Digital pathology (DP)—the practice of scanning glass slides into high-resolution whole-slide images (WSIs) and reviewing them on secure workstations enhanced by software and AI—is rapidly moving from “nice to have” to “clinical standard.” Here’s a detailed look at why DP is transforming cancer care today and what it enables next.

1) Faster, more flexible diagnosis and service coverage

• Any-time, any-where reporting. Once slides are digitized, cases can be assigned to the right subspecialist immediately—across sites and time zones—reducing bottlenecks and enabling true hub-and-spoke cancer pathways.
• Real-world gains in turnaround. Large hospitals that fully digitized their workflows have documented meaningful reductions in time to diagnosis after implementation.
• Telepathology second opinions. Digital consults compress days of courier time into hours, improving access to subspecialty expertise for complex cancer cases.

Note: Scanning introduces a front-end time cost; poorly optimized workflows can initially increase turnaround until teams fine-tune scanners, networks, and case distribution.

2) Better consistency and safety with AI assistance

• Regulatory momentum. The FDA first cleared whole-slide imaging for primary diagnosis in 2017, and since then, AI tools have gained approvals for cancer detection (including prostate cancer).
• Proven diagnostic performance. Studies demonstrate high diagnostic accuracy of AI-assisted pathology, supporting its use as a safety net to highlight small or rare foci.
• Error reduction and standardization. Heatmaps, triage, and case-prioritization features help pathologists focus effort where it matters most, supporting more consistent grading and staging.

3) Unlocking precision oncology at scale

• Seamless multimodal workflows. DP standardizes image capture for downstream quantification (IHC scoring, ISH/FISH counting) and easier correlation with molecular results—critical for targeted therapy decisions and trial matching.
• Faster pathways to treatment. Centralized and digital-first cancer care models depend on digitized workflows, enabling rapid multidisciplinary team discussions and faster treatment initiation.

4) Operational resilience amid workforce shortages

• Redistribute work, not people. Many countries face shortages of pathologists and lab scientists; DP helps spread workloads across networks and outsource peaks.
• Attract and retain talent. Digital tools and remote reporting align with modern work expectations and may help reduce burnout.

5) Quality, audit, and training—built in

• Traceability and QA. WSIs are inherently auditable—versioned, time-stamped, and searchable—simplifying peer review, discrepancy analysis, and proficiency testing.
• Education at scale. Curated slide sets and annotated heatmaps power training for residents and upskilling for consultants on new biomarkers and grading frameworks.

What’s changed recently

• Regulatory clarity. Multiple vendors now have FDA clearances for diagnostic use, and oncology-focused AI is entering workflows.
• Reimbursement tailwinds. The AMA has introduced CPT codes for slide digitization, making DP more financially sustainable.
• Vendor ecosystems maturing. Partnerships between scanner makers, LIS/LIMS providers, and AI firms are creating end-to-end validated solutions.

Barriers to plan for

• Up-front throughput and storage. High-volume labs must ensure adequate scanners and storage to avoid bottlenecks.
• Workflow and IT integration. Efficiency depends on LIS integration, viewer speed, and ergonomics—not just scanner specs.
• Validation and change management. Formal validation, training, and governance frameworks remain essential.

A step-by-step playbook for cancer centers

1. Pick the right use cases first. Begin with high-volume cancers like prostate and breast.
2. Design for scale. Ensure scanners and IT infrastructure can handle peak volumes.
3. Validate for primary diagnosis. Follow regulatory and vendor guidance for concordance.
4. Layer in AI where it helps most. Start with detection and triage tools.
5. Measure and iterate. Monitor turnaround, workload distribution, and efficiency.
6. Plan reimbursement and governance. Use available CPT codes and establish data policies.

Bottom line

Digital pathology is not just “microscopes on screens.” It is a new operating system for cancer diagnostics—accelerating pathways, supporting safer decisions with AI, expanding access to subspecialists, and laying the foundation for precision oncology at population scale.

Source

Digital Pathology – FDA, CAP, Philips, Roche, Paige, Ibex, ASCP, NHS, Nature & PubMed references