Evidence map›Paper›PMID 22648081›Full record

ReviewTopics in magnetic resonance imaging : TMRI2011

Molecular characterization of rheumatoid arthritis with magnetic resonance imaging.

Jeffrey T Gu, Linda Nguyen, Abhijit J Chaudhari, John D MacKenzie

Abstract readReview
In one paragraph

Review in Topics in magnetic resonance imaging : TMRI, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. EXPLORing Arthritis with Total-body Positron Emission Tomography.Seminars in musculoskeletal radiology · 2023
    Review
  3. HyperpolarizedNMR in biomedicine · 2021
    Review
  4. In vivo quantification of mouse autoimmune arthritis by PET/CT.International journal of rheumatic diseases · 2016
    Article
  5. Advancing musculoskeletal research with nanoscience.Nature reviews. Rheumatology · 2013
    Review
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

4 authors at 3 institutions in 1 country.

Jeffrey T GuDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143-0628 , USA.
Linda Nguyen
Abhijit J Chaudhari
John D MacKenzie
University of California, Davis · USUniversity of California, San Francisco · USUniversity of San Francisco · US

Funding

Molecular Imaging for Detection and Treatment Monitoring of ArthritisK08AR061412 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MACKENZIE, JOHN DEWOLFE · 2012 to 2016
$677k
NIAMS NIH HHS K08 AR061412NIAMS NIH HHS L40 AR056591
6 · The paper itself

Abstract

Several recent advances in the field of magnetic resonance imaging (MRI) may transform the detection and monitoring of rheumatoid arthritis (RA). These advances depict both anatomic and molecular alterations from RA. Previous techniques could detect specific end products of metabolism in vitro or were limited to providing anatomic information. This review focuses on the novel molecular imaging techniques of hyperpolarized carbon-13 MRI, MRI with iron-labeled probes, and fusion of MRI with positron emission tomography. These new imaging approaches go beyond the anatomic description of RA and lend new information into the status of this disease by giving molecular information.

Indexed as

Arthritis, RheumatoidCarbon IsotopesContrast MediaDextransHumansMagnetic Resonance ImagingMagnetite NanoparticlesMolecular ImagingPositron-Emission TomographyCarbon IsotopesContrast MediaDextransferumoxidesMagnetite Nanoparticles

Identifiers

PMID22648081
PMCPMC3387734
OpenAlexW2071183550

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.