Evidence map›Paper›PMID 33223003›Full record

ReviewRadiologic clinics of North America2021

Abbreviated MR Imaging for Breast Cancer.

Laura Heacock, Alana A Lewin, Hildegard K Toth, Linda Moy, Beatriu Reig

Abstract readReview
In one paragraph

Review in Radiologic clinics of North America, 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
–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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025
    Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. 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

5 authors.

Laura HeacockDepartment of Radiology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA. Electronic address: Laura.Heacock@nyulangone.org.
Alana A LewinDepartment of Radiology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA.
Hildegard K TothDepartment of Radiology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA.
Linda MoyDepartment of Radiology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA.
Beatriu ReigDepartment of Radiology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Christopher M Collins · 2014 to 2026
$19.3M
NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

Breast MR imaging is the most sensitive imaging method for the detection of breast cancer and detects more aggressive malignancies than mammography and ultrasound examination. Despite these advantages, breast MR imaging has low use rates for breast cancer screening. Abbreviated breast MR imaging, in which a limited number of breast imaging sequences are obtained, has been proposed as a way to solve cost and patient tolerance issues while preserving the high cancer detection rate of breast MR imaging. This review discusses abbreviated breast MR imaging, including protocols, multicenter clinical trial results, clinical workflow implementation challenges, and future directions.

Indexed as

BreastBreast NeoplasmsEarly Detection of CancerFemaleHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingReproducibility of ResultsSensitivity and SpecificityAbbreviated MR imagingBreast cancer screeningBreast MR imagingFAST imaging

Identifiers

PMID33223003
PMCPMC8211370

What OpenQuestion holds

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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.