Evidence map›Paper›PMID 32999694›Full record

ReviewPolish journal of radiology2020

Revisiting the WHO classification system of bone tumours: emphasis on advanced magnetic resonance imaging sequences. Part 2.

Shivani Ahlawat, Laura M Fayad

Open access · diamondAbstract readReview
In one paragraph

Review in Polish journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.8field-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

9 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Revolutionizing bone tumor management: cutting-edge breakthroughs in limb-saving treatments.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024
    Review
  6. Molecular and Translational Research on Bone Tumors.International journal of molecular sciences · 2023
    Article
  7. Review
  8. Article
  9. 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

2 authors at 2 institutions in 1 country.

Shivani AhlawatThe Johns Hopkins University School of Medicine, USA.
Laura M FayadThe Johns Hopkins University School of Medicine, USA.
Johns Hopkins Medicine · USJohns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Similarly to soft tissue tumours, the World Health Organisation (WHO) classification categorises bone tumours based on their similarity to normal adult tissue. The most recent WHO classification provides an updated classification scheme that integrates the biological behaviour of bone tumours, particularly cartilage-forming tumours, and tumours are now further subdivided as benign, intermediate (locally aggressive or rarely metastasising), and malignant. Radiologists play an important role in the detection and initial characterisation of bone tumours, with careful analysis of their matrix mineralisation, location, and overall anatomic extent including extra-compartmental extension and neurovascular invasion. Radiography remains central to the detection and characterisation of bone tumours; however, magnetic resonance imaging (MRI) is the ideal modality for local staging. This review will discuss the most recent updates to the WHO classification of bone tumours that are relevant to radiologists in routine clinical practice. The utility of advanced MRI sequences such as diffusion-weighted imaging, dynamic contrast enhanced sequences, and magnetic resonance spectroscopy that may provide insight into the biological behaviour of various bone tumours is highlighted.

Indexed as

bone tumoursMRIsarcomaWHO classification

Identifiers

PMID32999694
PMCPMC7509892
OpenAlexW3081638848

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.