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How close is pathology AI to making decisions that matter in real workflows, real trials, and real patient care?

In this episode of DigiPath Digest, I review five recent papers that approach that question from very different angles. We look at multimodal survival prediction in cervical cancer, pathology-driven response assessment in neoadjuvant immunotherapy for head and neck squamous cell carcinoma, AI-assisted Ki-67 scoring in pulmonary neuroendocrine neoplasms, automation and AI in hematologic diagnostics, and AI-based qFibrosis readouts from the Phase 3 MAESTRO-NASH trial.

What I liked about this set of papers is that they do not all tell the same story. Some show clear progress. Some show where AI already works well as an adjunct. Others make it very clear that validation, governance, reproducibility, and workflow design still matter just as much as model performance.

Key topics and timestamps

• 00:00 Introduction, Easter edition, and community updates 
• 00:51 USCAP recap, signed book giveaway, and free Digital Pathology 101 PDF 
• 02:04 Partnerships, lab automation preview, and what’s coming in this episode 
• 03:25 Multimodal deep learning for cervical cancer survival prediction 
• 13:00 Why pathology may be a better response endpoint than radiology in neoadjuvant HNSCC immunotherapy 
• 23:09 Ki-67 scoring in pulmonary neuroendocrine neoplasms: pathologists vs two AI systems 
• 33:46 AI, digital morphology, and automation in hematologic diagnostics 
• 43:29 qFibrosis, digital biomarkers, and the MAESTRO-NASH Phase 3 trial 
• 51:57 Closing thoughts, community updates, and Easter promotion 

Resources

1.  Deep Learning Can Predict the Overall Survival of Cervical Cancer Based on Histopathological Image, Gene Mutation and Clinical Information
    https://pubmed.ncbi.nlm.nih.gov/41902378/
   
2.  Modern Pathology-Driven Strategies in Neoadjuvant Immunotherapy for Head and Neck Squamous Cell Carcinoma: From Residual Tumor Quantification to Spatial and AI-Based Biomarkers
    https://pubmed.ncbi.nlm.nih.gov/41899621/
   
3.  Ki-67 Proliferation Index in Pulmonary Neuroendocrine Neoplasms: Interobserver Agreement Among Pathologists and Comparison of Two Artificial Intelligence-Based Image Analysis Systems
    https://pubmed.ncbi.nlm.nih.gov/41898274/
   
4.  Molecular Pathology, Artificial Intelligence, and New Technologies in Hematologic Diagnostics: Translational Opportunities and Practical Considerations
    https://pubmed.ncbi.nlm.nih.gov/41897649/
   
5.  Quantitative regression of qFibrosis with resmetirom: Exploratory histologic endpoints from the MAESTRO-NASH phase III clinical trial
    https://pubmed.ncbi.nlm.nih.gov/41895606/

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