A Blueprint for Digital Pathology

Pathology plays a critical role in medical diagnoses, with laboratory tests informing nearly 70% of clinical decisions in the United States.^[1] However, many pathology labs still depend on physical slides and microscopes. This slows the diagnostic process, makes collaboration more challenging, and limits patient access to vital health information. As the shift toward digital transformation continues, the US digital pathology market is expected to reach $2.43 billion, growing at a CAGR of 8.11%.^[2] To help drive this change, a leading healthcare provider in the US collaborated with CitiusTech and Google Cloud to transition pathology into a fully digital and cloud-based environment that transforms how diagnoses are made and shared.

The platform combines Google Cloud's secure and scalable infrastructure with CitiusTech's deep expertise in solving healthcare challenges with technology. Cloud technology and open standards ensure interoperability, speed, and data exchange. Artificial intelligence (AI) tools help deliver faster and more accurate diagnoses by identifying patterns often beyond human perception. Clinicians can collaborate more easily and gain clearer insights into patient health. By moving away from manual workflows, the platform makes pathology more connected, transparent, and efficient for everyone involved.

Overcoming traditional barriers in pathology

While essential to medical diagnostics, traditional pathology methods come with several challenges that affect efficiency and patient care. They face multiple obstacles that hinder speed, accuracy, and accessibility in pathology services, such as:

• Time-consuming and labor-intensive processes: Preparing and analyzing physical slides involves multiple steps, such as fixation, embedding, and staining, which slow down diagnoses and increase the risk of human error.
• Inefficient workflows and storage challenges: Handling physical slides slows down diagnostics and complicates storage and retrieval for future analysis.
• Limited accessibility and collaboration: Microscopic slides must be physically transported for consultations, making remote collaboration slow and inefficient.
• Subjectivity and increased potential for errors: Manual interpretations can vary from one pathologist to another, introducing subjectivity that can affect diagnostic consistency and accuracy.
• Minimal patient involvement: Due to limited accessibility, patients rarely have the option to seek a second opinion or view their pathology images, impacting transparency and engagement.

However, even early digital pathology solutions, particularly proprietary platforms, have limitations that must be addressed to truly unlock the potential of digital transformation in pathology.

Challenges with proprietary digital pathology solutions

While proprietary digital pathology platforms have helped modernize workflows, they often introduce potential limitations, including:

• Vendor lock-in and limited flexibility: Organizations are tied to a specific vendor ecosystem, making switching platforms or customizing features to meet evolving needs costly and complex.
• Lack of interoperability and standardization: These closed systems often don’t integrate well with broader healthcare IT infrastructure, with inconsistent file formats and workflows complicating cross-institution collaboration.
• Restricted access and limited support: Access to data is often constrained, with minimal transparency into system operations. Support remains vendor-dependent, resulting in slower resolutions and reduced adaptability.
• High total cost of ownership: Licensing, maintenance, and upgrade fees can significantly increase long-term costs.
• Data loss and security risks: Inadequate backup mechanisms and limited visibility into data management raise concerns around privacy, compliance, and business continuity.

By removing these limitations, organizations can unlock a more open, agile, and patient-centric pathology model. The healthcare provider is accelerating this shift with Google Cloud’s infrastructure and CitiusTech’s deep healthcare engineering expertise.

A cloud-first approach to digital pathology

To solve the key challenges, they designed the cloud-based platform with key features such as:

• Cloud-based storage and accessibility: Securely stores digital pathology images and reports, eliminating physical slide storage and transportation. Pathologists can access cases remotely for faster diagnoses and streamlined workflows.
• AI-driven diagnostics: AI and machine learning assist in detecting patterns and anomalies, automating routine analyses to reduce workload, minimize human error, and speed up diagnoses. These insights also support early disease detection.
• Interoperability across systems: With support from CitiusTech, the platform integrates industry standards like DICOM and supports IHE’s DPIA profile. This enables seamless data sharing across imaging systems, Laboratory Information Systems (LIS), and viewers without needing conversion or proprietary tools.
• Streamlined collaboration: Digital files enable real-time sharing among physicians, expediting second opinions and enabling multidisciplinary discussions for better treatment planning.
• Scalability for broader adoption: A standardized, cloud-based framework supports widespread implementation across hospitals and labs, making digital pathology more accessible at scale.
• Potential for improved patient engagement: With greater digitization, patients could eventually gain access to their pathology images and take a more active role in their care, enhancing transparency and shared decision-making.
• Google Cloud Platform services used: Cloud Storage, Pub/Sub, Healthcare API (DICOM/HL7), BigQuery, DIMSE-DICOM Web Adapter, VMs (Compute Engine), AppEngine, Config Manager, and Cloud Run.

Figure 1: Architecture diagram of the cloud-based digital pathology platform

The platform combines precision diagnostics with seamless information flow to help clinicians make faster, more informed decisions. It also sets the stage for a more integrated and insight-driven care model.

Transforming care delivery through advanced collaboration and diagnostic intelligence

This cloud-based digital pathology platform redefines how physicians collaborate, consult, and deliver timely, accurate care.

• Accelerated clinical coordination and consistency: Digital pathology easily enables remote consultations and centralized access to digital files, supporting standardized protocols and quality controls. This streamlines collaboration, reduces diagnostic variability, and ensures consistent care across teams and institutions.
• Fueling research and continuous learning: A digitized, structured repository of annotated cases enables advanced analytics, clinical research, and ongoing education for pathology teams. This helps foster innovation and continuous quality improvement.
• Context-aware diagnostics through metadata: CitiusTech’s integration capabilities enrich each pathology file with patient and specimen metadata from lab systems. This added context enhances clinical decision-making and also supports the development and performance of AI tools across diagnostic workflows.
• Achieve significant time savings: For a laboratory processing approximately 100,000 cases annually, digital pathology can lead to time savings equivalent to a 15-30% gain in efficiency. Integrating AI to automate analysis can further improve efficiency resulting in up to 25% reduction in average pathologist time spent per case.^[3] These efficiencies allow pathologists to focus their time on complex cases and treatment-informing decision-making, while also reducing their workloads.

A future-ready pathology model

Digital pathology has long been explored in healthcare, but this leading healthcare provider and Google Cloud have made a significant leap by pioneering a patient-centric, cloud-based model. One of the biggest roadblocks to widespread adoption has been the lack of standardized file formats, which complicates data storage and exchange across systems. CitiusTech addresses this challenge through integration frameworks built around open standards. This ensures seamless compatibility with third-party systems, viewers, and storage solutions. The DICOM-native approach supports long-term scalability and integrates effortlessly with existing IT infrastructure.

To enhance the utility of digital pathology, CitiusTech’s metadata enrichment tools embed critical patient and specimen context into DICOM files custom-built for institutional workflows and adaptable to other client-specific needs. This enriched data enables AI engines, diagnostic viewers, and other systems to extract more actionable insights. Integrated into a secure, standards-based foundation, these tools support smarter, more reliable diagnostics.

References:

1. Innovation in Laboratory Diagnostics is Revolutionizing Health Care Delivery (acla.com)
2. Digital Pathology Market Size to Hit USD 2.43 Billion by 2034 (biospace.com)
3. From Pixels to Precision 005: The Role of Digital Pathology in Addressing Pathology Workforce Challenges (pathai.com)