Evidence map›Paper›PMID 35039452›Full record

ArticleJournal of clinical pathology2023

Faster than light (microscopy): superiority of digital pathology over microscopy for assessment of immunohistochemistry.

Emily Clarke, Daniel Doherty, Rebecca Randell, Jonathan Grek, Rhys Thomas, Roy A Ruddle, Darren Treanor

Open access · hybridAbstract read
In one paragraph

Article in Journal of clinical pathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.3field-weighted citation impact, top 10% of its field
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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. The evolving role of DICOM in digital pathology.Journal of pathology informatics · 2026
    Review
  4. The patient matters: a roundtable discussion on pathology in the era of digitization and AI.Virchows Archiv : an international journal of pathology · 2026
    Article
  5. Digital transformation of pathology - the European Society of Pathology expert opinion paper.Virchows Archiv : an international journal of pathology · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
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

7 authors at 3 institutions in 2 countries.

Emily ClarkeDivision of Pathology and Data Analytics, University of Leeds, Leeds, UK e.l.clarke@leeds.ac.uk.ORCID http://orcid.org/0000-0001-7106-9898
Daniel DohertyDivision of Pathology and Data Analytics, University of Leeds, Leeds, UK.
Rebecca RandellFaculty of Health Studies, University of Bradford, Bradford, UK.
Jonathan GrekNorthern Ontario School of Medicine, Thunder Bay, Ontario, Canada.
Rhys ThomasDivision of Pathology and Data Analytics, University of Leeds, Leeds, UK.
Roy A RuddleSchool of Computing and Leeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Darren TreanorDivision of Pathology and Data Analytics, University of Leeds, Leeds, UK.
University of Leeds · GBNOSM University · CAUniversity of Bradford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsDigital pathology offers the potential for significant benefits in diagnostic pathology, but currently the efficiency of slide viewing is a barrier to adoption. We hypothesised that presenting digital slides for simultaneous viewing of multiple sections of tissue for comparison, as in those with immunohistochemical panels, would allow pathologists to review cases more quickly.

methodsNovel software was developed to view synchronised parallel tissue sections on a digital pathology workstation. Sixteen histopathologists reviewed three liver biopsy cases including an immunohistochemical panel using the digital microscope, and three different liver biopsy cases including an immunohistochemical panel using the light microscope. The order of cases and interface was fully counterbalanced. Time to diagnosis was recorded and mean times are presented as data approximated to a normalised distribution.

resultsMean time to diagnosis was 4 min 3 s using the digital microscope and 5 min 24 s using the light microscope, saving 1 min 21 s (95% CI 16 s to 2 min 26 s; p=0.02), using the digital microscope. Overall normalised mean time to diagnosis was 85% on the digital pathology workstation compared with 115% on the microscope, a relative reduction of 26%.

conclusionsWith appropriate interface design, it is quicker to review immunohistochemical slides using a digital microscope than the conventional light microscope, without incurring any major diagnostic errors. As digital pathology becomes more integrated with routine clinical workflow and pathologists increase their experience of the technology, it is anticipated that other tasks will also become more time-efficient.

Indexed as

Image Processing, Computer-AssistedMicroscopyHumansImmunohistochemistryPathologistsSoftwarecomputer systemsdiagnostic techniques and proceduresimmunohistochemistrypathologysurgical

Identifiers

PMID35039452
PMCPMC10176378
OpenAlexW4205819613

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.