Evidence map›Paper›PMID 34564299›Full record

ArticleTomography (Ann Arbor, Mich.)2021

Identification of Traumatic Bone Marrow Oedema: The Pearls and Pitfalls of Dual-Energy CT (DECT).

Giovanni Foti, Gerardo Serra, Venanzio Iacono, Claudio Zorzi

Open access · goldAbstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. 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 1 institution in 1 country.

Giovanni FotiDepartment of Radiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.ORCID 0000-0002-1426-2402
Gerardo SerraDepartment of Anesthesia and Analgesic Therapy, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
Venanzio IaconoDepartment of Orthopaedic Surgery, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
Claudio ZorziDepartment of Orthopaedic Surgery, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
Ospedale Sacro Cuore Don Calabria · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual-energy computed tomography (DECT) has been reported to successfully identify bone marrow oedema (BME) in various traumatic settings. DECT has multiple strengths, including the availability of both a 3D view of the anatomical area studied and of high-resolution dual energy specific maps super-imposed onto conventional grayscale morphological images. Windowing can be used to enhance the visualization of BME by increasing the level of the super-imposed images. Conversely, by decreasing the level of the super-imposition of color-coded images, it is possible to progressively enhance the visualization of fine anatomical details, which is useful for diagnosing associated imaging findings. Importantly, bone sclerosis may represent an important pitfall for DECT, potentially generating both false positive and false negative findings by locally altering CT numbers. The aim of this paper was to evaluate the strengths and limitations of DECT in accurately detecting traumatic BME, by considering practical approaches to imaging at several anatomical sites.

Indexed as

Bone MarrowBone Marrow DiseasesEdemaHumansSensitivity and SpecificityTomography, X-Ray Computedbone marrow edemacomputed tomographydual energytrauma

Identifiers

PMID34564299
PMCPMC8482263
OpenAlexW3195105888

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.