Evidence map›Paper›PMID 40664863›Full record

ArticleEuropean radiology2026

Motion artifacts and image quality in stroke MRI: associated factors and impact on AI and human diagnostic accuracy.

Christian Hedeager Krag, Felix Christoph Müller, Karen Lind Gandrup, Michael Brun Andersen, Jakob Møllenbach Møller, Marie Louise Liu, Anita Rud, Simon Krabbe, Lamaa Al-Farra, Mads Nielsen and 2 more

Abstract readComparative Study
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

12 authors.

Christian Hedeager KragDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark. christian.hedeager.krag.01@regionh.dk.ORCID http://orcid.org/0000-0001-5994-3132
Felix Christoph MüllerDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Karen Lind GandrupDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Michael Brun AndersenDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Jakob Møllenbach MøllerDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Marie Louise LiuDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Anita RudDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Simon KrabbeDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Lamaa Al-FarraDepartment of Radiology, University Hospital Copenhagen-Herlev and Gentofte, Copenhagen, Denmark.
Mads NielsenDepartment of Computer Science, University of Copenhagen, Copenhagen, Denmark.
Christina KruuseFaculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Mikael Ploug BoesenFaculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the prevalence of motion artifacts and the factors associated with them in a cohort of suspected stroke patients, and to determine their impact on diagnostic accuracy for both AI and radiologists. MATERIALS AND

methodsThis retrospective cross-sectional study included brain MRI scans of consecutive adult suspected stroke patients from a non-comprehensive Danish stroke center between January and April 2020. An expert neuroradiologist identified acute ischemic, hemorrhagic, and space-occupying lesions as references. Two blinded radiology residents rated MRI image quality and motion artifacts. The diagnostic accuracy of a CE-marked deep learning tool was compared to that of radiology reports. Multivariate analysis examined associations between patient characteristics and motion artifacts.

results775 patients (68 years ± 16, 420 female) were included. Acute ischemic, hemorrhagic, and space-occupying lesions were found in 216 (27.9%), 12 (1.5%), and 20 (2.6%). Motion artifacts were present in 57 (7.4%). Increasing age (OR per decade, 1.60; 95% CI: 1.26, 2.09; p < 0.001) and limb motor symptoms (OR, 2.36; 95% CI: 1.32, 4.20; p = 0.003) were independently associated with motion artifacts in multivariate analysis. Motion artifacts significantly reduced the accuracy of detecting hemorrhage. This reduction was greater for the AI tool (from 88 to 67%; p < 0.001) than for radiology reports (from 100 to 93%; p < 0.001). Ischemic and space-occupying lesion detection was not significantly affected.

conclusionMotion artifacts are common in suspected stroke patients, particularly in the elderly and patients with motor symptoms, reducing accuracy for hemorrhage detection by both AI and radiologists. KEY POINTS: Question Motion artifacts reduce the quality of MRI scans, but it is unclear which factors are associated with them and how they impact diagnostic accuracy. Findings Motion artifacts occurred in 7% of suspected stroke MRI scans, associated with higher patient age and motor symptoms, lowering hemorrhage detection by AI and radiologists. Clinical relevance Motion artifacts in stroke brain MRIs significantly reduce the diagnostic accuracy of human and AI detection of intracranial hemorrhages. Elderly patients and those with motor symptoms may benefit from a greater focus on motion artifact prevention and reduction.

Indexed as

ArtifactsHemorrhagic StrokeIschemic StrokeMagnetic Resonance ImagingMovementAgedAged, 80 and overAge FactorsCross-Sectional StudiesDeep LearningFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedMultivariate AnalysisArtifactsArtificial intelligenceBrainMagnetic resonance imagingStroke

Identifiers

PMID40664863
PMCPMC12712086

What Socratic 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 Socratic graph.