Evidence map›Paper›PMID 34063854›Full record

ReviewInternational journal of environmental research and public health2021

A Review of Breast Imaging for Timely Diagnosis of Disease.

Giulia Bicchierai, Federica Di Naro, Diego De Benedetto, Diletta Cozzi, Silvia Pradella, Vittorio Miele, Jacopo Nori

Abstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Imaging in Interventional Radiology: Breast Cryoablation.Seminars in interventional radiology · 2025
    Review
  3. Article
  4. Review
  5. 3D Harmonic and Subharmonic Imaging for Characterizing Breast Lesions: A Multi-Center Clinical Trial.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2022
    Article
  6. Special Issue "New Advances in Breast Imaging".Tomography (Ann Arbor, Mich.) · 2022
    Article
  7. Improved Machine Learning-Based Predictive Models for Breast Cancer Diagnosis.International journal of environmental research and public health · 2022
    Article
  8. Review
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

7 authors.

Giulia BicchieraiDiagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.ORCID 0000-0003-1979-7593
Federica Di NaroDiagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.
Diego De BenedettoDiagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.
Diletta CozziEmergency Radiology Department, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.
Silvia PradellaEmergency Radiology Department, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.
Vittorio MieleEmergency Radiology Department, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.ORCID 0000-0002-7848-1567
Jacopo NoriDiagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, 50139 Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is the cancer with the highest incidence in women in the world. In this last period, the COVID-19 pandemic has caused in many cases a drastic reduction of routine breast imaging activity due to the combination of various factors. The survival of BC is directly proportional to the earliness of diagnosis, and especially during this period, it is at least fundamental to remember that a diagnostic delay of even just three months could affect BC outcomes. In this article we will review the state of the art of breast imaging, starting from morphological imaging, i.e., mammography, tomosynthesis, ultrasound and magnetic resonance imaging and contrast-enhanced mammography, and their most recent evolutions; and ending with functional images, i.e., magnetic resonance imaging and contrast enhanced mammography.

Indexed as

Breast NeoplasmsCOVID-19Delayed DiagnosisFemaleHumansMagnetic Resonance ImagingMammographyPandemicsSARS-CoV-2breastbreast cancerCEMmammographyMRItomosynthesisultrasound

Identifiers

PMID34063854
PMCPMC8196652

What OpenQuestion holds

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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.