Evidence map›Paper›PMID 26692524›Full record

ReviewTranslational oncology2015

Imaging Breast Density: Established and Emerging Modalities.

Jeon-Hor Chen, Gultekin Gulsen, Min-Ying Su

Abstract readReview
In one paragraph

Review in Translational oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Concurrent water TMagnetic resonance imaging · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Breast Density Analysis Using Digital Breast Tomosynthesis.bioRxiv : the preprint server for biology · 2023
    Article
  8. Article
  9. Article
  10. Calibrated Breast Density Measurements.Academic radiology · 2019
    Article
  11. Article
  12. Spatial Correlation and Breast Cancer Risk.Biomedical physics & engineering express · 2019
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Generalized breast density metrics.Physics in medicine and biology · 2018
    Article
  18. Article
  19. Article
  20. 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

3 authors.

Jeon-Hor ChenTu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA; Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan. Electronic address: jeonhc@uci.edu.
Gultekin GulsenTu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA.
Min-Ying SuTu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA.

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Christine Hui · 1994 to 2026
$57.9M
Prediction of Neoadjuvant Chemo Pathological Response Using MRI MarkersR01CA127927 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI SU, MIN-YING L. · 2008 to 2017
$5.0M
Volume and Morphology of Fibroglandular Tissue for Breast Cancer Risk PredictionR21CA170955 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI CHEN, JEON-HOR, SU, MIN-YING L. · 2013 to 2014
$363k
NCI NIH HHS P30 CA062203NCI NIH HHS R01 CA127927NCI NIH HHS R21 CA170955
6 · The paper itself

Abstract

Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual's cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient's breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray-based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature.

Identifiers

PMID26692524
PMCPMC4700291

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.