Clinical Report: Doing More With Every Biopsy

Overview

Virtual staining offers a solution to the challenges of limited tissue availability in oncology by preserving samples for additional testing. This approach utilizes deep learning to generate virtual stains from unstained tissue sections.

Background

Tissue samples are critical in oncology for accurate diagnosis and treatment planning, yet the amount of available tissue from biopsies has not increased. Virtual staining addresses this issue by allowing pathologists to derive additional information from existing H&E slides, thereby preserving tissue for further molecular analyses.

Data Highlights

No numerical data or trial data was provided in the source material.

Key Findings

• Virtual staining can generate diagnostic images from unstained tissue sections using autofluorescence and deep learning models.
• Pathologists have consistently reached the same interpretations from virtual stains as from chemically stained tissue.
• This method preserves original tissue blocks for further testing, addressing the challenge of limited biopsy material.
• Tissue preservation is becoming a critical aspect of modern pathology workflows, especially with the rise of spatial biology applications.
• Virtual staining does not replace biological processes but provides a digital representation of trusted stains.

Clinical Implications

The implementation of virtual staining can enhance the efficiency of tissue use in oncology, allowing for more comprehensive analyses.

Conclusion

Virtual staining enables better utilization of limited tissue resources while maintaining diagnostic accuracy.

Related Resources & Content

1. College of American Pathologists, CAP, 2026 -- Collection and Handling of Thoracic Small Biopsy and Cytology Specimens
2. FDA, FDA, 2025 -- Considerations for Including Tissue Biopsies in Clinical Trials
3. the analytical scientist — Three Trends Shaping Multi-omics Sample Preparation
4. The ASCO Post — Targeted MR/Ultrasound Fusion–Guided Biopsy Increased Detection of  High-Risk Prostate Cancer
5. European Radiology — Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size
6. the asco post — AACR 2025: Survival Outcomes May Improve When Treatment Is Guided by Using Both Tissue and Liquid Biopsies
7. Three Trends Shaping Multi-omics Sample Preparation
8. Targeted MR/Ultrasound Fusion–Guided Biopsy Increased Detection of High-Risk Prostate Cancer
9. Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size
10. Collection and Handling of… | College of American Pathologists
11. Considerations for Including Tissue Biopsies in Clinical Trials | FDA
12. Autofluorescence Virtual Staining System for H&E Histology and Multiplex Immunofluorescence Applied to Immuno-Oncology Biomarkers in Lung Cancer - PMC