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

PURPOSE

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.

METHODS

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.

RESULTS

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 p<0.05). 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 p<0.05). 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.

CONCLUSION

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.