Destination DICOM in Digital Pathology: Drivers and Obstacles

Publication Date: 11/11/2023

11th November 2023 – Cranfield, UK – Digital pathology may have been a nascent sector historically, but sudden growth in the market since 2020 has sparked attention from both pathology and wider healthcare stakeholders.  

As investment continues, these wider stakeholders are becoming increasingly influential, and conversations surrounding pathology digitisation have started to evolve accordingly.  

One of the prime initiatives currently underway has to do with the standardisation of file formats and therefore interoperability of data in both digital pathology and wider healthcare. Increasingly the Digital Imaging and Communications in Medicine (DICOM) standard is emerging as a front runner, as it did in radiology many years previously. This article will examine some of the drivers and obstacles that lie ahead for its adoption.  

The route: what have we learned from radiology?  

As mentioned, radiology has been using DICOM successfully for some time and since its inception the standard has also spread beyond to clinical departments like dermatology, ophthalmology, and endoscopy. 

DICOM’s use in radiology has clearly shown the benefits of standardisation in healthcare. Its incorporation years previously allowed providers to facilitate easier access to patient data in and between networks, enabling healthcare practitioners to collaborate more easily to improve the standard of patient care. DICOM’s incorporation of metadata also facilitated many additional workflow services, including allowing users to manage imaging procedure worklists, report procedure and archiving status, organise layouts of images and encrypt datasets.  

DICOM for digital pathology ultimately offers the same benefits for interoperability and image access in pathology. 

The pot of gold: what else does DICOM offer pathology? 

Adoption of DICOM also offers users of digital pathology some additional benefits.  

Products already in place to enable systemic use of DICOM in radiology can support pathology department digitisation via offering access to existing VNAs, therefore removing the need to purchase new applications to support data management.. This is particularly attractive for the IT departments in hospitals, who face a growing challenge of managing large swathes of data from many different departments. Ultimately, this means IT resources are less stretched to facilitate digital pathology.  

However, the benefits of standardisation today now span beyond managing individual patient data. Arguably the biggest benefit in the adoption of DICOM is its use in the creation of data lakes for real-world data (RWD) studies. The use of existing clinical data in RWD studies has the potential to revolutionise clinical trials and precision medicine efforts by providing broader access than can be achieved in clinical trials. Standardising image outputs streamlines the creation of these data lakes and DICOM also allows additional metadata to be incorporated. Examples of metadata included in DICOM images is shown in table 1.  Access to acquisition data for example offers benefits because it allows clinicians to immediately identify variations in image curation, for example, whether the image has been scanned under different settings.  

Table 1 details of metadata which can be associated with a DICOM image. 

As Table 1 shows, there is standard and optionally included metadata within DICOM images.  This flexibility can also be a disadvantage because DICOM images can be created unequally across deployments and left open to interpretation if customers do not dictate unilaterally what must be included. This is often not the case in tenders across Western Europe today.  

A final advantage of the pyrimidal file format offered to digital pathology relates to storage latency.  The pyramidal structure means that tiered storage can be utilised via packing different imaging layers in different storage tiers. Indivudal image components (such as the 20x magnification) can then be stored where it can be accessed much more quickly in ‘hot’ tiers, whilst higher magnifications which may be recalled less often may be kept in ‘cold’ storage tiers which take longer to retrieve. This is an attractive characteristic that could potentially reduce overall storage costs, as was highlighted by Google in a recent Pathology Visions presentation. 

Potholes and Obstacles: What are the drawbacks of DICOM for pathology? 

Now we have peered into the ‘pot of gold’ DICOM has to offer, you may ask – why didn’t pathology adopt DICOM from the start?  

The industry is decades old and has historically relied on proprietary formats produced by scanner vendors, because modern digital pathology was only fully incorporated into the DICOM standard in 2010. 

Adoption was not immediate once this was complete for several reasons, the first being that scanner vendors haven’t yet fully embraced the format. Very few scanners are able to natively output DICOM even today.  

Secondly, pathology images can be up to 80 times larger than radiology images (Ashman, 2022) and DICOM header data can make the file 4-5% larger than a proprietary format (Sectra, 2016), effectively amplifying associated storage costs.   

As well as storage issues, an obvious point is that DICOM wasn’t originally built for digital pathology and was created to store black and white radiology images. Although DICOM is adaptable, the development process to improve it requires time and it is still undergoing significant alterations to make it more compatible for digital pathology – to follow its ongoing progress you need only follow DICOM working group 26. 

Getting Over the Hump: Where is DICOM in digital pathology today? 

Adoption of DICOM is currently very low in digital pathology as a whole. There are several reasons for this, including that the penetration of digital pathology in clinical settings is also extremely low. Arguably, ongoing clinical adoption will reveal DICOM’s most prominent benefits related to interoperability and RWD studies. Moreover, as we enter the era of Generative AI, new foundation models will be hungry for harmonised pathology data to support the development of new AI tools.  

Due to non-DICOM formats being more commonly used for WSIs today, image management system (IMS) and AI vendors have had no choice but to facilitate these alternative file formats. Over the years, these vendors have made significant investments into ensuring the non-DICOM formats efficiently run on their systems and have validated AI models for multiple formats. Therefore, in a world where scanners adopt DICOM, the same validation process will need to be repeated and some AI models would be made redundant. Whilst many IMS vendors have become much more open to DICOM over the last two years, AI vendors (which face a higher burden to market entry) are still somewhat reticent.    

Foot on the Pedal: Who are the drivers and passengers? 

As wider healthcare influencers, like radiology vendors and big tech, start to increase their activities in digital pathology, DICOM adoption will be inevitably pushed forward.  Healthcare technology vendors such as Sectra, GE, Agfa Healthcare and Siemens Healthineers are keen to incorporate pathology images into vendor neutral archives (VNAs)..   

In addition to vendor influences, there are reasons as to why clinical and research users may adopt DICOM. Table 2 summarises this. 

Table 2: A summary of various users in digital pathology and drivers and barriers behind usage.

The Final Stretch: How long will it take?  

In summary, the current technical specifications of DICOM may not be optimally suited for digital pathology today, but with the flexibility and backward compatible nature of the format, there is potential for adaptation to better support pathology in the near-term. When weighed alongside the benefits associated with leveraging existing infrastructure and enabling RWD studies, adoption of the standard poses much greater benefits than other available formats. 

Although the exact timeline is unclear, destination DICOM in pathology is inevitable.  


Ashman, K., Zhuge, H., Shanley, E., Fox, S., Halat, S., Sholl, A., Summa, B. (2022). Whole slide image data utilization informed by digital diagnosis patterns. Journal of Pathology Informatics. 13(100113). [Online]. Available at: [Accessed 22 November 2023]. 

Clunie, D A. (2021). DICOM Format and Protocol Standardization—A Core Requirement for Digital Pathology Success. Toxicologic Pathology. 49(4), pp.738-749. 

Hager, S. (2016). Introduction to the DICOM standard for digital pathology and its importance for workflow efficiency. [Online]. Last Updated: 8 March 2016. Available at: [Accessed 27 November 2023]. 

Related Research  

Digital Pathology Market Intelligence Service – World – 2023 

Signify Research’s Market Intelligence Service provides a rolling 12-month coverage of the global Digital Pathology market. The service is composed of four deliverables, as shown below.  This core market update, the first of four publications included as a part of the service, builds upon five years of previous research, and will enable you to: 

  • Inform product investment and business strategy 
  • Evaluate the ever-changing competitive landscape to assess the impact of associations and select potential partners 
  • Acquire a holistic view of the nuances between different pathology research and clinical markets 
  • Understand adjacent markets such as enterprise imaging, laboratory information systems and the influence these will have on Digital Pathology  

For any further questions, or samples of the service contents, please contact the Alexandra Bream, author of this insight, or Imogen Fitt the lead author for the service.  

About Alexandra Bream 

Alex joined Signify research in 2023 as a market analyst in the diagnostics and life sciences area. In summer 2023, Alex graduated from the University of Birmingham with a first-class degree in Biochemistry. At University Alex was the president for the Women in Science and Engineering society and is a big advocate for this. In Alex’s spare time she likes cooking and enjoys travelling. 

About Imogen Fitt 

Imogen joined Signify in 2018 as part of the Healthcare IT team. She holds a 1st class Biomedical Sciences degree from the University of Warwick where her studies included molecular biology and pharmacology. Since joining the team Imogen has studied the medical imaging software and hardware markets and is now expanding Signify Research’s Diagnostics and Lifesciences coverage. 

About the Diagnostics and Lifesciences Team 

The Diagnostics and Lifesciences team provides market intelligence and detailed insights on the multiple healthcare technology markets where the clinical world intersects with the preclinical. Our areas of coverage include digital pathology, laboratory information systems, clinical Real-World Data (cRWD) platforms, oncology information systems, tumour board software, oncology decision support software and radiotherapy IT. Each report provides a data-centric and global outlook of its markets with granular country-level insights. Our research process blends primary data collected from in-depth interviews with healthcare professionals and technology vendors, to provide a balanced and objective view of the market.  

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Signify Research provides healthtech market intelligence powered by data that you can trust. We blend insights collected from in-depth interviews with technology vendors and healthcare professionals with sales data reported to us by leading vendors to provide a complete and balanced view of the market trends. Our coverage areas are Medical Imaging, Clinical Care, Digital Health, Diagnostic and Lifesciences and Healthcare IT. 

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