Evidence map›Paper›PMID 39915189›Full record

ReviewPET clinics2025

Current and Future Applications of PET Radiomics in Radiation Oncology.

Yong Fan, Steven J Feigenberg, Charles B Simone

Abstract readReview
In one paragraph

Review in PET clinics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Yong FanDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, 3700 Hamilton Walk, Philadelphia, PA 19104-6116, USA. Electronic address: yong.fan@pennmedicine.upenn.edu.
Steven J FeigenbergDepartment of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, 2 West, Philadelphia, PA 19104, USA.
Charles B SimoneNew York Proton Center; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0M
Fast and robust deep learning tools for analysis of neuroimaging data of Alzheimer's diseaseR01AG066650 · NIA · UNIVERSITY OF PENNSYLVANIA · PI FAN, YONG · 2021 to 2025
$3.4M
Learning radiomic signatures to early predict response of rectal cancer patients to neoadjuvant chemoradiation therapyR21CA223358 · NCI · UNIVERSITY OF PENNSYLVANIA · PI FAN, YONG · 2018 to 2019
$380k
NCI NIH HHS P30 CA008748NCI NIH HHS R21 CA223358NIA NIH HHS R01 AG066650NIBIB NIH HHS R01 EB022573
6 · The paper itself

Abstract

This review delves into the principles of PET imaging and radiomics, emphasizing their importance in detecting, staging, and monitoring various cancers. It highlights the clinical applications of PET radiomics in oncology, showcasing its impact on personalized cancer care. Additionally, the review addresses challenges such as standardizing PET radiomics, integrating multiomics data, and ethical concerns in clinical decision-making. Future directions are also discussed, including broader applications of PET radiomics in clinical trials, artificial intelligence integration for automated analysis, and incorporating multiomics data for a comprehensive understanding of tumor biology.

Indexed as

NeoplasmsPositron-Emission TomographyRadiation OncologyArtificial IntelligenceHumansPrecision MedicineRadiomicsArtificial intelligenceMachine learningPETRadiomics

Identifiers

PMID39915189
PMCPMC11922665

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.