The use of digital pathology and image analysis in clinical trials

Pell, R., Oien, K. , Robinson, M., Pitman, H., Rajpoot, N., Rittscher, J., Snead, D. and Verrill, C. (2019) The use of digital pathology and image analysis in clinical trials. Journal of Pathology: Clinical Research, 5(2), pp. 81-90. (doi: 10.1002/cjp2.127) (PMID:30767396) (PMCID:PMC6463857)

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Abstract

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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Oien, Professor Karin
Authors: Pell, R., Oien, K., Robinson, M., Pitman, H., Rajpoot, N., Rittscher, J., Snead, D., and Verrill, C.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cancer Sciences
Journal Name:Journal of Pathology: Clinical Research
Publisher:Wiley
ISSN:2056-4538
ISSN (Online):2056-4538
Published Online:25 March 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Journal of Pathology: Clinical Research 5:81-90
Publisher Policy:Reproduced under a creative commons licence

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