The use of digital pathology and image analysis in clinical trials

• Published in: The journal of pathology. Clinical research Vol. 5; no. 2; pp. 81 - 90
• Main Authors: Pell, Robert, Oien, Karin, Robinson, Max, Pitman, Helen, Rajpoot, Nasir, Rittscher, Jens, Snead, David, Verrill, Clare, Driskell, Owen J, Hall, Andy, James, Jacqueline, Jones, Louise J, Craig, Clare, Sloan, Philip, Thomas, Gareth J, Elliott, Philip, Cheang, Maggie, Rodriguez‐Justo, Manuel, Rees, Gabrielle, Salto‐Tellez, Manuel, West, Nicholas P, Mirabile, Ilaria, Howlett, Emily, Stevenson, Laura, da Silva, Maria, Hartridge‐Lambert, Sidonie, Beecham, Joseph M, Traub, Stephanie, Katugampola, Sidath, Blagden, Sarah, Morden, James
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.04.2019; Wiley
• Subjects: Algorithms; Artificial intelligence; Automation; Biology; Clinical trials; Clinical Trials as Topic; Colorectal cancer; computerised image analysis; Deep learning; Dentistry; digital image analysis; digital microscopy; Humans; Image Interpretation, Computer-Assisted - methods; Image processing; Image Processing, Computer-Assisted - methods; Laboratories; Machine learning; Medical research; Medicine; Microscopy; Morphology; Morphometry; Open source software; Pathologists; Pathology; Prediction models; Public domain; Quality control; Regulation; Regulatory agencies; Regulatory approval; Studies; Telepathology - methods; Tumors; United Kingdom > UK; United States > US; computerised image analysis; digital image analysis; digital microscopy
• ISSN: 2056-4538; 2056-4538
• DOI: 10.1002/cjp2.127

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.