Evidence map›Paper›PMID 36105423›Full record

ReviewBJR open2022

MRI as a biomarker for breast cancer diagnosis and prognosis.

Francesca Galati, Veronica Rizzo, Rubina Manuela Trimboli, Endi Kripa, Roberto Maroncelli, Federica Pediconi

Open access · goldAbstract readReview
In one paragraph

Review in BJR open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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  6. Article
  7. Article
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  9. Article
  10. Review
  11. Review
  12. Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.International journal of molecular sciences · 2023
    Review
  13. 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

6 authors at 2 institutions in 1 country.

Francesca GalatiDepartment of Radiological, Oncological and Pathological Sciences, "Sapienza" - University of Rome, Viale Regina Elena, Rome, Italy.
Veronica RizzoDepartment of Radiological, Oncological and Pathological Sciences, "Sapienza" - University of Rome, Viale Regina Elena, Rome, Italy.
Rubina Manuela TrimboliHumanitas Clinical and Research Center - IRCCS, Via Manzoni 56 - 20089, Rozzano (MI), Italy.
Endi KripaDepartment of Radiological, Oncological and Pathological Sciences, "Sapienza" - University of Rome, Viale Regina Elena, Rome, Italy.
Roberto MaroncelliDepartment of Radiological, Oncological and Pathological Sciences, "Sapienza" - University of Rome, Viale Regina Elena, Rome, Italy.
Federica PediconiDepartment of Radiological, Oncological and Pathological Sciences, "Sapienza" - University of Rome, Viale Regina Elena, Rome, Italy.
Sapienza University of Rome · ITIstituti di Ricovero e Cura a Carattere Scientifico · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is the most frequently diagnosed female invasive cancer in Western countries and the leading cause of cancer-related death worldwide. Nowadays, tumor heterogeneity is a well-known characteristic of BC, since it includes several nosological entities characterized by different morphologic features, clinical course and response to treatment. Thus, with the spread of molecular biology technologies and the growing knowledge of the biological processes underlying the development of BC, the importance of imaging biomarkers as non-invasive information about tissue hallmarks has progressively grown. To date, breast magnetic resonance imaging (MRI) is considered indispensable in breast imaging practice, with widely recognized indications such as BC screening in females at increased risk, locoregional staging and neoadjuvant therapy (NAT) monitoring. Moreover, breast MRI is increasingly used to assess not only the morphologic features of the pathological process but also to characterize individual phenotypes for targeted therapies, building on developments in genomics and molecular biology features. The aim of this review is to explore the role of breast multiparametric MRI in providing imaging biomarkers, leading to an improved differentiation of benign and malignant breast lesions and to a customized management of BC patients in monitoring and predicting response to treatment. Finally, we discuss how breast MRI biomarkers offer one of the most fertile ground for artificial intelligence (AI) applications. In the era of personalized medicine, with the development of omics-technologies, machine learning and big data, the role of imaging biomarkers is embracing new opportunities for BC diagnosis and treatment.

Identifiers

PMID36105423
PMCPMC9459861
OpenAlexW4280525231

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.