Evidence map›Paper›PMID 40021671›Full record

ArticleScientific reports2025

3D quantification of metal-induced geometric distortions in MRI.

Hao Li, Ali C Özen, Alexander Juerchott, Michael Breckwoldt, Jessica Jesser, Dominik F Vollherbst, Daniel Schwarz, Martin Bendszus, Sabine Heiland, Tim Hilgenfeld

Abstract read
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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Intraoral Coil Arrays for Single-Tooth Dental MRI.Magnetic resonance in medicine · 2026
    Article
  3. 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

10 authors.

Hao LiDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Ali C ÖzenDepartment of Radiology, Medical Physics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Alexander JuerchottDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Michael BreckwoldtDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Jessica JesserDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Dominik F VollherbstDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Daniel SchwarzDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Martin BendszusDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Sabine HeilandDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
Tim HilgenfeldDepartment of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany. tim.hilgenfeld@med.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing number of patients with metal implants raises concerns about metal-induced geometric distortions (MD) in MR-guided treatments. This study proposes a method for three-dimensional quantification of MD and evaluates its accuracy and reliability. A 3D lattice phantom was designed and measured with two sequences (VIBE and SPACE) and two implants (crown-supported-dental-implant and stainless-steel-bracket). Automated detection of displacement of 9360 crossing points caused by MD was performed. Distortion-quantification accuracy was improved by correcting for noise-induced error (NE), related to different signal-to-noise ratios (SNR), and implant-related signal loss and pile-up artifact volumes (SLPUA). The method's accuracy was validated against computed tomography. Results showed high reliability, with an excellent intraclass correlation coefficient (≥ 0.99) and low mean residual errors in all directions (2.6%/1.6%/1.8% of voxel size in X/Y/Z direction). SNR/SLPUA volumes were significant confounders (p-value ≤ 0.001) when comparing different sequences/implants, but corrections significantly reduced their impacts (p-value ≤ 0.001). This method enables accurate 3D MD quantification and fair comparison across different sequences/implants. By optimizing MRI protocols for MD minimization and defining implant-specific MD profiles for patient data correction, it may help improve spatial accuracy in MRI-guided treatments in the future.

Indexed as

Dental ImplantsImaging, Three-DimensionalMagnetic Resonance ImagingMetalsArtifactsHumansPhantoms, ImagingReproducibility of ResultsSignal-To-Noise RatioTomography, X-Ray ComputedDental ImplantsMetalsAccuracy and reliabilityGeometric distortionImage noiseMagnetic resonance imagingMetallic implantsSusceptibility artifacts

Identifiers

PMID40021671
PMCPMC11871036

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Registered trials

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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.