Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice.

The use of artificial intelligence will transform clinical practice over the next decade and the early impact of this will likely be the integration of image analysis and machine learning into routine histopathology. In the UK and around the world, a digital revolution is transforming the reporting practice of diagnostic histopathology and this has sparked a proliferation of image analysis software tools. While this is an exciting development that could discover novel predictive clinical information and potentially address international pathology workforce shortages, there is a clear need for a robust and evidence-based framework in which to develop these new tools in a collaborative manner that meets regulatory approval. With these issues in mind, the NCRI Cellular Molecular Pathology (CM-Path) initiative and the British In Vitro Diagnostics Association (BIVDA) have set out a roadmap to help academia, industry, and clinicians develop new software tools to the point of approved clinical use. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

CM-Path Molecular Diagnostics Forum-consensus statement on the development and implementation of molecular diagnostic tests in the United Kingdom.

BACKGROUND: Pathology has evolved from a purely morphological description of cellular alterations in disease to our current ability to interrogate tissues with multiple 'omics' technologies. By utilising these techniques and others, 'molecular diagnostics' acts as the cornerstone of precision/personalised medicine by attempting to match the underlying disease mechanisms to the most appropriate targeted therapy. METHODS: Despite the promises of molecular diagnostics, significant barriers have impeded its widespread clinical adoption. Thus, the National Cancer Research Institute (NCRI) Cellular Molecular Pathology (CM-Path) initiative convened a national Molecular Diagnostics Forum to facilitate closer collaboration between clinicians, academia, industry, regulators and other key stakeholders in an attempt to overcome these. RESULTS: We agreed on a consensus 'roadmap' that should be followed during development and implementation of new molecular diagnostic tests. We identified key barriers to efficient implementation and propose possible solutions to these. In addition, we discussed the recent reconfiguration of molecular diagnostic services in NHS England and its likely impacts. CONCLUSIONS: We anticipate that this consensus statement will provide practical advice to those involved in the development of novel molecular diagnostic tests. Although primarily focusing on test adoption within the United Kingdom, we also refer to international guidelines to maximise the applicability of our recommendations.

The use of digital pathology and image analysis in clinical trials.

Digital pathology and image analysis potentially provide greater accuracy, reproducibility and standardisation of pathology-based trial entry criteria and endpoints, alongside extracting new insights from both existing and novel features. Image analysis has great potential to identify, extract and quantify features in greater detail in comparison to pathologist assessment, which may produce improved prediction models or perform tasks beyond manual capability. In this article, we provide an overview of the utility of such technologies in clinical trials and provide a discussion of the potential applications, current challenges, limitations and remaining unanswered questions that require addressing prior to routine adoption in such studies. We reiterate the value of central review of pathology in clinical trials, and discuss inherent logistical, cost and performance advantages of using a digital approach. The current and emerging regulatory landscape is outlined. The role of digital platforms and remote learning to improve the training and performance of clinical trial pathologists is discussed. The impact of image analysis on quantitative tissue morphometrics in key areas such as standardisation of immunohistochemical stain interpretation, assessment of tumour cellularity prior to molecular analytical applications and the assessment of novel histological features is described. The standardisation of digital image production, establishment of criteria for digital pathology use in pre-clinical and clinical studies, establishment of performance criteria for image analysis algorithms and liaison with regulatory bodies to facilitate incorporation of image analysis applications into clinical practice are key issues to be addressed to improve digital pathology incorporation into clinical trials.