Evidence map›Paper›PMID 28289855›Full record

ReviewSkeletal radiology2017

Whole-body MRI, dynamic contrast-enhanced MRI, and diffusion-weighted imaging for the staging of multiple myeloma.

Julie C Dutoit, Koenraad L Verstraete

Abstract readReview
PubMed Publisher
In one paragraph

Review in Skeletal radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Optimization of whole-body 2-[European radiology · 2022
    Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Advanced Imaging of Multiple Myeloma Bone Disease.Frontiers in endocrinology · 2018
    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

2 authors at 1 institution in 1 country.

Julie C DutoitDepartment of Radiology, Ghent University Hospital, MR -1 K12, De Pintelaan 185, 9000, Ghent, Belgium. Julie.Dutoit@UGent.be.
Koenraad L VerstraeteDepartment of Radiology, Ghent University Hospital, MR -1 K12, De Pintelaan 185, 9000, Ghent, Belgium.
Ghent University Hospital · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) is the most sensitive imaging technique for the detection of bone marrow infiltration, and has therefore recently been included in the new diagnostic myeloma criteria, as proposed by the International Myeloma Working Group. Nevertheless, conventional MRI only provides anatomical information and is therefore only of limited use in the response assessment of patients with multiple myeloma. The additional information from functional MRI techniques, such as diffusion-weighted imaging and dynamic contrast-enhanced MRI, can improve the detection rate of bone marrow infiltration and the assessment of response. This can further enhance the sensitivity and specificity of MRI in the staging of multiple myeloma patients. This article provides an overview of the technical aspects of conventional and functional MRI techniques with practical recommendations. It reviews the diagnostic performance, prognostic value, and role in therapy assessment in multiple myeloma and its precursor stages.

Indexed as

Contrast MediaDiffusion Magnetic Resonance ImagingHumansImage EnhancementMagnetic Resonance ImagingMultiple MyelomaNeoplasm StagingWhole Body ImagingContrast MediaDiffusion-weighted imagingDynamic contrast-enhanced MRIMRIMultiple myeloma

Identifiers

PMID28289855
OpenAlexW2597213575

What OpenQuestion holds

Textmetadata
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.