ABSTRACT
Myocardial infarct patients have an increased risk of scar-based ventricular tachycardia. Late gadolinium enhanced magnetic resonance (MR) imaging provides the geometric extent of myocardial infarct. Computational electrophysiological models based on such images can provide a personalized prediction of the patient's tachycardia risk. In this work, the effect of respiratory slice alignment image artifacts on image-based electrophysiological simulations is investigated in two series of models. For the first series, a clinical MR image is used in which slice translations are applied to artificially induce and correct for slice misalignment. For the second series, computer simulated MR images with and without slice misalignments are created using a mechanistic anatomical phantom of the torso. From those images, personalized models are created in which electrical stimuli are applied in an attempt to induce tachycardia. The response of slice-aligned and slice-misaligned models to different interval stimuli is used to assess tachycardia risk. The presented results indicate that slice misalignments affect image-based simulation outcomes. The extent to which the assessed risk is affected is found to depend upon the geometry of the infarct area. The number of unidirectional block tachycardias varied from 1 to 3 inducible patterns depending on slice misalignment severity and, along with it, the number of tachycardia inducing stimuli locations varied from 2 to 4 from 6 different locations. For tachycardias sustained by conducting channels through the scar core, no new patterns are induced by altering the slice alignment in the corresponding image. However, it affected the assessed risk as tachycardia inducing stimuli locations varied from 1 to 5 from the 6 stimuli locations. In addition, if the conducting channel is not maintained in the image due to slice misalignments, the channel-dependent tachycardia is not inducible anymore in the image-based model.
Subject(s)
Artifacts , Electrophysiologic Techniques, Cardiac , Computer Simulation , Gadolinium , Humans , Magnetic Resonance ImagingABSTRACT
BACKGROUND: The purpose of this study was to illustrate the additive value of computed tomography angiography (CTA) for visualisation of the coronary venous anatomy prior to cardiac resynchronisation therapy (CRT) implantation. METHODS: Eighteen patients planned for CRT implantation were prospectively included. A specific CTA protocol designed for visualisation of the coronary veins was carried out on a third-generation dual-source CT platform. Coronary veins were semi-automatically segmented to construct a 3D model. CTA-derived coronary venous anatomy was compared with intra-procedural fluoroscopic angiography (FA) in right and left anterior oblique views. RESULTS: Coronary venous CTA was successfully performed in all 18 patients. CRT implantation and FA were performed in 15 patients. A total of 62 veins were visualised; the number of veins per patient was 3.8 (range: 2-5). Eighty-five per cent (53/62) of the veins were visualised on both CTA and FA, while 10% (6/62) were visualised on CTA only, and 5% (3/62) on FA only. Twenty-two veins were present on the lateral or inferolateral wall; of these, 95% (21/22) were visualised by CTA. A left-sided implantation was performed in 13 patients, while a right-sided implantation was performed in the remaining 2 patients because of a persistent left-sided superior vena cava with no left innominate vein on CTA. CONCLUSION: Imaging of the coronary veins by CTA using a designated protocol is technically feasible and facilitates the CRT implantation approach, potentially improving the outcome.
ABSTRACT
Electrical activity at the level of the heart muscle can be noninvasively reconstructed from body-surface electrocardiograms (ECGs) and patient-specific torso-heart geometry. This modality, coined electrocardiographic imaging, could fill the gap between the noninvasive (low-resolution) 12-lead ECG and invasive (high-resolution) electrophysiology studies. Much progress has been made to establish electrocardiographic imaging, and clinical studies appear with increasing frequency. However, many assumptions and model choices are involved in its execution, and only limited validation has been performed. In this article, we will discuss the technical details, clinical applications and current limitations of commonly used methods in electrocardiographic imaging. It is important for clinicians to realise the influence of certain assumptions and model choices for correct and careful interpretation of the results. This, in combination with more extensive validation, will allow for exploitation of the full potential of noninvasive electrocardiographic imaging as a powerful clinical tool to expedite diagnosis, guide therapy and improve risk stratification.
