Evidence map›Paper›PMID 32548293›Full record

ArticleTomography (Ann Arbor, Mich.)2020

Quantitative Comparison of Prone and Supine PERCIST Measurements in Breast Cancer.

Jennifer G Whisenant, Jason M Williams, Hakmook Kang, Lori R Arlinghaus, Richard G Abramson, Vandana G Abramson, Kareem Fakhoury, A Bapsi Chakravarthy, Thomas E Yankeelov

Open access · goldAbstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 43% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

9 authors at 3 institutions in 1 country.

Jennifer G WhisenantVanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Jason M WilliamsVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN.
Hakmook KangVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN.
Lori R ArlinghausVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN.
Richard G AbramsonVanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Vandana G AbramsonVanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Kareem FakhouryDepartment of Radiation Oncology, University of Colorado Cancer Center-Anschutz Medical Campus, Aurora, CO.
A Bapsi ChakravarthyVanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Thomas E YankeelovOden Institute for Computational Engineering and Sciences; Livestrong Cancer Institutes; Department of Biomedical Engineering; Department of Diagnostic Medicine; and Department of Oncology, The University of Texas, Austin, TX.
Vanderbilt University Medical Center · USLivestrong Foundation · USUniversity of Colorado Denver · US

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
TISSUE CoreP50CA098131 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PARK, BEN HO, PIETENPOL, JENNIFER A · 2003 to 2024
$48.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast CancerU01CA174706 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, YANKEELOV, THOMAS E · 2013 to 2018
$2.5M
NCATS NIH HHS UL1 TR000445NCI NIH HHS P30 CA068485NCI NIH HHS P50 CA098131NCI NIH HHS U01 CA142565NCI NIH HHS U01 CA174706
6 · The paper itself

Abstract

Positron emission tomography (PET) is typically performed in the supine position. However, breast magnetic resonance imaging (MRI) is performed in prone, as this improves visibility of deep breast tissues. With the emergence of hybrid scanners that integrate molecular information from PET and functional information from MRI, it is of great interest to determine if the prognostic utility of prone PET is equivalent to supine. We compared PERCIST (PET Response Criteria in Solid Tumors) measurements between prone and supine FDG-PET in patients with breast cancer and the effect of orientation on predicting pathologic complete response (pCR). In total, 47 patients were enrolled and received up to 6 cycles of neoadjuvant therapy. Prone and supine FDG-PET were performed at baseline (

Indexed as

Breast NeoplasmsFluorodeoxyglucose F18Positron-Emission TomographyFemaleHumansRadiopharmaceuticalsTomography, X-Ray ComputedFluorodeoxyglucose F18Radiopharmaceuticals18F-fluorodeoxyglucoseFDG-PETpathological complete responsequantitative PET

Identifiers

PMID32548293
PMCPMC7289244
OpenAlexW3034118623

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.