Evidence map›Paper›PMID 29574492›Full record

ReviewSkeletal radiology2018

The anterior knee: normal variants, common pathologies, and diagnostic pitfalls on MRI.

Yong Wei Liu, Matthew R Skalski, Dakshesh B Patel, Eric A White, Anderanik Tomasian, George R Matcuk

Abstract readReview
PubMed Publisher
In one paragraph

Review in Skeletal radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. 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

6 authors.

Yong Wei LiuDepartment of Radiology, Harbor-UCLA Medical Center, Torrance, CA, 90509, USA.
Matthew R SkalskiDepartment of Radiology, Palmer College of Chiropractic - West Campus, San Jose, CA, 95134, USA.
Dakshesh B PatelDepartment of Radiology, Keck School of Medicine, University of Southern California, 1520 San Pablo Street, Suite L1600, Los Angeles, CA, 90033, USA.
Eric A WhiteDepartment of Radiology, Keck School of Medicine, University of Southern California, 1520 San Pablo Street, Suite L1600, Los Angeles, CA, 90033, USA.
Anderanik TomasianDepartment of Radiology, Keck School of Medicine, University of Southern California, 1520 San Pablo Street, Suite L1600, Los Angeles, CA, 90033, USA.
George R MatcukDepartment of Radiology, Keck School of Medicine, University of Southern California, 1520 San Pablo Street, Suite L1600, Los Angeles, CA, 90033, USA. matcuk@usc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The anterior aspect of the knee is host to an array of normal variants and potential pathology. These normal anatomic variants are often encountered and may mimic pathologies, leading to unnecessary work-up and treatments. On the other hand, there are several subtle abnormalities that may be easily overlooked or mistaken for variants or other injuries or diseases. Recognition of these diagnostic challenges is essential for radiologists to make an accurate diagnosis. This article reviews normal anatomical variants of ligaments, tendons, bones, and other important structures of the anterior knee, focusing on magnetic resonance imaging features. Commonly encountered injuries and abnormalities of the anterior knee and their diagnostic pitfalls are also discussed, highlighting findings on magnetic resonance imaging.

Indexed as

Magnetic Resonance ImagingAdolescentAgedBursa, SynovialFemaleFemurHumansKnee InjuriesKnee JointLigaments, ArticularMaleMedical IllustrationMeniscusMiddle AgedPatellaTendonsAnterior kneeBursaeFat padsPatellofemoral morphologySynovial plicaeVariants

Identifiers

PMID29574492

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.