Evidence map›Paper›PMID 27729326›Full record

ArticleCancer research2016

PET and MRI: Is the Whole Greater than the Sum of Its Parts?

Robert J Gillies, Thomas Beyer

Open access · bronzeAbstract read
In one paragraph

Article in Cancer research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

8 citing papers in PubMed, 21 citations in OpenAlex.

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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

2 authors at 2 institutions in 2 countries.

Robert J GilliesDepartment of Radiology, H Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. Robert.Gillies@moffitt.org.
Thomas BeyerCenter for Medical Physics and Biomedical Engineering, Medical University Vienna, General Hospital Vienna, Vienna, Austria.
Moffitt Cancer Center · USVienna General Hospital · AT

Funding

Causes & Consequences of Acid pH in TumorsR01CA077575 · NCI · UNIVERSITY OF ARIZONA · PI GILLIES, ROBERT J. · 1999 to 2018
$8.5M
Radiomics of NSCLCU01CA143062 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI GILLIES, ROBERT J., SCHABATH, MATTHEW B. · 2010 to 2020
$5.7M
MRI Imaging and Genetic Signatures to Manage Prostate Cancer OverdiagnosisR01CA189295 · NCI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI POLLACK, ALAN · 2014 to 2018
$3.2M
(PQC4) Habitats in Prostate CancerR01CA190105 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI BALAGURUNATHAN, YOGANAND, GILLIES, ROBERT J. · 2014 to 2017
$2.8M
NCI NIH HHS R01 CA077575NCI NIH HHS R01 CA189295NCI NIH HHS R01 CA190105NCI NIH HHS U01 CA143062
6 · The paper itself

Abstract

Over the past decades, imaging in oncology has been undergoing a "quiet" revolution to treat images as data, not as pictures. This revolution has been sparked by technological advances that enable capture of images that reflect not only anatomy, but also of tissue metabolism and physiology in situ Important advances along this path have been the increasing power of MRI, which can be used to measure spatially dependent differences in cell density, tissue organization, perfusion, and metabolism. In parallel, PET imaging allows quantitative assessment of the spatial localization of positron-emitting compounds, and it has also been constantly improving in the number of imageable tracers to measure metabolism and expression of macromolecules. Recent years have witnessed another technological advance, wherein these two powerful modalities have been physically merged into combined PET/MRI systems, appropriate for both preclinical or clinical imaging. As with all new enabling technologies driven by engineering physics, the full extent of potential applications is rarely known at the outset. In the work of Schmitz and colleagues, the authors have combined multiparametric MRI and PET imaging to address the important issue of intratumoral heterogeneity in breast cancer using both preclinical and clinical data. With combined PET and MRI and sophisticated machine-learning tools, they have been able identify multiple coexisting regions ("habitats") within living tumors and, in some cases, have been able to assign these habitats to known histologies. This work addresses an issue of fundamental importance to both cancer biology and cancer care. As with most new paradigm-shifting applications, it is not the last word on the subject and introduces a number of new avenues of investigation to pursue. Cancer Res; 76(21); 6163-6. ©2016 AACR.

Indexed as

Fluorodeoxyglucose F18HumansMagnetic Resonance ImagingNeoplasmsPositron-Emission TomographyPositron Emission Tomography Computed TomographyFluorodeoxyglucose F18

Identifiers

PMID27729326
PMCPMC5408508
OpenAlexW2530771352

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.