Evidence map›Paper›PMID 19299487›Full record

ArticleAJNR. American journal of neuroradiology2009

Window settings for the study of calcified carotid plaques with multidetector CT angiography.

L Saba, G Mallarin

Open access · hybridAbstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
2.9field-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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.

  1. Guideline
  2. Trial
  3. Article
  4. Carotid plaque characteristics by computed Tomography: A diagnostic accuracy systematic review.International journal of cardiology. Heart & vasculature · 2025
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Imaging Approaches to the Diagnosis of Vascular Diseases.Current atherosclerosis reports · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. CT Attenuation Analysis of Carotid Intraplaque Hemorrhage.AJNR. American journal of neuroradiology · 2018
    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 1 institution in 1 country.

L SabaDepartment of Science of the Images, Policlinico Universitario, Cagliari, Italy. lucasaba@tiscali.it
G Mallarin
Tiscali (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

summaryCT angiography (CTA) shows high sensitivity in detecting calcified plaques, but sometimes a bias in the exact quantification of stenosis degree occurs, mainly caused by the high linear attenuation coefficient of the calcified plaques. The purpose of this technical study was to evaluate the most appropriate CT window parameters for the assessment of calcified plaques stating which of them can provide the best inter-observer agreement. Scatter-plots and regression results showed the correlation between both width and level respectively depending on intraluminal Hounsfield units (HU) value (width = intraluminal HU x 2.07; level = intraluminal HU x 0.72). Obtained data indicated that the presence of different stenosis degrees did not modify visualization parameters.

Indexed as

AdultAgedAged, 80 and overAlgorithmsCalcinosisCarotid StenosisCerebral AngiographyFemaleHumansMaleMiddle AgedRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityTomography, X-Ray Computed

Identifiers

PMID19299487
PMCPMC7051539
OpenAlexW2152826468

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.