Advances in digital pathology continue to rise in popularity, increasing potential in clinical labs. But how do adoption strategies differ across the globe, and what do these regional contrasts reveal about future market direction? Here, Imogen Fitt, Principal Analyst at Signify Research, discusses the trends that are translating into real change in clinical workflows and decision-making.
Which elements of the digital pathology market are growing fastest right now?
Growth in digital pathology can be measured in several ways, which can make headline figures difficult to interpret – especially in industry press releases. Artificial intelligence (AI) as a market showed the fastest year-over-year revenue growth for 2023-2024, largely because it is still at an early stage.
Historically, digital pathology adoption has progressed in stages. Scanner hardware is typically the first investment, and a number of vendors have experienced double-digit revenue growth for several years as laboratories begin digitizing workflows. Best-of-breed image management system (IMS) software generally follows a few years later, with investment often tracking scanner placements as labs look to manage and operationalize the growing volume of digital slides. AI adoption has tended to come later, usually introduced more gradually as laboratories become comfortable with digitized slides and begin integrating more advanced tools into existing workflows.
Projected compound annual growth (CAGR) rates over the next five years are approximately 10.6 percent for hardware and 15.9 percent for software overall. Within software, growth ranges from 15.0 percent for image management solutions to 17.2 percent for image analysis tools (including AI).
The fastest-growing segment over the next five years is set to be services, with projected annual growth of 19.1 percent. This includes maintenance contracts, service agreements, and customized software development such as API access or algorithm customization. Higher service growth reflects increasing use of installed systems as scanners move from pilot projects into routine operation.
How do adoption patterns differ by care settings?
Academic medical centers (AMCs) typically lead in early implementation because they prioritize innovation and often have access to research grants. In any given marker, AMCs are therefore often the first to adopt scanners, AI tools, and other new pathology technologies.
Government funding also plays an important role. In the UK, scanner penetration in public settings is relatively high due to recent national funding programs supporting digital pathology deployment.
Healthcare delivery models also influence adoption. In some regions, hub-and-spoke laboratory networks are emerging in which centralized laboratories provide diagnostic support to smaller or remote facilities through telepathology. Canada provides one example, where telepathology networks help connect laboratories across geographically dispersed provinces.
Although community hospitals and smaller laboratories may deploy scanners, their scanning volumes and use of advanced digital analysis tools are often lower than those seen in larger centers. As a result, scanner installation numbers alone may not accurately reflect real clinical utilization.
What are the biggest practical barriers to digital pathology adoption worldwide?
Cost is often the most immediate barrier. Laboratories must fund scanners, software platforms, and AI tools, and investments must demonstrate financial or operational value. Reimbursement policies are closely linked to this issue, particularly in the US.
Historically, many adjacent healthcare technologies have expanded rapidly once reimbursement frameworks were established. Without clear financial incentives or operational benefits, laboratories may hesitate to invest soon enough despite potential clinical value.
Workflow disruption is another challenge. Digital pathology requires integration with laboratory information systems (LIS) and electronic health records (EHR). Many existing IT systems in health care are outdated or undergoing modernization, which can delay newer product implementations.
Pathologists frequently emphasize the importance of interoperability and workflow integration. Systems that require multiple interfaces or additional steps risk increasing workload and contributing to clinician burnout.
IT infrastructure also presents challenges. Although digital slide storage requirements are not yet mandated in many regions, future regulations could significantly increase storage demands. At the same time, many laboratories remain unfamiliar with cloud-based models such as software-as-a-service (SaaS), creating an additional need for education and guidance.
In real clinical practice, what does “successful” digital pathology implementation look like?
There is no single model of success that applies to every healthcare system or laboratory. However, the starting point should always be the problem the organization is trying to solve. For some laboratories, success may mean reducing diagnostic backlogs, staffing pressures, and reliance on external laboratories. In others, the goals may be improved efficiency, lower costs, or better working conditions for pathologists.
Workforce expectations are also changing. In the US, many younger pathologists expect digital tools in their workplace and may favor positions that support remote case review. As a result, digital pathology capabilities are increasingly becoming a recruitment and retention factor.
Although implementation can be complex, the broader direction of the market remains clear: digital pathology adoption continues to expand.
Across Western Europe, what adoption trends stand out most, and what makes implementation easier – or harder – across different healthcare systems?
Within Europe, Northern European countries lead digital pathology adoption. The Netherlands, the UK, and Nordic countries are considered among the most digitally mature markets due to long-term investment and supportive infrastructure.
Other regions are still developing. Italy has only recently expanded its digital pathology initiatives, while Germany – despite its large healthcare technology market – has historically adopted digital pathology more slowly due to conservative clinical practices and reimbursement challenges. Germany’s national healthcare digitalization fund is now beginning to support digital pathology projects.
Implementation tends to be easier in healthcare systems with centralized IT infrastructure. In Western Europe, national or regional LIS platforms often simplify integration because laboratories operate within a shared system environment.
Cultural factors may also influence adoption. In some technologically advanced countries, such as Japan and South Korea, pathologists have taken a more cautious approach to transitioning from traditional microscopy to digital workflows.
In the US, what are the main drivers behind investment in digital pathology now, and how are labs deciding between scanners, workflow platforms, and AI adoption?
One major driver is workforce flexibility, as digital workflows allow pathologists to review cases remotely.
Reimbursement remains a key issue. Category 3 CPT codes currently exist to collect data that could support future reimbursement decisions, but they are not yet widely used. Professional organizations such as the College of American Pathologists and the Digital Pathology Association are encouraging laboratories to adopt these codes to strengthen the case for reimbursement, potentially in a few years.
Private laboratories are also expanding digital pathology capabilities. In some cases, large organizations are acquiring smaller laboratories that already operate digitally and using them as a foundation for broader digital transformation.
Competition may further accelerate adoption in these settings. Digital workflows can reduce turnaround times by eliminating the need to ship glass slides between laboratories, creating pressure for competitors to implement similar technologies.
Purchasing strategies are also evolving. Historically, laboratories often adopted digital pathology in stages – first purchasing scanners, then later investing in IMS platforms and AI tools as digital slide volumes increased. More recently, some laboratories are evaluating scanners, workflow systems, and AI platforms simultaneously to support faster implementation.
China is often described as a rapidly growing digital pathology market. What does research show about what’s fueling that growth, and how adoption differs between large centers and smaller settings?
China has become one of the digital pathology markets with the most opportunity for vendors. Market research indicates that thousands of scanners have already been installed across the country. This expansion reflects strong government investment in healthcare technology and a national strategy focused on artificial intelligence development.
China’s healthcare system operates across several tiers, from highly advanced hospitals that frequently pilot new technologies to smaller regional institutions. Telepathology networks are expanding across the country, helping connect laboratories and address disparities in specialist availability.
Academic institutions are also investing heavily in large whole-slide imaging archives to support research and AI algorithm development. These datasets are expected to play an important role in training and validating future diagnostic tools.
Although growth has slowed slightly in some segments, vendors in certain niche areas still report annual growth rates of 20 to 30 percent, indicating significant remaining expansion potential.
From a lab leadership perspective, what do the global trends suggest about the next 12 to 24 months of digital pathology growth and day-to-day clinical adoption?
Digital pathology scanning volumes are increasing, and several countries are expected to launch large national or regional procurement initiatives in the coming years. Egypt is one recent example: Roche Diagnostics is partnering with its Ministry of Health and Universal Health Insurance system to deploy digital pathology across the public health system, aiming to improve diagnostic speed and accuracy, particularly in underserved regions.
Large healthcare and life sciences companies are also paying closer attention to digital pathology, often forming partnerships with smaller technology developers as the field matures.
At the same time, digital pathology is increasingly being considered alongside other imaging technologies. Frameworks such as the Diagnostic Imaging Adoption Model – developed by the Healthcare Information and Management Systems Society and the European Society of Radiology – are incorporating pathology into broader assessments of digital imaging maturity.
Institutions that achieve the highest levels of digital maturity provide important examples of how digital pathology can be integrated into wider healthcare IT ecosystems.
Although adoption varies by region and healthcare structure, the global trend toward digital pathology implementation continues to move forward as laboratories expand digitization and integrate new technologies into routine diagnostic practice. While vendor dynamics may shift, the long-term transition of pathology toward digital workflows remains clear.
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