Evidence map›Paper›PMID 33033654›Full record

ArticleJournal of pathology informatics2020

A Point-of-Use Quality Assurance Tool for Digital Pathology Remote Working.

Alexander I Wright, Emily L Clarke, Catriona M Dunn, Bethany J Williams, Darren E Treanor, David S Brettle

Open access · goldAbstract read
In one paragraph

Article in Journal of pathology informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 19 citations in OpenAlex.

  1. Considerations for digital pathology displays.Journal of pathology informatics · 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

6 authors at 2 institutions in 1 country.

Alexander I WrightSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
Emily L ClarkeSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
Catriona M DunnSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
Bethany J WilliamsSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
Darren E TreanorSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
David S BrettleSection of Pathology and Data Analytics, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
University of Leeds · GBLeeds Teaching Hospitals NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathology services are facing pressures due to the COVID-19 pandemic. Digital pathology has the capability to meet some of these unprecedented challenges by allowing remote diagnoses to be made at home, during periods of social distancing or self-isolation. However, while digital pathology allows diagnoses to be made on standard computer screens, unregulated home environments may not be conducive for optimal viewing conditions. There is also a paucity of experimental evidence available to support the minimum display requirements for digital pathology. This study presents a Point-of-Use Quality Assurance (POUQA) tool for remote assessment of viewing conditions for reporting digital pathology slides. The tool is a psychophysical test combining previous work from successfully implemented quality assurance tools in both pathology and radiology to provide a minimally intrusive display screen validation task, before viewing digital slides. The test is specific to pathology assessment in that it requires visual discrimination between colors derived from hematoxylin and eosin staining, with a perceptual difference of ±1 delta E (dE). This tool evaluates the transfer of a 1 dE signal through the digital image display chain, including the observers' contrast and color responses within the test color range. The web-based system has been rapidly developed and deployed as a response to the COVID-19 pandemic and may be used by anyone in the world to help optimize flexible working conditions at: http://www. virtualpathology.leeds.ac.uk/res earch/systems/pouqa/.

Indexed as

Digital pathologydisplay validationpsychophysical testquality assuranceremote diagnosis

Identifiers

PMID33033654
PMCPMC7513773
OpenAlexW3042885143

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.