Evidence map›Paper›PMID 36525050›Full record

ArticleAbdominal radiology (New York)2023

Lexicon for adrenal terms at CT and MRI: a consensus of the Society of Abdominal Radiology adrenal neoplasm disease-focused panel.

Daniel I Glazer, William W Mayo-Smith, Erick M Remer, Elaine M Caoili, Julie H Song, Myles T Taffel, James T Lee, Olga R Brook, Atul B Shinagare, Michael A Blake and 5 more

Abstract readConsensus Statement
PubMed Publisher
In one paragraph

Article in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

15 authors.

Daniel I GlazerDepartment of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA. dglazer@bwh.harvard.edu.ORCID 0000-0002-1547-5215
William W Mayo-SmithDepartment of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
Erick M RemerImaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH, 44195, USA.
Elaine M CaoiliDepartment of Radiology, Michigan Medicine, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA.
Julie H SongDepartment of Radiology, Warren Alpert School of Medicine, Brown University, 222 Richmond Street, Providence, RI, 02903, USA.
Myles T TaffelDepartment of Radiology, New York University Grossman School of Medicine, 660 First Avenue, 3rd Floor, New York, NY, 10016, USA.
James T LeeDepartment of Radiology, University of Kentucky, 800 Rose St, HX 315, Lexington, KY, 40536, USA.
Olga R BrookDepartment of Radiology, Harvard Medical School, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, 02215, USA.
Atul B ShinagareDepartment of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
Michael A BlakeDepartment of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA, 02114, USA.
Khaled M ElsayesDepartment of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX, 77030, USA.
Nicola SchiedaDepartment of Radiology, University of Ottawa, 501 Smyth Road, Ottawa, ON, Canada.
Antonio C WestphalenDepartment of Radiology, Urology, and Radiation Oncology, University of Washington, 1959 N.E. Pacific St, Seattle, WA, USA.
Michael J CampbellDepartment of Surgery, Davis Medical Center, University of California, 2279 45th Street, Sacramento, CA, 95817, USA.
Michael T CorwinDepartment of Radiology, Davis Medical Center, University of California, 4860 Y St, Ste 3100, Sacramento, CA, 95817, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSubstantial variation in imaging terms used to describe the adrenal gland and adrenal findings leads to ambiguity and uncertainty in radiology reports and subsequently their understanding by referring clinicians. The purpose of this study was to develop a standardized lexicon to describe adrenal imaging findings at CT and MRI.

methodsFourteen members of the Society of Abdominal Radiology adrenal neoplasm disease-focused panel (SAR-DFP) including one endocrine surgeon participated to develop an adrenal lexicon using a modified Delphi process to reach consensus. Five radiologists prepared a preliminary list of 35 imaging terms that was sent to the full group as an online survey (19 general imaging terms, 9 specific to CT, and 7 specific to MRI). In the first round, members voted on terms to be included and proposed definitions; subsequent two rounds were used to achieve consensus on definitions (defined as ≥ 80% agreement).

resultsConsensus for inclusion was reached on 33/35 terms with two terms excluded (anterior limb and normal adrenal size measurements). Greater than 80% consensus was reached on the definitions for 15 terms following the first round, with subsequent consensus achieved for the definitions of the remaining 18 terms following two additional rounds. No included term had remaining disagreement.

conclusionExpert consensus produced a standardized lexicon for reporting adrenal findings at CT and MRI. The use of this consensus lexicon should improve radiology report clarity, standardize clinical and research terminology, and reduce uncertainty for referring providers when adrenal findings are present.

Indexed as

Adrenal Gland NeoplasmsGastrointestinal DiseasesRadiologyHumansMagnetic Resonance ImagingTomography, X-Ray ComputedAdrenal incidentalomaAdrenal noduleCTLexiconMRI

Identifiers

PMID36525050

What OpenQuestion holds

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Registered trials

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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.