Evidence map›Paper›PMID 42782329›Full record

ReviewAbdominal radiology (New York)2026

Decoding the image: finding diagnostic signals in multi-modality abdominal artifacts.

Gabrielle Dickerson, Joseph Chirico, Andreas Loening, Jade J Wong-You-Cheong, Barton Frederick Lane, Florence Xini Doo

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 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

6 authors.

Gabrielle DickersonDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA.
Joseph ChiricoDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA.
Andreas LoeningDepartment of Radiology, Stanford University, Palo Alto, USA.ORCID https://orcid.org/0000-0003-3316-7467
Jade J Wong-You-CheongDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA.
Barton Frederick LaneDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA.ORCID http://orcid.org/0000-0002-7088-1910
Florence Xini DooDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA. fdoo@umd.edu.ORCID http://orcid.org/0000-0001-6519-5222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging artifacts and related physiologic, pathologic, and iatrogenic phenomena are common across every radiology modality and often provide useful diagnostic information. This pictorial essay introduces a structured, four-category framework for recognizing and interpreting abdominal artifacts and related phenomena (ARPs): (1) the "Virtual Biopsy," encompassing ARPs that aid in characterizing tissue composition and pathology; (2) the "Flowmeter," representing ARPs that provide insight into physiologic or pathologic flow states; (3) the "Signpost," describing ARPs that direct attention toward or mimic the underlying pathology; and (4) the "Tiebreaker," reviewing ARPs that prompt multi-modality correlation or other problem-solving to reach the correct diagnosis. Representative clinical cases illustrate each category across medical imaging modalities. This framework provides a systematic approach to incorporating ARPs into diagnostic reasoning.

Indexed as

Abdominal imagingDiagnostic errorsImage interpretationImaging artifactsMultimodality imagingRadiology education

Identifiers

What OpenQuestion holds

Textmetadata
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.