Evidence map›Paper›PMID 37336693›Full record

ReviewPET clinics2023

AI-Enhanced PET and MR Imaging for Patients with Breast Cancer.

Valeria Romeo, Linda Moy, Katja Pinker

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in PET clinics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. 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 at 3 institutions in 2 countries.

Valeria RomeoDepartment of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, Naples 80138, Italy. Electronic address: valeria.romeo@unina.it.
Linda MoyDepartment of Radiology, New York University School of Medicine, 160 East 34th Street, New York, NY 10016, USA.
Katja PinkerDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 East 66th Street, New York, NY 10065, USA.
Memorial Sloan Kettering Cancer Center · USNew York University · USUniversity of Naples Federico II · IT

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

New challenges are currently faced by clinical and surgical oncologists in the management of patients with breast cancer, mainly related to the need for molecular and prognostic data. Recent technological advances in diagnostic imaging and informatics have led to the introduction of functional imaging modalities, such as hybrid PET/MR imaging, and artificial intelligence (AI) software, aimed at the extraction of quantitative radiomics data, which may reflect tumor biology and behavior. In this article, the most recent applications of radiomics and AI to PET/MR imaging are described to address the new needs of clinical and surgical oncology.

Indexed as

Breast NeoplasmsArtificial IntelligenceFemaleHumansMagnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyArtificial intelligenceBreast cancerPET/MR imagingRadiomics

Identifiers

PMID37336693
PMCPMC10947491
OpenAlexW4381056807

What OpenQuestion holds

Textmetadata
LicenceTDM
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.