Evidence map›Paper›PMID 29386056›Full record

ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2018

Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging.

Ruixi Zhou, Wei Huang, Yang Yang, Xiao Chen, Daniel S Weller, Christopher M Kramer, Sebastian Kozerke, Michael Salerno

Erratum issuedAbstract read
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Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. DynamicMagnetic resonance in medicine · 2024
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  14. Dual-excitation flip-angle simultaneous cine and TMagnetic resonance in medicine · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Ruixi ZhouDepartment of Medicine, University of Virginia Health System, Charlottesville, VA, USA.
Wei HuangDepartment of Medicine, University of Virginia Health System, Charlottesville, VA, USA.
Yang YangDepartment of Medicine, University of Virginia Health System, Charlottesville, VA, USA.
Xiao ChenMedical Imaging Technologies, Siemens Healthineers, Princeton, NJ, USA.
Daniel S WellerDepartment of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA.
Christopher M KramerDepartment of Medicine, University of Virginia Health System, Charlottesville, VA, USA.
Sebastian KozerkeDepartment of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
Michael SalernoDepartment of Medicine, University of Virginia Health System, Charlottesville, VA, USA. ms5pc@virginia.edu.ORCID 0000-0001-7051-1031

Funding

High-Resolution Whole Heart Quantitative CMR Perfusion Imaging in Ischemic Heart DiseaseR01HL131919 · NHLBI · UNIVERSITY OF VIRGINIA · PI ENNIS, DANIEL B · 2017 to 2021
$3.5M
Quantitative Adenosine Stress CMR with Spiral Pulse SequencesK23HL112910 · NHLBI · UNIVERSITY OF VIRGINIA · PI SALERNO, MICHAEL · 2012 to 2016
$789k
NHLBI NIH HHS K23 HL112910NHLBI NIH HHS R01 HL131919
6 · The paper itself

Abstract

backgroundCardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging.

methodsA simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists.

resultsIn the phantom experiments, images reconstructed with the MC strategy had higher SSIM (p < 0.01) and lower RMSE (p < 0.01) in the presence of respiratory motion. For patient studies, the MC strategy improved k-t PCA and k-t SLR reconstruction image quality (p < 0.01). The performance of k-t SLR without motion correction demonstrated improved image quality as compared to k-t PCA in the setting of respiratory motion (p < 0.01), while with motion correction there is a trend of better performance in k-t SLR as compared with motion corrected k-t PCA.

conclusionsOur simple and robust rigid motion compensation strategy greatly reduces motion artifacts and improves image quality for standard k-t PCA and k-t SLR techniques in setting of respiratory motion due to imperfect breath-holding.

Indexed as

Coronary CirculationRespirationArtifactsBlood Flow VelocityBreath HoldingCoronary Artery DiseaseHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMyocardial Perfusion ImagingPhantoms, ImagingPredictive Value of TestsReproducibility of ResultsCMR perfusionImage reconstructionK-t accelerationMotion compensationMyocardial perfusion

Identifiers

PMID29386056
PMCPMC5793398

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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.