Evidence map›Paper›PMID 30767396›Full record

ArticleThe journal of pathology. Clinical research2019

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

Robert Pell, Karin Oien, Max Robinson, Helen Pitman, Nasir Rajpoot, Jens Rittscher, David Snead, Clare Verrill, UK National Cancer Research Institute (NCRI) Cellular-Molecular Pathology (CM-Path) quality assurance working group

Abstract read
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In one paragraph

Article in The journal of pathology. Clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Digital Pathology in Hematopathology: From Vision to Deployment.International journal of laboratory hematology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Robert PellNuffield Department of Surgical Sciences, University of Oxford, and Oxford NIHR Biomedical Research Centre, Oxford, UK.ORCID 0000-0003-2371-0403
Karin OienInstitute of Cancer Sciences - Pathology, University of Glasgow, Glasgow, UK.
Max RobinsonCentre for Oral Health Research, Newcastle University, Newcastle upon Tyne, UK.
Helen PitmanStrategy and Initiatives, National Cancer Research Institute, London, UK.
Nasir RajpootDepartment of Computer Science, University of Warwick, Warwick, UK.
Jens RittscherNuffield Department of Surgical Sciences, University of Oxford, and Oxford NIHR Biomedical Research Centre, Oxford, UK.
David SneadDepartment of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK.
Clare VerrillNuffield Department of Surgical Sciences, University of Oxford, and Oxford NIHR Biomedical Research Centre, Oxford, UK.
UK National Cancer Research Institute (NCRI) Cellular-Molecular Pathology (CM-Path) quality assurance working group

Funding

Cancer Research UK 25351Department of Health HTA/17/84/07Medical Research Council MR/N005813/1Medical Research Council MR/N005872/1
6 · The paper itself

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.

Indexed as

Image Interpretation, Computer-AssistedImage Processing, Computer-AssistedPathologistsTelepathologyAlgorithmsClinical Trials as TopicHumansMicroscopycomputerised image analysisdigital image analysisdigital microscopy

Identifiers

PMID30767396
PMCPMC6463857

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.