Evidence map›Paper›PMID 38929989›Full record

ReviewJournal of clinical medicine2024

PET Molecular Imaging in Breast Cancer: Current Applications and Future Perspectives.

Sanaz Katal, Michael J McKay, Kim Taubman

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

3 authors.

Sanaz KatalMedical Imaging Department, St. Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia.
Michael J McKayNorthwest Regional Hospital, University of Tasmania, Burnie, TAS 7320, Australia.
Kim TaubmanMedical Imaging Department, St. Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia.ORCID 0000-0001-9294-7530

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Positron emission tomography (PET) plays a crucial role in breast cancer management. This review addresses the role of PET imaging in breast cancer care. We focus primarily on the utility of 18F-fluorodeoxyglucose (FDG) PET in staging, recurrence detection, and treatment response evaluation. Furthermore, we delve into the growing interest in precision therapy and the development of novel radiopharmaceuticals targeting tumor biology. This includes discussing the potential of PET/MRI and artificial intelligence in breast cancer imaging, offering insights into improved diagnostic accuracy and personalized treatment approaches.

Indexed as

androgen receptor (AR)artificial intelligence (AI)breast cancerdeep learning (DL)estrogen receptor (ER)FAPIFDGFDHTFEShuman epidermal growth factor receptor 2 (HER2)machine learning (ML)PETPET/CTPET/MRIprogesterone receptor (PR)

Identifiers

PMID38929989
PMCPMC11205053

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.