Computational Pathology: Building a Connected Digital Pathology Ecosystem

What Is Computational Pathology?

Computational pathology enables pathologists and researchers to extract deeper insights from digital pathology images using AI-powered image analysis and quantitative tissue analytics. These tools help identify patterns, quantify biomarkers, and evaluate tissue characteristics at a scale that would be difficult to achieve through manual review alone.

At the same time, computational pathology depends on the quality of the digital images being analyzed. Consistent specimen preparation, staining, scanning, and quality control are critical for generating reliable data and supporting confidence in downstream analysis. By digitizing routine workflows and enabling algorithm-assisted analysis, laboratories can improve standardization while allowing pathologists to focus their expertise on higher-value research activities.

The Foundation: Digitization at Scale

As digital pathology adoption grows, laboratories must manage increasing image volumes while maintaining image quality and workflow efficiency. High-throughput whole slide imaging provides the foundation for computational pathology by generating consistent digital datasets that support analysis, collaboration, and AI applications.

Leica Biosystems offers scalable scanning solutions designed to support routine pathology, translational research, and enterprise-wide digital pathology programs.

For high-volume laboratories, timely image acquisition is essential to supporting efficient computational pathology workflows. The Aperio GT Elite scanner is designed to deliver rapid, high-quality whole slide imaging at scale, helping laboratories generate the consistent digital datasets required for image management, collaboration, and AI-enabled analysis.

Published performance data indicates scan speeds of up to 103 slides per hour and as fast as 22 seconds per slide, helping laboratories accelerate image acquisition while minimizing manual intervention.

As digital pathology programs expand, laboratories need scalable workflows that can support growing slide volumes while maintaining operational efficiency. The Aperio GT 450 scanner provides a scalable digital pathology platform suitable for routine pathology, translational research, and enterprise deployments.

In a workflow study conducted at NeoGenomics, the Aperio GT 450 scanner demonstrated measurable efficiency improvements compared with the previous-generation Aperio AT2 Scanner, including:

• 64% improvement in throughput
• 94% reduction in quality control technician time

Research organizations working with fluorescence, multiplex imaging, FISH, and spatial biology workflows can extend computational pathology capabilities using the Aperio FL platform. By supporting both brightfield and fluorescence imaging, the Aperio FL platform enables researchers to generate digital datasets suitable for advanced quantitative tissue analysis and biomarker research.
 

Reliable Computational Pathology Requires Quality Control

Artificial intelligence is only as reliable as the data used to train and deploy it. Digital pathology artifacts introduced during specimen preparation, staining, coverslipping, scanning, or image acquisition can affect image quality and downstream analysis.

To help laboratories identify image quality issues earlier in the workflow, Leica Biosystems offers Aperio iQC software, an AI-powered quality control solution. Integrated directly with the Aperio GT scanner family, Aperio iQC software automatically detects six common image issues during scanning and alerts users while slides remain on the scanner, helping support more consistent digital pathology outputs. 

A study conducted at Heidelberg University underscored the value of automated quality control in digital pathology workflows. Published performance results demonstrated:

• Reduced reviewer-specific time, including a 68.6% reduction for digital pathology technicians (17.3 minutes per case) and a 34.2% reduction for pathologists (3.4 minutes per case).
• Detection of up to 24% more artifacts with Aperio iQC software compared with manual review by histotechnicians, supporting consistent, reproducible, standardized results.
• Reduced quality control costs by automating repetitive review tasks, with manual WSI quality control estimated at $1 per slide in technician time alone.

These findings highlight how AI-assisted quality control can improve efficiency and reduce the time required for individual slide review.
 

From Digital Images to Quantitative Insight

Image management

Once slides have been digitized and quality checked, institutions need efficient ways to store, access, review, and share digital images. Centralized image management helps drive collaboration, remote review, education, and enterprise-wide access to pathology data.

The Aperio HALO AP image management system pairs with the Aperio GT Elite, Aperio GT 180, and Aperio GT 450 scanners to create a connected workflow that unifies digital slides, case information, annotations, and collaborative review. By bringing these elements together in a single environment, Aperio HALO AP software helps support efficient image management across digital pathology programs.

Quantitative analysis

Computational pathology extends beyond image viewing. Quantitative image analysis tools enable researchers to generate objective measurements and transform whole slide images into datasets that support biomarker discovery, translational research, spatial biology, and pharmaceutical development.

For research applications involving biomarker quantification, segmentation, tissue classification, and AI-assisted image analysis, the HALO image analysis platform integrates with Aperio FL scanner workflows to support quantitative tissue analysis and advanced research applications.

Accessing an Expanding AI Ecosystem

As computational pathology matures, laboratories need flexible ways to evaluate and adopt specialized AI applications without disrupting established workflows or managing separate software environments. A connected ecosystem enables organizations to expand capabilities while maintaining consistency across imaging, review, and analysis activities.

Understanding the ROI of Computational Pathology

The value of computational pathology extends beyond faster scanning or image storage. By connecting digitization, quality control, image management, and analysis within a unified workflow, organizations can realize value across operational, clinical, and research activities. Potential areas of return on investment include:

• Reduced manual slide handling and transportation
• More efficient quality control workflows
• Increased scanner throughput
• Improved access to subspecialty expertise
• Faster consultation workflows
• Standardized biomarker quantification
• Scalable support for research programs
• Reduced variability in image review processes
• Improved utilization of pathology resources

By automating routine tasks, computational pathology helps laboratories make better use of pathology expertise, enabling pathologists to focus on interpretation, collaboration, education, and research.