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Comparative Study
. 2025 Jul;29(30):1-75.
doi: 10.3310/SPLK4325.

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

David Rj Snead  1   2 , Ayesha S Azam  1   2 , Jenny Thirlwall  2 , Peter Kimani  2 , Louise Hiller  2 , Adam Bickers  3 , Clinton Boyd  4 , David Boyle  4 , David Clark  5 , Ian Ellis  5   6 , Kishore Gopalakrishnan  1 , Mohammad Ilyas  5   6 , Paul Kelly  4 , Maurice Loughrey  4   7 , Desley Neil  8 , Emad Rakha  5   6 , Ian Sd Roberts  9 , Shatrughan Sah  1 , Maria Soares  9 , YeeWah Tsang  1 , Manuel Salto-Tellez  7   10 , Helen Higgins  2 , Donna Howe  2 , Abigail Takyi  1 , Yan Chen  5 , Agnieszka Ignatowicz  11 , Jason Madan  2 , Henry Nwankwo  2 , George Partridge  5 , Janet Dunn  2
Affiliations
Comparative Study

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

David Rj Snead et al. Health Technol Assess. 2025 Jul.

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. J Clin Pathol 2021;74:448-55. https://doi.org/10.1136/jclinpath-2020-206764).

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 Health Technology Assessment; Vol. 29, No. 30. See the NIHR Funding and Awards website for further award information.

Keywords: DIAGNOSIS; DIGITAL IMAGING; DIGITAL PATHOLOGY; DISCORDANCE; VALIDATION; WHOLE SLIDES IMAGE.

Plain language summary

Pathologists use a microscope to examine tissue samples, called light microscopy. This enables them to make the diagnosis, give information on treatment and provide prognosis to clinicians. The reports made by pathologists are interpretations of what the slides are showing, and this can be extremely difficult, so differences in interpretation between pathologists occur quite often. Asking colleagues’ opinion on cases is one of the best ways of recognising and reducing these differences in interpretation. Digital pathology is a process of converting microscope slides to computer image files. Digital pathology allows some advantages to pathologists, namely: to move cases easily between pathologists, for example to get a case seen by the next available pathologist who can report it, to view the cases at any location, for example work from home or report cases for a distant laboratory with a shortage of pathologists, to confer easily with multiple colleagues on difficult cases, and to rapidly check diagnoses made on previous samples the patient may have had. As a result, digital pathology could potentially lead to safer more efficient working. In order to use digital pathology in practice, we need to know pathologists produce equivalent reports as compared to light microscopy. This study compared light microscopy with digital pathology in examining 2024 samples from breast, gastrointestinal, including cancer screening samples, skin and kidney. Most samples recruited (80%) were routine, but at least 20% of cases were challenging cases. Pathologists worked in teams examining the same series of cases twice once through light microscopy and once through digital pathology with viewings separated by 6 weeks and the order randomised. Differences in reports were arbitrated to establish if they would have changed treatment (significant) or not (insignificant). Pathologists reviewed all the significant differences to decide the ground truth. Statistical analysis measured the agreement between light microscopy and digital pathology in comparison to a reference point of 98.3% agreement derived from a previous study. The results show an agreement overall of 99.95%. Specialty groups showing: breast 99.4%, gastrointestinal 99.96%, skin 99.99% and renal 99.99%. Cancer screening cases showed overall agreement was 98.96%, and in breast 96.27% and large bowel 99.93%. In comparison to ground truth, the differences between pathologists were similar with light microscopy and digital pathology. Analysis showed the differences detected occurred in entities known to produce differences in interpretation between pathologists. The study shows that pathologists give equivalent diagnoses when using digital pathology as they would using light microscopy. The differences detected are those you would expect to see in any event due to interpretable nature of examining these samples.

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