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Predictors of Cardiac Implantable Electronic Device Artifact on Cardiac MRI: The Utility of a Device Related Score

Authors :
Scott D. Flamm
Deborah H Kwon
Duygu Kocyigit
Bruce L. Wilkoff
Mostafa Abozeed
Christine Jellis
Source :
Heart, Lung and Circulation. 30:1348-1355
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Cardiac magnetic resonance imaging (CMR) image quality can be degraded by artifact in patients with cardiac implantable electronic devices (CIED). We aimed to establish a clinical risk score, so patient selection for diagnostic CMR could be optimised.In this retrospective cohort study, CMRs performed for clinical use in subjects with CIED from January 2016 to May 2019 were reviewed. Subject anthropometry, CIED generator/lead specifications and pre-scan chest X-ray (CXR) measurements were collected. Generator-related artifact size was measured on axial steady state free precession images. Interpretability of late gadolinium enhancement (LGE) imaging was performed based on a three-grade visual score attributed to each of 17 myocardial segments.Fifty-seven (57) patients (59±16 years, 74% male) fitted the inclusion criteria. Artifact precluded left ventricle (LV) evaluation (≥5 segments) in 17 (30%). Artifact was more common with implantable cardioverter-defibrillators, related to generator volume, mass, height, width, thickness, and area, along with right ventricular (RV) lead length and diameter (all p0.05). Artifact was associated with distance from generator to LV apex, generator to RV lead tip and shortest distance from generator to heart on CXR (all p0.05). On multivariable regression modelling, RV lead diameter (OR 5.861, 95% CI 1.866-18.407, p=0.002) and distance from generator to LV apex (OR 0.693, 95% CI 0.511-0.940, p=0.019) were independent predictors of artifact. Multivariable predictors were used to develop Device Related CMR Artifact Prediction Score (DR-CAPS), where all patients with DR-CAPS=0 had fully interpretable LGE imaging.Simple, readily available measures, such as lead characteristics and pre-scan CXR measures, can stratify patients via an artifact prediction score to optimise selection for diagnostic CMR.

Details

ISSN :
14439506
Volume :
30
Database :
OpenAIRE
Journal :
Heart, Lung and Circulation
Accession number :
edsair.doi.dedup.....8b47301cdd748b4779fe154e50f79ad3
Full Text :
https://doi.org/10.1016/j.hlc.2021.02.011