Evidence map›Paper›PMID 24877813›Full record

ArticleMedical physics2014

Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment.

Jang-Hwan Choi, Andreas Maier, Andreas Keil, Saikat Pal, Emily J McWalter, Gary S Beaupré, Garry E Gold, Rebecca Fahrig

Abstract readEvaluation Study
In one paragraph

Article in Medical physics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.6field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Article
  3. Joint Cone-Beam CT Reconstruction and Rigid Motion Compensation Using A Differentiable Projector.Proceedings of SPIE--the International Society for Optical Engineering · 2026
    Article
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  7. Practical workflow for arbitrary non-circular orbits for CT with clinical robotic C-arms.Proceedings of SPIE--the International Society for Optical Engineering · 2022
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  12. Review
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  14. Article
  15. Article
  16. Article
  17. Image-Based Motion Compensation for High-Resolution Extremities Cone-Beam CT.Proceedings of SPIE--the International Society for Optical Engineering · 2016
    Article
  18. Article
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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

8 authors at 5 institutions in 2 countries.

Jang-Hwan ChoiDepartment of Radiology, Stanford University, Stanford, California 94305 and Department of Mechanical Engineering, Stanford University, Stanford, California 94305.
Andreas MaierDepartment of Radiology, Stanford University, Stanford, California 94305.
Andreas KeilDepartment of Radiology, Stanford University, Stanford, California 94305.
Saikat PalBiomedical Engineering Department, California Polytechnic State University, San Luis Obispo, California 93407.
Emily J McWalterDepartment of Radiology, Stanford University, Stanford, California 94305.
Gary S BeaupréMusculoskeletal Research Laboratory, VA Palo Alto Health Care System, Palo Alto, California 94304.
Garry E GoldDepartment of Radiology, Stanford University, Stanford, California 94305.
Rebecca FahrigDepartment of Radiology, Stanford University, Stanford, California 94305.
Stanford University · US3D-Micromac (Germany) · DECalifornia Polytechnic State University · USFriedrich-Alexander-Universität Erlangen-Nürnberg · DEVA Palo Alto Health Care System · US

Funding

Weight-Bearing Imaging of the Knee Using C-Arm CTR01AR065248 · NIAMS · STANFORD UNIVERSITY · PI GOLD, GARRY E · 2015 to 2018
$2.0M
C-Arm CT for Guidence of Cardiac InterventionsR01HL087917 · NHLBI · STANFORD UNIVERSITY · PI FAHRIG, REBECCA · 2009 to 2010
$1.5M
Axiom zeego shared instrument grantS10RR026714 · NCRR · STANFORD UNIVERSITY · PI FAHRIG, REBECCA · 2010 to 2010
$500k
NCRR NIH HHS S10 RR026714NHLBI NIH HHS 1 R01HL087917NHLBI NIH HHS R01 HL087917NIAMS NIH HHS R01 AR065248
6 · The paper itself

Abstract

purposeA C-arm CT system has been shown to be capable of scanning a single cadaver leg under loaded conditions by virtue of its highly flexible acquisition trajectories. In Part I of this study, using the 4D XCAT-based numerical simulation, the authors predicted that the involuntary motion in the lower body of subjects in weight-bearing positions would seriously degrade image quality and the authors suggested three motion compensation methods by which the reconstructions could be corrected to provide diagnostic image quality. Here, the authors demonstrate that a flat-panel angiography system is appropriate for scanning both legs of subjects in vivo under weight-bearing conditions and further evaluate the three motion-correction algorithms using in vivo data.

methodsThe geometry of a C-arm CT system for a horizontal scan trajectory was calibrated using the PDS-2 phantom. The authors acquired images of two healthy volunteers while lying supine on a table, standing, and squatting at several knee flexion angles. In order to identify the involuntary motion of the lower body, nine 1-mm-diameter tantalum fiducial markers were attached around the knee. The static mean marker position in 3D, a reference for motion compensation, was estimated by back-projecting detected markers in multiple projections using calibrated projection matrices and identifying the intersection points in 3D of the back-projected rays. Motion was corrected using three different methods (described in detail previously): (1) 2D projection shifting, (2) 2D deformable projection warping, and (3) 3D rigid body warping. For quantitative image quality analysis, SSIM indices for the three methods were compared using the supine data as a ground truth.

resultsA 2D Euclidean distance-based metric of subjects' motion ranged from 0.85 mm (±0.49 mm) to 3.82 mm (±2.91 mm) (corresponding to 2.76 to 12.41 pixels) resulting in severe motion artifacts in 3D reconstructions. Shifting in 2D, 2D warping, and 3D warping improved the SSIM in the central slice by 20.22%, 16.83%, and 25.77% in the data with the largest motion among the five datasets (SCAN5); improvement in off-center slices was 18.94%, 29.14%, and 36.08%, respectively.

conclusionsThe authors showed that C-arm CT control can be implemented for nonstandard horizontal trajectories which enabled us to scan and successfully reconstruct both legs of volunteers in weight-bearing positions. As predicted using theoretical models, the proposed motion correction methods improved image quality by reducing motion artifacts in reconstructions; 3D warping performed better than the 2D methods, especially in off-center slices.

Indexed as

Fiducial MarkersMotionAlgorithmsArtifactsCalibrationComputer SimulationFour-Dimensional Computed TomographyHumansKneeLegModels, BiologicalPattern Recognition, AutomatedPhantoms, ImagingPostureRadiation DosageRadiographic Image Enhancement

Identifiers

PMID24877813
PMCPMC4008764
OpenAlexW2070705230

What OpenQuestion holds

Textmetadata
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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.