Evidence map›Paper›PMID 41318716›Full record

ReviewPathologie (Heidelberg, Germany)2026

[Digital, DICOM, diagnostics-unity over chaos : Data communication in digital pathology].

Christoph Blattgerste, Maximilian Legnar, Cleo-Aron Weis

Abstract readReviewEnglish Abstract
In one paragraph

Review in Pathologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Christoph BlattgersteComputational Pathology Heidelberg, Institut für Pathologie, Uniklinikum Heidelberg, Im Neuenheimer Feld 224, 69120, Heidelberg, Deutschland. christoph.blattgerste@uni-heidelberg.de.
Maximilian LegnarComputational Pathology Heidelberg, Institut für Pathologie, Uniklinikum Heidelberg, Im Neuenheimer Feld 224, 69120, Heidelberg, Deutschland.
Cleo-Aron WeisComputational Pathology Heidelberg, Institut für Pathologie, Uniklinikum Heidelberg, Im Neuenheimer Feld 224, 69120, Heidelberg, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digitization of histological specimens enables new computer-assisted analysis and artificial intelligence (AI)-supported diagnostics, but is hampered by a lack of standards. Interoperability between proprietary formats and clinical systems such as the Picture Archiving and Communication System (PACS) or Laboratory Information Systems (LIS) poses a particular challenge. The Digital Imaging and COmmunications in Medicine (DICOM) format, adapted from radiology, offers an open, vendor-independent solution that integrates image data, metadata, and analysis results and enables interoperable exchange. A literature review shows a growing number of publications on digital and computer-assisted pathology, with DICOM increasingly being discussed as a key format. With an open-source, modular Docker pipeline, we demonstrate the practical implementation of DICOM-compliant workflows for storing and visualizing whole slide images and AI results. This creates the basis for standardized, transparent, and trustworthy digital pathology.

Indexed as

Radiology Information SystemsArtificial IntelligenceClinical Laboratory Information SystemsHumansImage Processing, Computer-AssistedComputational pathologyComputer visionData communicationStandardizationWhole slide images

Identifiers

PMID41318716
PMCPMC12852278

What OpenQuestion holds

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LicenceCC BY
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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.