Evidence map›Paper›PMID 33332980›Full record

ArticleThe British journal of radiology2021

Clumped vs non-clumped internal enhancement patterns in linear non-mass enhancement on breast MRI.

Shu Tian Chen, James Covelli, Satoko Okamoto, Bruce L Daniel, Wendy B DeMartini, Debra M Ikeda

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in The British journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

9 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Ultrasound diagnosis of non-mass MRI-detected lesions.Journal of medical ultrasonics (2001) · 2023
    Review
  7. Review
  8. Article
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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

6 authors at 3 institutions in 3 countries.

Shu Tian ChenDepartment of Diagnostic Radiology, Chang-Gung Memorial Hospital, Chiayi, Taiwan.ORCID https://orcid.org/0000-0003-2650-3338
James CovelliDepartment of Radiology, Stanford University School of Medicine, California, United States.
Satoko OkamotoDepartment of Radiology, St. Marianna University School of Medicine, Kawasaki, Japan.
Bruce L DanielDepartment of Radiology, Stanford University School of Medicine, California, United States.
Wendy B DeMartiniDepartment of Radiology, Stanford University School of Medicine, California, United States.
Debra M IkedaDepartment of Radiology, Stanford University School of Medicine, California, United States.
Stanford University · USChiayi Chang Gung Memorial Hospital · TWSt. Marianna University School of Medicine · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare positive predictive values (PPVs) of clumped

methodsWith IRB (Institutional Review Board) approval, we retrospectively reviewed 598 lesions undergoing MRI-VABB from January 2015 to April 2018 that showed linear NME. We reviewed the electronic medical records for MRI-VABB pathology, any subsequent surgery and clinical follow-up. The X

resultsThere were 120/598 (20%) linear NME MRI-VABB lesions with clumped (52/120, 43%)

conclusionsLinear NME showed malignancy in 21% of our series. Linear NME with clumped or non-clumped internal enhancement patterns, regardless of lesion size, might need to undergo MRI-VABB in appropriate populations. ADVANCES IN KNOWLEDGE: Evaluation of linear NME lesions on breast MRI focuses especially on internal enhancement pattern.

Indexed as

AdultAgedAged, 80 and overBreastBreast NeoplasmsFemaleHumansImage-Guided BiopsyMagnetic Resonance ImagingMiddle AgedRetrospective StudiesVacuum

Identifiers

PMID33332980
PMCPMC7934299
OpenAlexW3112194646

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.