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What actually needs to be in place before digital pathology can replace the microscope?

In this episode of DigiPath Digest, I walk through the 2026 Polish Society of Pathologists guidelines and translate them into practical steps for real pathology labs. This isn’t theory. It’s about hardware fidelity, data integrity, validation, and AI integration — and what each of these actually requires in daily workflow.

We talk about scanner resolution standards (≤0.26 μm per pixel), 4K monitor calibration, visually lossless compression (20:1), scalable storage, pathologist-driven validation, and what “non-inferiority” truly means.

Digital pathology is not just a change of medium. It’s an operational shift.

Episode Highlights

[00:02] Community & growth
1,600+ new newsletter subscribers, 10,000+ Facebook members, and free Digital Pathology 101 book access.

[07:20] The 4 pillars of adoption
Hardware fidelity · Data integrity · Clinical validation · Future integration.

[08:30] Hardware requirements
40x equivalent scanning (≤0.26 μm/px), 4K monitors, >300 cd/m² luminance, 10-bit color depth.

[12:00] Workflow & throughput
200–300 slides/day per scanner, automated focus control, urgent case prioritization.

[17:25] Storage & archiving
~1 GB per slide. Active archive (6–24 months). Long-term retention (10–20 years). GDPR compliance & TLS encryption.

[23:09] Validation philosophy
Pathologist-centered validation.
Two phases:
• Familiarization (~20 retrospective cases)
• Dual review with discrepancy tracking
Goal: digital must be non-inferior to glass.

[29:03] AI in digital pathology
AI supports quantification (Ki-67, HER2, ER/PR, PD-L1), tumor detection, and future multimodal predictions — but pathologists remain central.

[33:26] Intraoperative telepathology
<5-minute scan-to-view time.
Minimum 100 Mbps upload.
Redundancy and safety protocols required.

[34:50] Can digital cameras replace scanners?
Hybrid workflows exist. Regulatory compliance still applies.

[38:19] Adoption checklist summary
Certified scanners (CE-IVD/FDA), calibrated monitors, scalable storage, phased validation, and documented QC.

Key Takeaways

• Digital pathology adoption is a structured process — not just buying a scanner.
• Validation is individualized and tissue-specific.
• Infrastructure and quality control are as important as image quality.
• AI enhances reproducibility and quantification but does not replace pathologists.
• Regulatory compliance and data governance are non-negotiable.

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