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Subspecialties Histology, Digital and computational pathology, Technology and innovation

Targeting the Forgotten

It is now well recognized that histopathology is facing a challenging future characterized by a global decline in the number of pathologists coupled with an increased diagnostic workload (1, 2). Though compromised service delivery under such pressure seems almost inevitable, help may be at hand.Over the last two decades, major innovations in histopathology have centered on the implementation of digital scanning and whole slide imaging (2). Centers investing in digital pathology have the potential to reap benefits such as streamlined workflows, increased pathologist efficiency, rapid/cheaper second opinions and external consultations, and faster diagnostic turnaround times – all while creating opportunities for remote working (3). These benefits may extend further as the foundation of image-based infrastructures tantalizingly promises to support the development and deployment of artificial intelligence (AI) solutions to lighten the diagnostic burden – the incipient so-called ‘third revolution’ in pathology (4). That said, adoption of digital pathology varies worldwide. In this regard, the UK leads in Europe (5), while other countries, such as the US, lag behind. But what we lack are comprehensive evaluations of the technology’s adoption in the field.

Angie Berwick

Graham Holland

A pathologist-focused agenda?

To date, studies on the acceptability of AI and related technologies have focused on the opinions of histopathologist end-users (6), while neglecting the views of the end-beneficiaries: patients. This mindset may partly reflect the clinical immaturity of these technologies and the fact that patients typically have very limited interactions with pathology services, as opposed to other clinical disciplines where there is a greater stakeholder oversight of public and patient involvement (PPI). Nevertheless, given the cross-sectional relevance of pathology and its system-critical impact on other clinical disciplines (2), such involvement is key.

Another contributing factor may be differences in healthcare systems, for which the UK and US offer markedly contrasting examples. In the former, the National Health Service (NHS) represents a government-funded, single payor system, wherein patients often have minimal involvement in diagnostic processes, with many being unaware of the clinical role of histopathologists. By contrast, the US system has a fragmented reimbursement pathway where patient management is heavily influenced by insurance coverage. In the US, the risk for many is that reimbursement strategies and policies may dictate diagnostic analyses performed.

Similarly, the understanding of PPI is also subject to national interpretation. In the UK, PPI depends on willing volunteers representing a disease area (such as cancer), who are driven by a desire to help patients gain knowledge of complex medical matters, which informs their input into their own clinical management decisions and personalized treatment options. Moreover, it aims to offer a patient-centric view for researchers investigating novel diagnostic and treatment solutions, and their subsequent clinical adoption.

In the US, patient advocacy is driven by organizations that lobby on behalf of communities with more specific disease types (for example, breast cancer). Their activities are guided by a combination of funded research and philanthropic donation-based opportunities, community need, government and regulatory lobbying, and the provision of knowledge for educational services, patients and caregivers. PPI involvement (typically by the Patient and Family Advisory Council, PFAC) extends to healthcare providers, payors, and pharmaceutical companies, and provides evidence of involvement of patients and caregivers in their programs. Despite these differences, the goal of both UK and US-based patient advocacy organizations should align in offering patients faster, reliable and, ideally, more affordable diagnoses without unduly burdening diagnostic services.

Brad Power

Thinking ahead: involving patients

In recent years, the UK in particular has witnessed a concerted effort in adopting a holistic, patient-centered approach in healthcare and service user-led research in the wake of changing patient attitudes to established biomedical authority – notably, following a number of well publicized medical scandals (7). There are, as such, founding principles underpinning the legitimacy of PPI centered on moral, policy-based and, in the case of research, methodological grounds. As such, empowering patients has been enshrined in the UK’s National Institute for Health and Care Excellence (NICE) PPI policy’s progressive key principles. First, lay people and their advocates should have opportunities to contribute to developing guidance, advice, and quality standards with a view to supporting their implementation. Second, this contribution should inform NICE’s guidance and ensure that products are focused and relevant to those stakeholders most directly affected by its recommendations (8).

The benefits of PPI involvement are tangible, with various studies demonstrating how patients can effectively contribute to service improvement as well as better health outcomes and patient experience (7, 9, 10, 11, 12). This success has translated into NHS England’s commitment to empower patients, their caregivers, and advocates to participate in making informed decisions about their individual care and treatment (13).

Actively considering PPI engagement in the digital pathology space, especially regarding AI and its potential clinical adoption, now seems very timely. From our ongoing UK-based studies, we understand that patients and their advocates are not only increasingly cognizant of the potential personal and clinical benefits of such technologies; they are also prepared to embrace their clinical adoption, albeit as diagnostic adjuncts combined with histopathologist input. This viewpoint may offer a comforting message to any clinicians concerned that they may be at risk of being replaced by diagnostic algorithms.

Nic Orsi

A future framework

The benefits of PPI engagement for validating patient support in research and clinical utility evaluations are easily conceived and can offset any practical issues pertaining to establishing advocacy groups – and the same applies in the adoption of AI in digital pathology. In an ideal setting, PPI should be incorporated at all stages of research (such as grant applications, ethics review, publication), clinical evaluation, cost-to-benefit analyses, and clinical adoption. Each stage should provide opportunities for iterative feedback – a model that the UK, at least, is increasingly moving toward. Importantly, such an interactive, inclusive, and transparent system will build trust with both end-users and beneficiaries. And just as importantly, by giving patients a voice in cutting- edge medical advances, we ensure that the research/clinical adoption of these new technologies remain grounded in achieving a positive impact on patients and their advocates. Active, engaged, and educated patients get better outcomes – and so, regardless of whether institutions listen, patients should speak more.

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  1. B Märkl et al., “Number of pathologists in Germany: comparison with European countries, USA, and Canada,” Virchows Archiv, 478, 335 (2021). PMID: 32719890.
  2. L Pantanowitz, “Twenty years of digital pathology: an overview of the road travelled, what is on the horizon, and the emergence of vendor-neutral archives,” J Pathol Inform, 9, 40 (2018). PMID: 30607307.
  3. BJ Williams et al., “Future-proofing pathology: the case for clinical adoption of digital pathology,” J Clin Pathol, 70, 1010 (2017). PMID: 28780514.
  4. M Salto-Tellez et al., “Artificial intelligence-the third revolution in pathology,” Histopathology, 74, 372 (2019). PMID: 30270453.
  5. BJ Williams et al., “Digital pathology access and usage in the UK: results from a national survey on behalf of the National Cancer Research Institute’s CM-Path initiative,” J Clin Pathol, 2018, 71, 463 (2018).
  6. J Drogt et al., “Integrating artificial intelligence in pathology: a qualitative interview study of users’ experiences and expectations,” Mod Pathol, 35, 1540 (2022). PMID: 35927490.
  7. P Wilson et al., “ReseArch with Patient and Public invOlvement: a RealisT evaluation - the RAPPORT study,” Health Serv Deliv Res, 3 (2015). PMID: 26378332.
  8. National Institute for Health and Care Excellence, “Patient and public involvement policy” (2023). Available at:
  9. S de Souza et al., “Patient involvement in rheumatology outpatient service design and delivery: a case study,” Health Expect, 20, 508 (2017). PMID: 27345769.
  10. T Jackson et al., “Patient and public involvement in research: from tokenistic box ticking to valued team members,” BMC Med, 18, 79 (2020). PMID: 32279658.
  11. AM Biggane et al., “PPI in research: a reflection from early stage researchers,” Research Involvement and Engagement, 5, 35 (2019). PMID: 31832239.
  12. C Longoni, CK Morewedge, “AI can outperform doctors. So why don’t patients trust it?” (2019). Available at:
  13. NHS England, “Involving people in their own care” (2022). Available at:
About the Authors
Angelene Berwick

PhD student and Senior Research Technician at University of Leeds, UK.

Graham Holland

Retired infrastructure asset manager and a chartered engineer and chartered geologist. He is a member of the Leeds Teaching Hospitals Trust's Cardiovascular and Cancer PPI, Leeds, UK.

Bradford Power

Process innovator and the founder of CancerHackerLab, based in the Boston area, Massachusetts, USA.

Nicolas M. Orsi

Chief Pathologist at 4D Path, Newton, Massachusetts, USA, and Clinician Scientist in Histopathology, University of Leeds, Leeds, UK.

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