Evidence map›Paper›PMID 37387439›Full record

ReviewPathologica2023

The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board.

Alessandro Caputo, Vincenzo L'Imperio, Francesco Merolla, Ilaria Girolami, Eleonora Leoni, Vincenzo Della Mea, Fabio Pagni, Filippo Fraggetta

Open access · diamondAbstract readReview
In one paragraph

Review in Pathologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.Virchows Archiv : an international journal of pathology · 2025
    Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. 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

8 authors at 5 institutions in 2 countries.

Alessandro CaputoDepartment of Pathology, Ruggi University Hospital, Salerno, Italy.
Vincenzo L'ImperioDepartment of Medicine and Surgery, Pathology, University of Milan-Bicocca, IRCCS Fondazione San Gerardo dei Tintori, Monza, Italy.
Francesco MerollaDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, Campobasso, Italy.
Ilaria GirolamiDepartment of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy; Lehrkrankenhaus der Paracelsus Medizinischen Privatuniversität.
Eleonora LeoniPathology Unit, Busto Arsizio Hospital, Busto Arsizio, Italy.
Vincenzo Della MeaDepartment of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy.
Fabio PagniDepartment of Medicine and Surgery, Pathology, University of Milan-Bicocca, IRCCS Fondazione San Gerardo dei Tintori, Monza, Italy.
Filippo FraggettaPathology Unit, Gravina Hospital Caltagirone ASP, Catania, Italy.
University of Milano-Bicocca · ITOspedale di Bolzano · ITOspedale di Circolo di Busto Arsizio · ITUniversity of Molise · ITUniversity of Udine · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered. Methods: On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education. Results: Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides. Conclusion: Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care.

Indexed as

Health PersonnelPathologistsHumansartificial intelligencecomputational pathologydigital pathologyeducation

Identifiers

PMID37387439
PMCPMC10462988
OpenAlexW4382632661

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.