Evidence map›Paper›PMID 41937992›Full record

ReviewWorld journal of radiology2026

Proposing Incidental-Reporting and Data System: A classification system for incidental findings in radiology.

Nikolaos-Achilleas Arkoudis, Ornella Moschovaki-Zeiger, Christos Koutserimpas, Niki Lama, Georgios Velonakis, Dimitrios Filippiadis, Stavros Spiliopoulos, Nikolaos Kelekis

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nikolaos-Achilleas ArkoudisResearch Unit of Radiology and Medical Imaging, National and Kapodistrian University of Athens, Athens 11528, Attikí, Greece.
Ornella Moschovaki-Zeiger2 Department of Radiology, Attikon University General Hospital, National and Kapodistrian University of Athens, Athens 12462, Attikí, Greece.
Christos KoutserimpasSchool of Health Rehabilitation Sciences, University of Patras, Patra 26504, Dytikí Elláda, Greece.
Niki LamaResearch Unit of Radiology and Medical Imaging, National and Kapodistrian University of Athens, Athens 11528, Attikí, Greece.
Georgios VelonakisResearch Unit of Radiology and Medical Imaging, National and Kapodistrian University of Athens, Athens 11528, Attikí, Greece.
Dimitrios Filippiadis2 Department of Radiology, Attikon University General Hospital, National and Kapodistrian University of Athens, Athens 12462, Attikí, Greece.
Stavros Spiliopoulos2 Department of Radiology, Attikon University General Hospital, National and Kapodistrian University of Athens, Athens 12462, Attikí, Greece.
Nikolaos Kelekis2 Department of Radiology, Attikon University General Hospital, National and Kapodistrian University of Athens, Athens 12462, Attikí, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incidental findings are increasingly common in radiology yet reporting and follow-up remain inconsistent. We introduce Incidental-Reporting and Data System (I-RADS) as a classification system across imaging modalities and anatomical regions. I-RADS aims to improve communication among physicians, standardize recommendations, and promote research. Along with preexisting tools and guidelines, adoption of I-RADS could harmonize the management of incidental findings, improve patient outcomes, and support multicenter studies.

Indexed as

Artificial intelligence in radiologyClassification systemCommunicationData harmonizationData systemIncidental findingsRadiologyResearchStandardizationStructured reporting

Identifiers

PMID41937992
PMCPMC13047575

What OpenQuestion holds

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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.