JCP | October 2026 | Volume 79, Issue 10 Editor’s Choice Artificial Intelligence in Digital Pathology for Prostate Cancer Detection: FDA Clearance and Real-World Implementation 🔓 Open Access Retrospective analysis of Claudin 18.2 expression in advanced gastrointestinal peritoneal disease Serum versus lithium-heparin plasma for lipid testing Also in this issue: AI and the evolving role of pathologists, digital pathology, oral squamous cell carcinoma, molecular diagnostics & more. Explore the October issue of JCP! #JCP #ClinicalPathology #Pathology #DigitalPathology #ArtificialIntelligence #OpenAccess

Are our pathology guidelines keeping pace with reality? 📖 A thought-provoking proposal to make diagnostic criteria practical, accessible and globally applicable in this excellent paper by the authors - Philippe Benjamin Stephenson, Olaleke Folaranmi, José Jiménez Heffernan, and Sanjay Mukhopadhyay, published in the BMJ Journal of Clinical Pathology. Three powerful messages: 🔹 Make criteria feasible across resource settings 🔹 Focus on what truly impacts diagnosis and treatment 🔹 Guideline panels should include community pathologists and represent the global community of pathologists The best guidelines should not just define what is ideal—they should help every pathologist make the best possible diagnosis with the resources available. Link to the full paper here bit.ly/4cvgo6K

This review paper by the authors - Sarah E Coupland, Arvind Rao, Danny Jonigk, Roman Bülow, Runjan Chetty, Swapnil Ulhas Rane, Sandeep Dave, Kikkeri N Naresh, critically evaluates the current evidence supporting the use of AI in digital pathology and outlines the conditions required to bridge proof-of-concept studies and safe deployment in routine practice. Link here for more details bit.ly/4zF6yt3

The September issue of the Journal of Clinical Pathology is here! Editor's choice - Review article titled "Promise and pragmatism of AI in global-scale digital pathology: pan-cancer approaches for clinical practice" Also in this issue: - Review article on luminal phenotype in low-grade breast epithelilal proliferations - Original research paper on HER2-low as a unique subgroup - MRI-targeted vs systematic needle core biopsies in prostate cancer - Basal plasmacytosis and eosinophilia for distinguishing IBD from GI Tuberculosis on mucosal biopsy - Mesenchymal neoplasm with RAF/BRAF alterations - and many interesting short reports

Can Ki-67 counting go digital—without a whole-slide scanner? 🔬💻 A new JCP study puts several digital approaches to the test for Ki-67 quantification in gastrointestinal well-differentiated neuroendocrine tumours (NETs). - 68 NETs were evaluated using manual counting vs digital image analysis - QuPath, ImageJ and ChatGPT-based colour segmentation showed strong agreement with manual Ki-67 counting - Even simple microscope camera-captured images performed comparably to whole-slide images - Grade changes were uncommon—and occurred mainly around the critical Ki-67 cut-off values - Some platforms performed better than others, highlighting the importance of validation before clinical use Why does this matter? Digital Ki-67 assessment may not have to depend on expensive whole-slide imaging infrastructure. Open-source tools + a microscope camera could make more reproducible quantification accessible to a much wider range of laboratories. 📖 Open access article linked here: bit.ly/4crJUdp #JCPJournal #DigitalPathology #Pathology #Ki67 #NeuroendocrineTumor #ArtificialIntelligence #QuPath #ImageAnalysis #openaccess

Can Ki-67 counting go digital—without a whole-slide scanner? 🔬💻 A new JCP study puts several digital approaches to the test for Ki-67 quantification in gastrointestinal well-differentiated neuroendocrine tumours (NETs). - 68 NETs were evaluated using manual counting vs digital image analysis - QuPath, ImageJ and ChatGPT-based colour segmentation showed strong agreement with manual Ki-67 counting - Even simple microscope camera-captured images performed comparably to whole-slide images - Grade changes were uncommon—and occurred mainly around the critical Ki-67 cut-off values - Some platforms performed better than others, highlighting the importance of validation before clinical use Why does this matter? Digital Ki-67 assessment may not have to depend on expensive whole-slide imaging infrastructure. Open-source tools + a microscope camera could make more reproducible quantification accessible to a much wider range of laboratories. 📖 Open access article linked here: bit.ly/4crJUdp #JCPJournal #DigitalPathology #Pathology #Ki67 #NeuroendocrineTumor #ArtificialIntelligence #QuPath #ImageAnalysis #openaccess

The August issue of the Journal of Clinical Pathology has plenty to explore! Rethinking triple-negative breast cancer as a threshold-defined diagnostic category Exploring liver disease diagnostics and access barriers in African settings — 🔓 Open Access Asking what AI means for the future of diagnostic pathology — 🔓 Open Access Using metagenomic sequencing to uncover microbial characteristics of granulomatous lobular mastitis Plus, new insights across pancreatic, prostate, gallbladder and hematopathology And don’t miss the Editor’s Choice on digital Ki-67 quantification in neuroendocrine tumours. Which article are you reading first? #JCPJournal #ClinicalPathology #Pathology #OpenAccess #DigitalPathology #PathologyResearch

Can Ki-67 counting go digital—without a whole-slide scanner? 🔬💻 A new JCP study puts several digital approaches to the test for Ki-67 quantification in gastrointestinal well-differentiated neuroendocrine tumours (NETs). - 68 NETs were evaluated using manual counting vs digital image analysis - QuPath, ImageJ and ChatGPT-based colour segmentation showed strong agreement with manual Ki-67 counting - Even simple microscope camera-captured images performed comparably to whole-slide images - Grade changes were uncommon—and occurred mainly around the critical Ki-67 cut-off values - Some platforms performed better than others, highlighting the importance of validation before clinical use Why does this matter? Digital Ki-67 assessment may not have to depend on expensive whole-slide imaging infrastructure. Open-source tools + a microscope camera could make more reproducible quantification accessible to a much wider range of laboratories. 📖 Open access article linked here: bit.ly/4crJUdp #JCPJournal #DigitalPathology #Pathology #Ki67 #NeuroendocrineTumor #ArtificialIntelligence #QuPath #ImageAnalysis #openaccess

🧬 One mutation. Two completely different stories. The same MYD88 mutation that helps diagnose Waldenström macroglobulinemia can also identify aggressive subsets of diffuse large B-cell lymphoma. But that's only part of the story. Its presence can: ✔ Refine difficult diagnoses ✔ Predict response to BTK inhibitors ✔ Be detected through liquid biopsies ✔ Carry opposite prognostic implications depending on the lymphoma A single molecular alteration with diagnostic, prognostic, and therapeutic impact across multiple lymphoid malignancies. Find out in this month's Gene of the Month: MYD88 Gene, linked here: bit.ly/4o94W5b

Can AI really replace pathologists ? Read @RunjanChetty & Dr Kenneth Fleming's take on this controversial question in this pertinent editorial piece from the JCP! bit.ly/4ds0BqN

Read this editorial titled "Extranodal extension in head and neck cancer: why HN-CLEAR matters and what still needs proof" by the authors - Dr Vikram Deshpande, Dr Munita Bal for an indepth understanding and clarity. Link to the editorial bit.ly/4whlTyk

From adaptor protein to oncogenic driver. A leucine-to-proline substitution at codon 265 (L265P) transforms MYD88 from a tightly regulated signalling adaptor into a constitutively active driver of lymphoma. The result? - Persistent NF-κB activation - Enhanced B-cell survival - Uncontrolled proliferation How does a single molecular alteration reshape an entire signalling network? Read the full Gene of the Month article to see how MYD88 became one of the most important biomarkers in lymphoid malignancies: bit.ly/4o94W5b