Evidence map›Paper›PMID 34297167›Full record

ReviewSkeletal radiology2022

Update of pediatric soft tissue tumors with review of conventional MRI appearance-part 2: vascular lesions, fibrohistiocytic tumors, muscle tumors, peripheral nerve sheath tumors, tumors of uncertain differentiation, and undifferentiated small round cell sarcomas.

Ezekiel Maloney, Khalid Al-Dasuqi, Lina Irshaid, Annie Wang, Kimia Kani, Andrew Haims, Jack Porrino

Abstract readReview
PubMed Publisher
In one paragraph

Review in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 3 institutions in 1 country.

Ezekiel MaloneyDepartment of Radiology, University of Washington, Seattle Children's Hospital, 4800 Sand Point Way NE, Seattle, WA, 98105, USA.
Khalid Al-DasuqiYale Radiology and Biomedical Imaging, 330 Cedar Street, New Haven, CT, 06520, USA.
Lina IrshaidDepartment of Pathology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.
Annie WangYale Radiology and Biomedical Imaging, 330 Cedar Street, New Haven, CT, 06520, USA.
Kimia KaniDepartment of Radiology, University of Maryland Medical Center, 22 S Greene St, Baltimore, MD, 21201, USA.
Andrew HaimsYale Radiology and Biomedical Imaging, 330 Cedar Street, New Haven, CT, 06520, USA.
Jack PorrinoYale Radiology and Biomedical Imaging, 330 Cedar Street, New Haven, CT, 06520, USA. jack.porrino@yale.edu.
Yale University · USUniversity of Maryland, Baltimore · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are numerous soft tissue tumors and tumor-like conditions in the pediatric population. Magnetic resonance imaging is the most useful modality for imaging these lesions. Although certain soft tissue lesions exhibit magnetic resonance features characteristic of a specific diagnosis, most lesions are indeterminate, and a biopsy is necessary for diagnosis. We provide a detailed update of soft tissue tumors and tumor-like conditions that occur in the pediatric population, emphasizing each lesion's conventional magnetic resonance imaging appearance, using the recently released 5

Indexed as

Muscle NeoplasmsNerve Sheath NeoplasmsSarcomaSoft Tissue NeoplasmsCell DifferentiationChildHumansMagnetic Resonance ImagingPediatricSarcomaSoft tissue massTumorVascular malformation

Identifiers

PMID34297167
OpenAlexW3185947469

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.