detection of neuropathology in research and clinical settings. Tensor valued diffusion encoding schemes (b-tensor) have been developed to enrich the microstructural data that can be obtained through DW-MRI. These advanced methods have proven to be more specific to microstructural properties than conventional DW-MRI acquisitions. Additionally, machine learning methods are particularly useful for the study of multidimensional data sets. In this work, we have tested the reach of b-tensor encoding data analyses with machine learning in different histopathological scenarios. We achieved this in three steps: 1) We induced different forms of white matter damage in rodent optic nerves. 2) We obtained ex-vivo DW-MRI with b-tensor encoding schemes and calculated quantitative metrics using Q-space Trajectory Imaging. 3) We used a machine learning model to identify the main contributing features and built a voxel-wise probabilistic classification map of histological damage. Our results show that this model is sensitive to characteristics of microstructural damage. In conclusion, b-tensor encoded DW-MRI analyzed with machine learning methods, have the potential to be further developed for the detection of histopathology and neurodegeneration. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Andrew Janowczyk is an assistant professor at Emory University, USA. Andrew's research focuses on applying computer vision and machine learning algorithms to digital pathology. His key area of expertise is in leveraging deep learning to build computational models for aiding pathologists in many common tasks, such as disease detection and cancer grading.

Podcast Editor, Liz McInnes, interviews author Ronnie Chamanza to discuss the article, "The Influence of Geographical Origin, Age, Sex, and Animal Husbandry on the Spontaneous Histopathology of Laboratory Cynomolgus Macaques (Macaca Fascicularis): A Contemporary Global and Multisite Review of Historical Control Data" which can currently be found in Vol 50, Issue 5, 2022 of Toxicologic Pathology. Click here to read the article

On July 7, Intercept Pharmaceuticals released new results from the continuation of the REGENERATE trial and announced their intent to file a new NDA for obeticholic acid (OCA) in NASH fibrosis. In this conversation, Stephen Harrison leads Jörn Schattenberg, Louise Campbell and Roger Green in considering whether the evidence in the new release will be sufficient to get the drug approved.Stephen starts by noting that we have not heard anything about the results of the REVERSE trial, which evaluated obeticholic acid (OCA) in patients with compensated cirrhosis. As he notes, even if OCA is not approved for cirrhosis, many hepatologists will consider giving this drug to cirrhotic patients, particularly compensated cirrhotics who face a significant worsening of their condition in a fairly short period of time. Jörn comments on this briefly to agree that the cirrhosis data will create a complete data set, then returns to the pruritus issue. Mostly, his point about cirrhosis is that given the high placebo rate suggests there is "something about how the question is asked." He finishes this comment by discussing the importance of getting a first drug approved and stating his anticipation of what happens when FDA reviews these data. Roger goes on to note that he has a unique experience in this group: he has discontinued a drug therapy based on pruritus (in his case, a cancer drug). Having lived through that experience, he expresses skepticism that pruritus that resolves on discontinuation will be a reason for the drug to be rejected. Stephen concurs, and Roger goes on to state that the perceived cardiovascular risk in 2020 made sense as a reason not to approve, but not pruritus. Stephen and Louise concur that we will not know the entire story until we know the lengths to which providers went to keep patients in this study, but both are hopeful (and pretty much expect) that while there may be boundaries on patient types and guidance on treatment, the case for approval appears likely to succeed. During the second half of this conversation, panelists share their common hope that this data will be sufficient to get OCA approved and discuss what this could mean for the entire Fatty Liver stakeholder community.

On July 7, Intercept Pharmaceuticals released new results from the continuation of the REGENERATE trial and announced their intent to file a new NDA for obeticholic acid (OCA) in NASH fibrosis. In this conversation, Stephen Harrison leads Jörn Schattenberg, Louise Campbell and Roger Green in considering less obvious questions surrounding efficacy and safety.Stephen starts this conversation by asking the group how important it is for a drug (in this case, obeticholic acid) to show a combined endpoint of fibrosis improvement and NASH resolution. He notes this is a tougher standard to hit but notes that it might be quite important.Jörn describes this comment as a "good point" that probably was not addressed due to the low level of NASH resolution when viewed as a primary endpoint. Louise says she would need to know more about the diets patients were on while in the trial given the effect diet can have on liver fat. She then goes on to say that one question she would like to have answered is how many patients needed counseling on their pruritus to stay in the study and what exact steps did researchers take to keep these patients in. She points out that knowing the steps necessary to maintain patient adherence is vitally important to caregivers but rarely reported for trials, if ever.Roger makes two points. His first basically supports Jörn's comment that the low level of NASH resolution as a primary endpoint virtually guarantees that the number of patients achieving the dual endpoint will be minimal at best. His second harkens back to Stephen's earlier point about including a larger post-18 month patient pool in the efficacy analysis. To Roger, it appears that Intercept made the sound commercial decision to reveal only the data necessary to generate the analyses necessary for approval. It felt to him as if Intercept assessed the least risky way to refute each point in the CRL, and then did only the analyses necessary to refute points successfully. In essence, Roger describes the analysis as a way to de-risk the drug and believes they appear to have done so effectively. At this point, Stephen shifts direction. He gives Intercept "accolades...they didn't give up. They persevered. They continued to drive forward and they added three different adjudication committees." And while he believes there is more analysis to be done, he describes the contents of the press release as "a very, very positive implication for the field" and "give[s] it two thumbs up." After Roger concurs, Stephen goes back to Louise's questions about pruritus and notes that the methodology for evaluating pruritus might have produced overstated results. In essence, the investigator asked patients whether they were experiencing pruritus at every visit, an approach Stephen and Jörn believe was likely to produce an overstatement on itching. Stephen continues this line of thinking to note that investigators were forced to discontinue therapy under certain pruritus reports. As the conversation ends, he notes that he is far more interested in hepatic effects.

On July 7, Intercept Pharmaceuticals released new results from the continuation of the REGENERATE trial and announced their intent to file a new NDA for obeticholic acid (OCA) in NASH fibrosis. In this conversation, Stephen Harrison leads Jörn Schattenberg, Louise Campbell and Roger Green in examining the new efficacy analysis and exploring what it means for obeticholic acid, both in terms of the drug's performance and its revised prospects for FDA approval.After reviewing the four key points from Intercept's press release, Stephen Harrison kicks off this conversation by looking at a broader efficacy picture than mere regression of fibrosis, to ask what percentage of patients experienced no further progression of fibrosis compared to the placebo group. Stephen notes that the clinical value of simply halting fibrosis progression in an F3 patient is tremendously important because it allows an asymptomatic patient to continue life at its current level of quality. He adds, "we can manage co-morbidities" separately. He goes on to wonder why Intercept did not expand the analysis to include the large number of patients who made it past the 18-month biopsy time point but were not part of the original 2019 efficacy cohort.At this point, Stephen takes a step back from the actual data to describe how the consensus approach worked on histological reads and to praise the approach for providing clear, simple answers. Jörn Schattenberg picks up the conversation by agreeing with Stephen's assessment of the consensus approach, which he describes as emulating how colleagues assess challenging cases or histopathology reports in actual practice. Roger joins the conversation to wonder why the consensus reading process would have the effect of reducing the percentage of patients who improve in the placebo group on one reading but not elsewhere. More important to him, he goes on to agree with the idea that if this agent regresses fibrosis in some cases but halts progression in most or all, it might become a valuable part of a combination therapy that includes other agents with a stronger effect against steatosis than fibrosis. Thinking from a patient perspective, Louise notes that consensus reads should give the patient greater confidence in the results. In terms of confidence and border reads, Stephen points out that some of the presentations at the recent ILC2022 meeting that drugs that have an impact on NASH might also affect liver volume. (He notes that the open-label cirrhotic cohort of the resmetirom trial MAESTRO-NAFLD 1 also showed spleen volume reduction and an inverse effect on platelet count.) Setting aside the cirrhosis results, he notes that if we start to measure liver volume when conducting biopsies, we can correct estimates of the impact of fibrosis to account for changes in "what we see" based on changes in liver volume. As the conversation ends, he notes that this might be a fruitful topic for future research that can translate into patient treatment.

On July 7, Intercept Pharmaceuticals released new results from the continuation of the REGENERATE trial and announced their intent to file a new NDA for obeticholic acid (OCA) in NASH fibrosis. In this conversation, Stephen Harrison leads Jörn Schattenberg, Louise Campbell and Roger Green in examining how the larger sample and longer time patients were on therapy changed the safety and tolerability profile from the initial analysis.After reviewing the four key points from Intercept's press release, Stephen Harrison kicks off this conversation by discussing the safety evaluation, which included a far larger population with significantly longer exposure to study drug. After describing the enriched population, he quotes from the press release, "Emergent adverse events treatment, emergent serious adverse events, and deaths were generally balanced across the OTC and placebo treatment groups." He goes on to cite the considerable differences in pruritus across groups (22% in placebo, 33% in 10mg and 55% in 25mg), share the comment that most discontinuation stemmed from pruritus, note that gall bladder-related events occurred in less than 3% of patients and, finally, that OCA 25mg had a higher rate of biliary events. He then asked the rest of the group for comments.Jörn commented first, noting that this was mostly "recapitulated" data, but with a much broader set of subjects. Because risk:benefit ratio was perceived as the pivotal issue around the time of the original Complete Response Letter (CRL), he describes the data as improved "by a lot."Louise describes as "reassuring" the idea that the NASH dose could be so much higher than the approved PBC dose (25mg vs. 5 or 10mg) but not demonstrate additional safety concerns. She goes on to declare that practices planning to use OCA should be "planning pathways into delivery" in anticipation that the high level of pruritus will lead to a significant set of discontinuation with a careful approach to patient orientation and management. Roger shared his recollection that increases in LDL levels and the implicit associated cardiovascular risk were major issues in the negative risk:benefit assessment, but that this analysis appears to report that levels returned to normal within the first year of treatment. This might increase chances for approval.At this point, Stephen reads the press release carefully to identify potential safety hazards that are not addressed directly in the document, although, as he notes, one can fit only so much into a press release. As the conversation ends, Stephen asks Jörn if he has "ongoing lingering questions". Jörn notes that he wondered how the reads were done and that he also looked for LDL data. He makes a few other points, but suspects that they may have been covered in the 2019 paper.

This week, NASH Tsunami responds to listeners who have asked "Where are the episodes on drug development?" by asking Stephen Harrison to lead a review of the NASH pipeline.Stephen starts by noting that the mechanics of the drug development pathway, which we discussed earlier this year in the context of NASH-TAG and strategies on how to shift away from traditional metrics, remain what they have been: same conditional endpoints (fibrosis improvement without worsening NASH or NASH resolution without worsening fibrosis, or improving both) and the same need for biopsy read as is has been. Stephen explains the difference between dual primary endpoints and co-primary endpoints in the context of a recent announcement from Madrigal. From there, he goes on to list the various drugs and modes of action in different stages of development, starting with the five agents in Phase 3, then working his way back through the Phase 2b studies to discuss some of the more significant or interesting agents earlier in development. One interesting point Stephen raises is that clinical development for obeticholic acid, the Intercept drug that FDA failed to approve, continues. By now, he notes we have data on over 2,000 patients and a significant number of patients that have been studied for over four years. Jörn Schattenberg registers his excitement at the size of this population and the wealth of data they offer researchers. Throughout this discussion of ongoing research, including not only Intercept but the length of some of the resmetirom studies, Stephen notes that NASH drug development is very much a work in process. Led by Stephen, the group goes on to consider what our failures to date have taught us about doing drug development better, a phenomenon that Stephen, Jörn and Louise all note makes them hopeful for the future. Stephen specifically notes that drug developers and researchers alike have broadened their ambitions from simply reducing fibrosis and liver fat to being part of a total metabolic solution that includes diabetes, obesity and cardiovascular health along with liver. Before leaving the conversation, Stephen notes the critical need to improvement diversity of clinical trial populations and notes that while it may take some years, he sees the future of patient treatment as lying in combination therapy. After Stephen leaves, the discussion shifts slightly, with more focus on cirrhosis, the reasons for drug development and increasing optimism that the drug development community is on the right path. Toward the end, the discussion turns to consider quality of life, which if affected negatively by Fatty Liver disease. Jörn notes that it could serve as the third leg of a stool or tripod to pull NASH drugs over the line. Roger suggests the possibility that a lot of antidepressants are being prescribed for patients who would feel better with less fatty livers. On that optimistic note, the group provides final answers about the most striking part of the episode and departs to live another week.This episode is sponsored by Madrigal Pharmaceuticals. Today's extra-sode is a summary of Madrigal's disease-focused presentation at the recent CLDF LiverConnect meeting.

The 5th Global NASH Congress will take place in London (in person only) on May 27 and 28. Louise Campbell and scientist/entrepreneur Rachel Zayas, who will cover the Congress for NASH Tsunami, join Ian Rowe and regulars Jörn Schattenberg and Roger Green to discuss some key papers and issues covered there. This episode focuses on a range of topics: the importance of weight loss, the challenges of histology and how to overcome them in drug development, and what panelists hope to take away from this meeting.

The episode and this conversation is sponsored by HistoIndex. This specific conversation focuses on ways and AI-assistive technologies and analyses can improve our abilities to assess efficacy in drugs that treat advanced fibrosis and cirrhosis.For this extrasode, HistoIndex Chief Scientific Officer Dean Tai joins Quentin Anstee, Mazen Noureddin, Joern Schattenberg and Roger Green to discuss how AI-based algorithms can support improved analysis of ballooned hepatocyte changes both in advanced fibrosis and cirrhosis patients.The rest of the conversation probes how this work will affect diagnosis and drug development, what other tests panelists can foresee and areas where Histoindex is looking to create new algorithms and improve existing ones.This conversation starts with Histoindex Chief Scientific Officer Dean Tai discussing the approach his company takes to AI-assisted hepatopathology. Dean starts by discussing briefly how staining, which is extremely helpful when the goal is to define the individual patient, becomes one more source of error in the more quantitative approach necessary for drug trials. He goes on to point out that while they can achieve 90% success in reproducing an individual coder's result using AI, their goal is to achieve 99% success. He finishes by defining the goal as "majority-agreed hepatocytes," hepatocytes where 5 or more of the 9 pathologists in the initial exercise agreed that a hepatocyte had ballooned. As Dean puts it, with ballooned hepatocytes, "you are really trying to identify bad apples from all apples," not "oranges from apples."In explaining the Histoindex approach, Dean describes some pathologists as "under-callers" who identify relatively few ballooned cells and others as "over-callers" who identify far more cells. The primary difference between the two groups was how large they needed a cell to be before they classed it as "ballooned."Because these differences were systematic and structural, Quentin questions whether we can ever "train" consistent responses. He suggests that consistency will grow for a while but then coders will revert more to their historical patterns. In response to a question from Mazen, Quentin goes on to note that the number of pathologists necessary to validate a ballooned cell will vary inversely with the number of cells identified. For example, a model based on 7-member agreement produces results that are more specific, less sensitive. A model based on 3-member agreement would produce more sensitivity, less specificity. As a result, the team settled on 5 (majority of 9) as the best-rounded number. Mazen responds that for drug trials, being more specific is preferable because it creates a better chance for the drug to appear efficacious when it is.The panelists go on to note that this tool is extremely helpful today in Phase 2, but not in Phase 3 and Dean explains some of the concepts Histoindex is working on to support future use in Phase 3 trials.At that point, the conversation shifts to having Mazen discuss his work in cirrhosis. Going back through historic work, and particularly separate work from Drs. Garcia-Tsao and Younossi, Mazen identified three features to track: septal thickness, nodular features and fibrosis area (the SNOF score). Using these metrics Mazen sought data from the Galectin trials because these were among the few trials that measures portal pressures. The Galectin data allowed researchers to correlate these kinds of measures to a 20% change in portal pressures. This score wound up being reliable in detecting portal hypertension and in two particularly pivotal measures: detecting presence of varices and changes of greater than 20% in portal pressures.

One major discussion at NASH-TAG this year was about the inconsistency in ballooned hepatocyte identification and how this inconsistency inflates screen fail rates and possibly placebo response across studies. This conversation is part of a thorough exploration of this issue.This conversation starts with Roger Green asking Stephen Harrison how clinical trial analysis might change for the better pending implementation of what researchers learned in this study. Stephen suggests that the area in greatest need of improvement is efficacy analysis at the back end of clinical trials. Specifically Stephen notes that variability in placebo response rates is the single largest factor determining which Phase 2b and Phase 3 trials are deemed success or failure. He asks whether there is a way to correlate the AI assessment of ballooned hepatocyte improvement to changes in fibrosis and, separately, whether we should be looking at more tissue. Stephen notes that the present approach has led us to kill good drugs due to analytical error. Louise Campbell agrees and makes a different point, which is that over time, exhaustion leads to consistent changes in the ways experts evaluate data. Quentin takes Louise's point as an interesting question about controlling for intra-rater variability. After some interplay, Stephen discusses how he was trained to read slides (by Dr. Brunt, lead author on this paper). He was taught first to get an overall feel for whether the slide architecture looks like NASH before scouring for ballooned hepatocytes. Quentin notes that the AI methodology (qBallooning2) incorporates some assessment of fibrosis into the identification of balloon cells.The episode and this conversation are sponsored by HistoIndex. Conversation 14.5 is a discussion of how artificial intelligence driven assistive technology can improve the consistency of ballooned hepatocyte scoring in advanced fibrosis and support development of robust outcomes for fibrosis studies.

One major discussion at NASH-TAG this year was about the inconsistency in ballooned hepatocyte identification and how this inconsistency inflates screen fail rates and possibly placebo response across studies. This conversation is part of a thorough exploration of this issue.This conversation starts with Roger Green wrapping up the earlier discussion of the relationship between holistic NASH assessment and ballooned hepatocyte scoring by saying it is not surprising that fibrosis is an element in ballooned cell scoring, given that pathologists start with a holistic assessment and work back from there.Jörn Schattenberg asks Quentin Anstee to comment on Stephen Harrison's proposal to use 3 slides for H & E reads. After discussing a different strategy ("keep reading until you see enough cells"), Quentin suggests a protocol with a constant, relatively small number of slides for each case. Roger then asks Quentin how many ballooned cells might appear on a single slide; Quentin answers that this is a challenging question but on the slide where everyone saw the most ballooned cells, the number scored by an individual pathologist ranged from 45 to 225. After Louise Campbell comments on the need to make the best possible use of tissue out of respect to the patient who is donating the biopsy, Roger asks a final question: a year or two from now, what is likely to be different and what can we aspire to be different as a result of this study. Quentin would like to see ballooned hepatocyte assessment move from a "Yes/No" assessment to a continuous assessment of volume and would like to see regulators recognize the role and value of AI-assistive technologies in drug development. Mazen Noureddin concurs and goes on to ask what we might expect in terms of changes in the screen fail rate. In different ways and with different nuances, Jörn, Louise and Roger concur as well.The episode and this conversation are sponsored by HistoIndex. Conversation 14.5 is a discussion of how artificial intelligence driven assistive technology can improve the consistency of ballooned hepatocyte scoring in advanced fibrosis and support development of robust outcomes for fibrosis studies.

One major discussion at NASH-TAG this year was about the inconsistency in ballooned hepatocyte identification and how this inconsistency inflates screen fail rates and possibly placebo response across studies.This conversation is part of a thorough exploration of this issue. It starts with Mazen Noureddin raising two questions about the entire subject of ballooned hepatocyte scoring in NAS assessment: should we use it at all, and if we should, should we move immediately to AI as the key to analysis?Quentin provides nuanced answers to both questions. On the issue of ballooned hepatocytes, he notes that these were originally designated to characterize individual patients, not to create semi-quantitative scores. Today, he notes, we are asking far more of ballooned hepatocyte assessment than it was designed to do. On the issue of AI, Quentin notes his care to use the phrase "AI-assisted tehcnology," that we need pathologists to confirm that what the patient has is, in fact, NAFLd instead of, for example, autoimmune hepatitis. Once that is proven, then we can ask AI to provide a more quantiatively consistent assessment.Jörn Schattenberg begins his comments by noting and agreeing with the idea that we are asking more of ballooned hepatocyte assessment than it was designed to do. He proceeds to ask whether we can augment hepatocyte analysis with a liquid biomarker or with a different stain.Quentin suggests that the solution will not lie in stains. The idea or liquid biomarkers is more promising, but first we will need to reduce error in the assessment and then focus our attention on biomarkers (he mentions NIS-4) that were designed to assess hepatocytes.Roger Green finishes this conversation by noting the the phrase "semi-quantitative" itself invites analytical error. We power studies assuming that the important error is statistical and can be resolved by sample size, whereas the bigger challenge is in the qualitative assessment of the slides. If qualitative variability is dramatic, as it is here, it will dwarf statistical error and mean that all samples are underpowered. Roger concludes by asking whether we should forestall major shifts until we understand how much we can reduce analytical error through AI assistance. Quentin concurs.The episode and this conversation are sponsored by HistoIndex. Conversation 14.5 is a discussion of how artificial intelligence driven assistive technology can improve the consistency of ballooned hepatocyte scoring in advanced fibrosis and support development of robust outcomes for fibrosis studies.

One major discussion at NASH-TAG this year was about the inconsistency in ballooned hepatocyte identification and how this inconsistency inflates screen fail rates and possibly placebo response across studies.This conversation explores that issue in detail. It begins with Quentin Anstee eloquently laying out the challenge that led to this study and the approach it took.The challenge: recent studies have produce Kappa values for coding NAS scores in the 0.55 - 0.60 range. These scores suggests a level of error-related noise that might swamp a signal that a drug actually works.The solution: nine of the world's leading hepatopathologists (who, Quentin notes, were "amazingly generous with their time") scored ten different liver biopsies by drawing circles around the slides they determined were ballooned cells and then repeated the process 90 days later in a different order, with some mirrored or rotated.First finding: Concordance was "relatively modest." There was only one slide in the entire exercise where all nine pathologists found a ballooned hepatocyte. This clearly suggested that relying on a measure of the number of ballooned cells on a slide as a measure of disease was likely to produce inconsistent results due to what Quentin describes as "the lack of a common vocabulary" or vision between the pathologists.After noting how small a sample a single cell was, Stephen Harrison asks whether we would be served better if we evaluated the volume of ballooned cells on a slide, rather than the absolute number.As the conversation ends, Quentin notes analyzing a slide looking for ballooned cell is a much more complex procedure than nonhepatologists previously appreciated. He suggests that if we are looking for an analysis that is quantitative and consistent, volume may provide more robust results than looking at an actual number.The episode and this conversation are sponsored by HistoIndex. Conversation 14.5 is a discussion of how artificial intelligence driven assistive technology can improve the consistency of ballooned hepatocyte scoring in advanced fibrosis and support development of robust outcomes for fibrosis studies.

One major discussion at NASH-TAG this year was about the inconsistency in ballooned hepatocyte identification and how this inconsistency inflates screen fail rates and possibly placebo response across studies. This episode explores that issue in detail.The episode is sponsored by HistoIndex. At the back of the episode is a discussion of how artificial intelligence driven assistive technology can improve the consistency of ballooned hepatocyte scoring in advanced fibrosis and support development of robust outcomes for fibrosis studies.This conversation includes three of the paper's authors, including last author Quentin Anstee. The conversation starts with Professor Anstee discussing how the paper came to be. He quickly jumps into the meet of the discussion, which is the relatively low concordance between highly skilled world class hepatopathologists over how many ballooned hepatocytes they see on a slide of a patient who might have NASH.  The results suggested significant differences between two world-class hepatopathologists looking at the same slide in terms of the presence and significance of hepatocytes. The next stage of the episode consists of other panelists praising the study while asking questions about its implications. Stephen Harrison asks how we can take these findings into drug development. Mazen Noureddin asks whether these results suggest either that we should question using ballooned hepatocytes in drug development or, more likely, we should shift immediately to an AI-mediated solution to get more consistent results. Jörn Schattenberg asks whether liquid biopsies would improve prediction and, presciently, whether we are asking more from liver histology than it can deliver. This points to a pivotal issue: liver histology was developed initially to characterize individual patients qualitatively. Today, we call these findings "semi-quantitative" and use them to analyze trial results.Two problems: the error embedded in the differences between how two pathologists would interpret the same slide is far greater than the sampling error, leading us to undersample and overinterpret. Second, we try to "prove" the value of blood-based biomarkers and AI-based assistive technologies by comparing them to something that is deeply flawed in the first place.The extrasode discusses how HistoIndex used created the qBallooning2 analysis to improve the common identification of ballooned hepatocytes in patients with advanced fibrosis. In addition, Mazen Nourediin discussed his AASLD Poster of Distinction from 2022, which looks at ways that artificial intelligence techniques can support more robust analysis of improved outcomes in patients with cirrhosis.In the end, though, no 4,000 character summary can do this episode justice. To fully get the impact of this critically important discussion, plan to listen at least twice. Listen to the first part to comprehend the scope of the issue around ballooned hepatocytes and the challenges it causes, and the second part to learn how inventive data scientists can create better solutions by processing large amounts of data and being willing to challenge historical assumptions. NOTE: HistoIndex is sponsoring a complementary webinar, Deciphering NASH: Fibrosis Dynamics in Cirrhotic Patients and Insights into Ballooned Hepatocytes using AI, at 11:00 am Eastern Daylight Time on Tuesday, March 23. For more information, visit the event website at https://www.global-engage.com/event/nash-data-on-fibrosis-and-ballooning-using-ai/.

NAIL-NIT is both a response to the challenges of histopathology and an effort to create a different vision of testing liver patients.This episode starts with Stephen Harrison describing the events that came to demonstrate how challenging current histopathology approaches: a series of drug development failures that reflect shortcomings in methodology rather than in the developmental drugs themselves. Sen Sundaram notes that the difference between the NAIL-NIT approach and that of other consortia is that NAIL-NIT seeks to link NITs directly to outcomes rather than correlating them to histopathology-based measures. Mazen Noureddin discussed the frequency at which patients with obvious NASH and fibrosis fail to screen into studies due to inability to find balloon hepatocytes in the biopsy-derived slides and raises the human ethical implications of excluding these patients. Amy Articolo encourages us to envision a future in which drugs are available to treat patients and make sure we have the best possible testing to diagnose and prescribe the proper therapeutic regimens to patients. From there, the discuss shifts as Stephen Harrison and Sen Sundaram discuss the quality of data existing today that links NITs directly to outcomes. Sen notes that "if we think about the amount of data that we have" for NITs and outcomes, "we probably have more data now than is cited to support histopathology in a current guidance."

This week's episode introduces us to the topic of melanoma We cover: - Risk factors- Precursor lesions- Histopathology and important histopathological features related to poor prognosis - Melanoma types and their appearance including superficial spreading, nodular, lentigo maligna melanoma, acral lentiginous, and desmoplastic - Workup including excisional biopsy and when to stage patients- Staging with AJCC 8th edition TNM staging classification - When to perform sentinel lymph node biopsy and lymph node dissection Keep an eye out for next week's episode where we talk about management of melanoma!DisclaimerThe information in this podcast is intended as a revision aid for the purposes of the General Surgery Fellowship Exam.This information is not to be considered to include any recommendations or medical advice by the author or publisher or any other person. The listener should conduct and rely upon their own independent analysis of the information in this document.The author provides no guarantees or assurances in relation to any connection between the content of this podcast and the general surgical fellowship exam.  No responsibility or liability is accepted by the author in relation to the performance of any person in the exam.  This podcast is not a substitute for candidates undertaking their own preparations for the exam.To the maximum extent permitted by law, no responsibility or liability is accepted by the author or publisher or any other person as to the adequacy, accuracy, correctness, completeness or reasonableness of this information, including any statements or information provided by third parties and reproduced or referred to in this document. To the maximum extent permitted by law, no responsibility for any errors in or omissions from this document, whether arising out of negligence or otherwise, is accepted.The information contained in this podcast has not been independently verified.© Amanda Nikolic 2022

Histopathology is elementary in the diagnostics of patients with MDS, but its high-dimensional data are underused. By elucidating the association of morphologic features with clinical variables and molecular genetics, this study highlights the vast potential of convolutional neural networks in understanding MDS pathology and how genetics is reflected in BM morphology. Article: https://bloodcancerdiscov.aacrjournals.org/content/2/3/238

Hi friends, this is Dr. Michael Williams and welcome back to another episode of the diversify in path podcast. This podcast explores how investing in diversity can lead to a high return of investment in pathology and laboratory medicine by learning from the knowledge and experiences of diverse voices within our field. My next guest is Dr. Ryan ClarkDr.  Clark is a Foundation Year 2 Doctor (two years post-graduation from medical school) in Glasgow, Scotland. He is also an Honorary Clinical Fellow in Medical Education and Histopathology at the University of Glasgow. In his clinical and academic practice, Ryan utilizes his experiences as a low SES, LGBTQIA+, disabled person to enhance the work that he does. He also works as part of the Diversity Network at the Royal College of Pathologists to help make pathology the most inclusive place it can be. Twitter:  Ryan Clark (@RyanCla60282460) / Twitter

Mei Lin Bissonnette is Clinical Associate Professor at the University of British Columbia and Director of the BC Provincial Renal Pathology Laboratory, St. Paul's Hospital, Vancouver, British Columbia, Canada.Hayley Pincott is Associate Practitioner in the Oral Pathology and Microbiology department at Cardiff and Vale University Health Board, Cardiff, UK.

In advance of NASH-TAG 2022 this weekend, Jörn Schattenberg joins the Surfers to answer a key conference question: are we ready to pivot toward non-invasive tests and better uses of histopathology? The group explores a range of questions and ideas that are likely to emerge during Saturday night's fireside chats.The group explores a range of questions and ideas that are likely to emerge during Saturday night's fireside chats. Highlights include:7:03 – Stephen Harrison begins to discuss NASH-TAG 20227:45 – Jörn Schattenberg: we're not ready to move beyond biopsy in 2022. Hope that we will bring forward the right program by end of year8:31 – Roger agrees8:43 – Stephen agrees, but looks to determine how to resolve pivotal challenges9:46 – Stephen lists discussants for the fireside chats, including regulators, researchers and industry representatives10:30 – Stephen lists  key topics for his talk on non-cirrhotic trial endpoints11:37 – Stephen lists “hurdles” biopsy  "needs to overcome" 12:40 – Stephen's key issue for histopathology : why we only score one H&E and one tri-chrome read per sample. He suggests three H & E and promises to reveal data on this in his talk.15:08 – Jörn: "Why three?” 16:08 – Stephen: no magic, three non-contiguous reads “just makes sense.” The goal is to is to find ballooned hepatocytes or clustering, which might not appear in one slide but will frequently elsewhere in the sample.18:11 – Stephen: choose the slide with the strongest presence of disease18:47 – Key benefit: we screen fail fewer people on ballooned hepatocytes19:59 – Potential secondary benefit: reducing resolution scores in the placebo group21:09 – Stephen: three companies looking at this. All see a major difference.21:29 – Stephen: there are commercial issues as well: high screen fail rates inflate costs and take lots of time. This approach will save money and time.24:13 – Stephen: I like Jörn's idea about using AI here. It will enhance reproducibility.24:52 – Stephen: another issue is the shift from one to multiple pathologists. Multiple pathologists turns out to drive screen fail rate higher. We need something to counter that.26:49 – Louise Campbell: getting more tissue is beneficial for the patient27:52 – Louise: a lot of NIT evaluation comes from pairing to biopsy samples. The more samples, the more opportunity to test NITs.29:14 – Stephen shifts to getting beyond the biopsy. FDA issue: link an NIT to outcome. The cirrhosis chat gives us our first shot on goal.30:55 – Stephen: one challenge with non-cirrhotics is that NITs are not included in the major Phase 3 trials32:07 – Jörn: this is a pivotal issue and NASH-TAG is the right place to discuss it33:33 – Louise: consider quality-of-life as a high value outcome measure33:57 – Jörn: how do we explore stabilization of disease with NITs?34:31 – Stephen: all these are reasons to “set the stage” with cirrhotic cohorts first, learn the lessons, then extend to non-cirrhotics37:56 – Closing question: what will make 2022 successful to you in terms of moving this agenda forward?38:17 – Jörn: data from the consortia38:50 – Stephen: a clear idea of what will get us to a surrogate endpoint with NITs. Until then. improve histopathology practices.39:54 – Louise: anything with histopathology that leads us toward NITs is good. Also, we will need to do more remotely as long as COVID keeps rearing its head.40:51 – Roger: let's learn more and make two cases one on economics and the other on data quality41:17 – Stephen: one more thing: better economics and stronger data will motivate Big Pharma to invest43:53 – Stephen: at the end of the day, it's all about economics44:53 – Roger: burnt money feels wasted, makes study investment feel like an expense46:09 – Stephen: listen for more Saturday night47:16 – Business report

In this episode, we talk with Heather Couture about how to make deep learning models for tissue image analysis more robust to domain shift. Supervised deep learning has made a strong mark in the histopathology image analysis space, however, this is a data-centric approach. We train the image analysis solution on whole slide images and want them to perform on other whole slide images - images we did not train on. The assumption is that the new images will be similar to the ones we train the image analysis solution on, but how similar do they need to be? And what is domain and domain shift?Domain: a group of similar whole slide images (WSI). E.g., WSIs coming from the same scanner or coming from the same lab. We train our deep learning model on these WSIs, so we call it our source domain. We later want to use this model and target a different group of images, e.g. images from a different scanner or a different lab - our target domain.When applying a model trained on a source domain to a target domain we shift the domain and the domain shift can have consequences for the model performance. Because of the differences in the images the model usually performs worse...How can we prevent it or minimize the damage?Listen to Heather explain the following 5 ways to handle the domain shift:Standardize the appearance of your images with stain normalization techniquesColor augmentation during training to take advantage of variations in stainingDomain adversarial training to learn domain-invariant featuresAdapt the model at test time to handle the new image distributionFinetune the model on the target domainClick here to read Heather's full article on making histopathology image analysis models more robust to domain shift.Visit Pixel Scientia Labs here.And listen to our previous episode titled "Why machine learning expertise is needed for digital pathology projects" here to learn more about the subjects and learn how Heather and her company can help.

Dr. Insa Schmidt provides a summary of her study "Circulating Plasma Biomarkers in Biopsy-Confirmed Kidney Disease," on behalf of her colleagues.

This conversation is part of SurfingNASH's 2021 NAFLD Year-In-Review. Dr. Mazen Noureddin, Director of the Fatty Liver Program at Cedars Sinai, Los Angeles, joins Louise Campbell and Roger Green to discuss advances in AI in histopathology.Mazen Noureddin notes that while non-invasive tests are important and likely to become more so over time, drug development today will need to rely on AI to interpret and ultimately improve histology reads. One benefit he notes is the ability of AI reads to reveal differences between cirrhosis patients in terms of percentage of liver that is F4 vs. F3. In one study, AI also reduced the percent efficacy in a placebo group when compared to human readers. Mazen raises the pivotal question, "When are we going to use these AI techniques in clinical trials?" He and Louise Campbell suggest that we might have enough confidence today to analyze via AI, if only to compare results to what traditional, error-ridden approaches. He notes thats Louise suggests strongly that adopting the Ishak score might be a good way to go. Ultimately, Mazen suggests we can detect more liver features and also clarify unclear results.

Rajendra Singh is Professor of Dermatology and Pathology, Director of Dermatopathology, and Associate Chair of Digital Pathology at Northwell Health, New York, USA. He is also the Founder of PathPresenter Corporation. He can be found on Twitter at @mydermpath and @pathpresenter.Melanie Bois is Consultant in the Division of Anatomic Pathology and Assistant Professor of Laboratory Medicine and Pathology at Mayo Clinic, Rochester, Minnesota, USA. She can be found on Twitter at @MelanieBoisMD.Join us back on the tour bus on January 11, 2022, for the next stop in our two-episode, histopathology special!

Welcome to episode 6 of IMPACT Medicom's podcast series on Precision Medicine in Oncology. In this episode Dr. Gonzalez discusses testing methodology, particularly for mismatch repair deficiency, as well as potential emerging biomarkers for metastatic colorectal cancer. Our Guest: Dr. Raul Gonzalez is an Associate Professor of Pathology at Harvard Medical School and the Director of Gastrointestinal Pathology at Beth Israel Deaconess Medical Center in Boston, Massachusetts.  Dr. Gonzalez is a surgical pathologist specializing in gastrointestinal pathology. He is the Editor- in-Chief of Pathology Outlines and the Reviews Editor for Histopathology. He also serves as the Vice Chair for the College of American Pathologists Surgical Pathology Committee and the Website Committee Chair for the Hans Popper Hepatopathology Society.This podcast episode was sponsored by Merck Canada.If you enjoy our podcast, please review and subscribe. For more podcasts and other medical education content, visit our website at: https://www.impactmedicom.com

Prostate Cancer Diagnosis and Prognosis: Histopathology with guest Dr. Peter Humphrey September 19, 2021 Yale Cancer Center visit: http://www.yalecancercenter.org email: canceranswers@yale.edu call: 203-785-4095

Prostate Cancer Diagnosis and Prognosis: Histopathology with guest Dr. Peter Humphrey September 19, 2021 Yale Cancer Center visit: http://www.yalecancercenter.org email: canceranswers@yale.edu call: 203-785-4095

Most people in live poultry production haven't spent a lot of time reading about histopathology.  Still, veterinarians who specialize in diagnosing disease in animal tissues are spending more time in processing plants helping to minimize costly carcass condemnations while maintaining the company's high standards for quality.   

Dr. Soliman discusses his team's analysis of clinical predictors of low histopathology in eyes that were enucleated because of retinoblastoma. The goal of the study is to find clinical indicators in retinoblastoma that could be used to salvage eyes via eye-preserving treatment methods instead of enucleation. 

Over the last 18 months or so a number of dogs in the United Kingdom have been affected by a disorder which causes skin lesions initially followed within a few days by signs of acute kidney injury. Histopathology in these cases has shown cutaneous and renal glomerular vasculopathy consistent with changes seen in a condition known as Alabama Rot, described in North America but not previously reported in the UK. In this podcast we discuss the experience with this disorder in the UK thus far and illustrate what is – or more accurately – what is not known about this disorder. The podcast features Dr Rosanne Jepson who is a Lecturer in Internal Medicine at the RVC and also a member of the Renal Replacement Therapy team at the QMHA. Rosanne has a special interest in nephrology in particular. A couple of links mentioned in the podcast include: Forestry Commission (England) website which has a list of the reported cases including their geographical distribution The Animal Health Trust questionnaire has now closed. Another source of further information about the disease is Anderson Moores. If you have any comments about this podcast, please get in touch (email sjasani@rvc.ac.uk; tweet @RoyalVetCollege using #saclinpod; or use the RVC's Facebook page).