Evidence map›Paper›PMID 37646814›Full record

ArticleEuropean radiology2023

Breast density and the likelihood of malignant MRI-detected lesions in women diagnosed with breast cancer.

Antti Sassi, Annukka Salminen, Arja Jukkola, Maija Tervo, Niina Mäenpää, Saara Turtiainen, Leena Tiainen, Timo Liimatainen, Teemu Tolonen, Heini Huhtala and 2 more

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 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
2.1field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Time-dependent diffusion MRI as in vivo histology: microstructural biomarkers for breast cancer diagnosis and prognostic stratification.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Antti SassiDepartment of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland. antti.sassi@fimnet.fi.
Annukka SalminenDepartment of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland.
Arja JukkolaFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Maija TervoFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Niina MäenpääFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Saara TurtiainenFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Leena TiainenFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Timo LiimatainenResearch Unit of Medical Imaging Physics and Technology, University of Oulu, Oulu, Finland.
Teemu TolonenFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Heini HuhtalaFaculty of Social Sciences, Tampere University, Tampere, Finland.
Irina Rinta-KiikkaDepartment of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland.
Otso ArponenDepartment of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland.
Tampere University · FITampere University Hospital · FITampere University · FIOulu University Hospital · FI

Funding

Tays MJ006L and 9AC002
6 · The paper itself

Abstract

objectivesTo assess whether mammographic breast density in women diagnosed with breast cancer correlates with the total number of incidental magnetic resonance imaging (MRI)-detected lesions and the likelihood of the lesions being malignant.

methodsPatients diagnosed with breast cancer meeting the EUSOBI and EUSOMA criteria for preoperative breast MRI routinely undergo mammography and ultrasound before MRI at our institution. Incidental suspicious breast lesions detected in MRI are biopsied. We included patients diagnosed with invasive breast cancers between 2014 and 2019 who underwent preoperative breast MRI. One reader retrospectively determined breast density categories according to the 5

resultsOf 946 patients with 973 malignant primary breast tumors, 166 (17.5%) had a total of 175 (18.0%) incidental MRI-detected lesions (82 (46.9%) malignant and 93 (53.1%) benign). High breast density according to BI-RADS was associated with higher incidence of all incidental enhancing lesions in preoperative breast MRIs: 2.66 (95% confidence interval: 1.03-6.86) higher for BI-RADS density category B, 2.68 (1.04-6.92) for category C, and 3.67 (1.36-9.93) for category D compared to category A (p < 0.05). However, high breast density did not predict higher incidence of malignant incidental lesions (p = 0.741). Incidental MRI-detected lesions in the contralateral breast were more likely benign (p < 0.001): 18 (27.3%)/48 (72.7%) vs. 64 (58.7%)/45 (41.3%) malignant/benign incidental lesions in contralateral vs. ipsilateral breasts.

conclusionWomen diagnosed with breast cancer who have dense breasts have more incidental MRI-detected lesions, but higher breast density does not translate to increased likelihood of malignant incidental lesions. CLINICAL RELEVANCE STATEMENT: Dense breasts should not be considered as an indication for preoperative breast MRI in women diagnosed with breast cancer. KEY POINTS: • The role of preoperative MRI of patients with dense breasts diagnosed with breast cancer is under debate. • Women with denser breasts have a higher incidence of all MRI-detected incidental breast lesions, but the incidence of malignant MRI-detected incidental lesions is not higher than in women with fatty breasts. • High breast density alone should not indicate preoperative breast MRI.

Indexed as

Breast NeoplasmsBreastBreast DensityFemaleHumansMagnetic Resonance ImagingMammographyRetrospective StudiesBreast densityBreast neoplasmsIncidental findingsMagnetic resonance imaging

Identifiers

PMID37646814
PMCPMC10598189
OpenAlexW4386272477

What OpenQuestion holds

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LicenceCC BY
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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.