Evidence map›Paper›PMID 40437551›Full record

ArticleBMC research notes2025

Investigation of radiology professionals' awareness of CT head artifacts.

Moawia Gameraddin, Awadia Gareeballah, Abdulaziz A Qurashi, Abdullah Fahad Alshamrani, Osama Ahmed Alasiri, Maher Mosfer Aljohani, Amel F Alzain, Omar Adel Almutairi, Abdulmalik Basheer Alenezi, Renad Albadrani and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Moawia GameraddinDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia. m.bushra@yahoo.com.
Awadia GareeballahDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Abdulaziz A QurashiDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Abdullah Fahad AlshamraniDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Osama Ahmed AlasiriDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Maher Mosfer AljohaniDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Amel F AlzainDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Omar Adel AlmutairiDepartment of Medical Imaging, King Abdulaziz Medical City, Riyadh, Saudi Arabia.
Abdulmalik Basheer AleneziDepartment of medical imaging, AlHammadi hospital, Riyadh, Saudi Arabia.
Renad AlbadraniShifa Taibah Polyclinic, Al-Madinah, Saudi Arabia.
Awatif OmerDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Maisa ElzakiDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Abdalrahim Tagelsir ElsayedDepartment of Diagnostic Radiology, College of Applied Medical Sciences, Taibah University, Al-Madinah, Saudi Arabia.
Emadeldin Mohamed MukhtarDepartment of Radiological Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveComputerized tomography (CT) artifacts can happen for various causes. It is critical to understand these artifacts because they can mimic disease or reduce image quality to non-diagnostic levels. CT artifacts can be characterized according to their underlying cause. This study aims to evaluate and compare the understanding of CT head artifacts between radiographers and radiography interns, supplemented by insights from a select group of participating radiologists.

resultsA cross-sectional survey study included 150 participants. All participants' average knowledge score of CT head artifact was good (77.81%). The most correctly identified CT head artifacts were the metal artifact (86%), ring artifact (84.7%), and motion artifact (81.3%). The beam hardening artifact was correctly identified less frequently (62%). There is significant difference in the recognition of motion artifacts among the participants (P = 0.001) knowledge of CT head image artifacts improved significantly with more experienced participants (P = 0.001), where participants with less than 10 months of experience had a higher rate of incorrect responses (85 incorrect vs. 31 correct). The recognition of these artifacts improves with experience and advanced age. Understanding these artifacts is essential to avoid misdiagnosis of various diseases.

Indexed as

ArtifactsClinical CompetenceHeadRadiologistsTomography, X-Ray ComputedAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesAwarenessCT image artifactsKnowledge scoresMotional artifactsRadiographers

Identifiers

PMID40437551
PMCPMC12121074

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.