Evidence map›Paper›PMID 40654002›Full record

ArticleHealth technology assessment (Winchester, England)2025

Variation within and between digital pathology and light microscopy for the diagnosis of histopathology slides: blinded crossover comparison study.

David Rj Snead, Ayesha S Azam, Jenny Thirlwall, Peter Kimani, Louise Hiller, Adam Bickers, Clinton Boyd, David Boyle, David Clark, Ian Ellis and 20 more

Abstract readMulticenter StudyComparative Study
In one paragraph

Article in Health technology assessment (Winchester, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

30 authors.

David Rj SneadHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0000-0002-0766-9650
Ayesha S AzamHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0000-0003-2681-8153
Jenny ThirlwallWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0009-0006-5587-5180
Peter KimaniWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0001-8200-3173
Louise HillerWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0001-8538-9163
Adam BickersPathlinks, Northern Lincolnshire and Goole NHS Foundation Trust, Lincoln, UK.ORCID 0009-0005-0153-9643
Clinton BoydInstitute of Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK.ORCID 0000-0002-3138-6220
David BoyleInstitute of Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK.ORCID 0000-0003-3352-5092
David ClarkHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0002-1575-8119
Ian EllisHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0001-5292-8474
Kishore GopalakrishnanHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0000-0003-0459-6967
Mohammad IlyasHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0001-7949-7504
Paul KellyInstitute of Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK.ORCID 0000-0002-4350-6998
Maurice LoughreyInstitute of Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK.ORCID 0000-0001-8424-1765
Desley NeilDepartment of Cellular Pathology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.ORCID 0000-0001-9800-6811
Emad RakhaHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0002-5009-5525
Ian Sd RobertsDepartment of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID 0000-0002-4885-7957
Shatrughan SahHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0009-0005-8299-8998
Maria SoaresDepartment of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID 0000-0001-6231-8987
YeeWah TsangHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0009-0000-3147-6712
Manuel Salto-TellezCentre for Public Health, Queen's University, Belfast, Northern Ireland, UK.ORCID 0000-0001-8586-282X
Helen HigginsWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0002-7095-4542
Donna HoweWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0002-8363-8127
Abigail TakyiHistopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID 0000-0003-2696-6148
Yan ChenHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0003-3107-7898
Agnieszka IgnatowiczInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.ORCID 0000-0002-5863-0828
Jason MadanWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0003-4316-1480
Henry NwankwoWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0001-7401-1923
George PartridgeHistopathology Department, Nottingham University Hospital NHS Trust, Nottingham, UK.ORCID 0000-0002-0832-0725
Janet DunnWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0001-7313-4446

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital pathology refers to the conversion of histopathology slides to digital image files for examination on computer workstations as opposed to conventional microscopes. Prior to adoption, it is important to demonstrate pathologists provide equivalent reports when using digital pathology in comparison to bright-field and immunofluorescent light microscopy, the current standard of care. Objective: A multicentre comparison of digital pathology with light microscopy for reporting of histopathology slides, measuring variation within and between pathologists on both modalities. Design: A blinded crossover 2000-case study estimating clinical management concordance (identical diagnoses plus differences not affecting patient management). Each sample was assessed twice by four pathologists (once using light microscopy, once using digital pathology, the order randomly assigned and a 6-week gap between viewings). Random-effects logistic regression models, including crossed random-effects terms for case and pathologist, estimated percentage clinical management concordance. Findings were interpreted with reference to 98.3% concordance (Azam AS, Miligy IM, Kimani PKU, Maqbool H, Hewitt K, Rajpoot NM, Snead DRJ. Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis. Setting: Sixteen consultant pathologists, four for each specialty, from six National Health Service laboratories. Experience ranged from 3 to 35 years. Some were early adopters of digital pathology, but the majority were new to digital pathology. Interventions: Eight viewings per sample (four pathologists with light microscopy and with digital pathology), culminating in a consensus ground truth, enabling measurement of agreement within and between readers. Samples enrolled reflected routine practice, included cancer screening biopsies, and were enriched for areas of difficulty [e.g. dysplasia (7, 10, 11)]. State-of-the-art digital pathology equipment designed for diagnosis, and holding either Conformité Européene or Food and Drug Administration approval, was used. Main outcome: Intra-pathologist variation between reports issued on digital pathology and light microscopy, inter-pathologist variation against ground-truth diagnosis using light microscopy and digital pathology. Secondary outcomes: Pathologist-recorded reporting times, along with their confidence in diagnosis, analysis of eye-tracking evaluating examination techniques, and a qualitative study examining attitudes of pathologists and laboratory staff to digital pathology adoption. Results: Two thousand and twenty-four cases (608 breast, 607 gastrointestinal, 609 skin, 200 renal) were recruited, with breast and gastrointestinal including screening samples [207 (34%) breast, 250 (41%) gastrointestinal]. Overall, in light microscopy versus digital pathology comparisons, clinical management concordance levels were 99.95% (95% confidence interval 99.91 to 99.97). Similar results were observed within specialties [breast: 99.40% (95% confidence interval 99.06 to 99.62); gastrointestinal 99.96% (95% confidence interval 99.89 to 99.99); skin 99.99% (95% confidence interval 99.92 to 100.0); renal 99.99% (95% confidence interval 99.57 to 100.0)], and within screening cases [98.96% (95% confidence interval 98.42 to 99.32), breast 96.27% (94.63 to 97.43), gastrointestinal 99.93% (95% confidence interval 99.68 to 99.98)]. Reporting time between digital pathology and light microscopy was similar, but pathologists became faster on digital pathology with familiarity. Pathologists recorded high levels of confidence in their diagnosis with light microscopy, significantly higher than digital pathology. Limitations: Cytology cases and specialty groups outside those tested were not examined. The study used two digital pathology scanning systems. Other systems available on the market were not tested. Conclusions: Clinical management concordance levels between the two modalities exceed the reference 98.3% in breast, gastrointestinal, skin and renal specialties, and pooled breast and large bowel cancer screening cases. Subgroup analysis of clinically significant differences revealed a range of differences including areas where interobserver variability is known to be high, which were distributed between reads performed with both platforms and without apparent trends to either. Future work: The use of digital pathology for cytology samples remains an area for further research. Study registration: This study is registered as ISRCTN14513591. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/84/07) and is published in full in

Indexed as

MicroscopyPathology, ClinicalCross-Over StudiesHumansObserver VariationDIAGNOSISDIGITAL IMAGINGDIGITAL PATHOLOGYDISCORDANCEVALIDATIONWHOLE SLIDES IMAGE

Identifiers

PMID40654002
PMCPMC12278374

What Socratic holds

Textmetadata
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 Socratic graph.