Evidence map›Paper›PMID 36138072›Full record

ArticleBritish journal of cancer2022

Breast density is strongly associated with multiparametric magnetic resonance imaging biomarkers and pro-tumorigenic proteins in situ.

Peter Lundberg, Mikael F Forsgren, Jens Tellman, Johan Kihlberg, Anna Rzepecka, Charlotta Dabrosin

Open access · hybridAbstract read
In one paragraph

Article in British journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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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 1 institution in 1 country.

Peter LundbergDepartment of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-8661-2232
Mikael F ForsgrenCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Jens TellmanDepartment of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Johan KihlbergCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Anna RzepeckaDepartment of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Charlotta DabrosinDepartment of Oncology and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden. charlotta.dabrosin@liu.se.ORCID http://orcid.org/0000-0001-7191-0018
Linköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh mammographic density is an independent risk factor for breast cancer by poorly understood molecular mechanisms. Women with dense breasts often undergo conventional magnetic resonance imaging (MRI) despite its limited specificity, which may be increased by diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) and contrast. How these modalities are affected by breast density per se and their association with the local microenvironment are undetermined.

methodsHealthy postmenopausal women attending mammography screen with extremely dense or entirely fatty breasts underwent multiparametric MRI for analyses of lean tissue fraction (LTF), ADC and perfusion dynamics. Microdialysis was used for extracellular proteomics in situ.

resultsSignificantly increased LTF and ADC and delayed perfusion were detected in dense breasts. In total, 270 proteins were quantified, whereof 124 related to inflammation, angiogenesis, and cellular growth were significantly upregulated in dense breasts. Most of these correlated significantly with LTF, ADC and the perfusion data.

conclusionsADC and perfusion characteristics depend on breast density, which should be considered during the implementation of thresholds for malignant lesions. Dense and nondense breasts are two essentially different biological entities, with a pro-tumorigenic microenvironment in dense breasts. Our data reveal several novel pathways that may be explored for breast cancer prevention strategies.

Indexed as

Breast NeoplasmsMultiparametric Magnetic Resonance ImagingBiomarkersBreast DensityCarcinogenesisFemaleHumansMammographyTumor MicroenvironmentBiomarkers

Identifiers

PMID36138072
PMCPMC9681775
OpenAlexW4296793421

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.