Atrial and Ventricular Myocardium Extraction Using Model-based Techniques

Single-beat noninvasive imaging of ventricular endocardial and epicardial activation in patients undergoing CRT

Background

Little is known about the effect of cardiac resynchronization therapy (CRT) on endo- and epicardial ventricular activation. Noninvasive imaging of cardiac electrophysiology (NICE) is a novel imaging tool for visualization of both epi- and endocardial ventricular electrical activation.

Methodology/Principal Findings

NICE was performed in ten patients with congestive heart failure (CHF) undergoing CRT and in ten patients without structural heart disease (control group). NICE is a fusion of data from high-resolution ECG mapping with a model of the patient's individual cardiothoracic anatomy created from magnetic resonance imaging. Beat-to-beat endocardial and epicardial ventricular activation sequences were computed during native rhythm as well as during ventricular pacing using a bidomain theory-based heart model to solve the related inverse problem. During right ventricular (RV) pacing control patients showed a deterioration of the ventricular activation sequence similar to the intrinsic activation pattern of CHF patients. Left ventricular propagation velocities were significantly decreased in CHF patients as compared to the control group (1.6±0.4 versus 2.1±0.5 m/sec; p<0.05). CHF patients showed right-to-left septal activation with the latest activation epicardially in the lateral wall of the left ventricle. Biventricular pacing resulted in a resynchronization of the ventricular activation sequence and in a marked decrease of total LV activation duration as compared to intrinsic conduction and RV pacing (129±16 versus 157±28 and 173±25 ms; both p<0.05).

Conclusions/Significance

Endocardial and epicardial ventricular activation can be visualized noninvasively by NICE. Identification of individual ventricular activation properties may help identify responders to CRT and to further improve response to CRT by facilitating a patient-specific lead placement and device programming.

Single-beat noninvasive imaging of cardiac electrophysiology of ventricular pre-excitation

OBJECTIVES

The aim of this study was to determine whether noninvasive imaging of cardiac electrophysiology (NICE) is feasible in patients with Wolff-Parkinson-White (WPW) syndrome in the clinical setting of a catheter laboratory and to test the accuracy of the noninvasively obtained ventricular activation sequences as compared with that of standard invasive electroanatomic mapping.

BACKGROUND

NICE of ventricular activation could serve as a useful tool in the treatment of cardiac arrhythmias and might help improve our understanding of arrhythmia mechanisms.

METHODS

NICE works by fusing the data from high-resolution electrocardiographic mapping and a model of the patient's cardiac anatomy obtained by magnetic resonance imaging. The ventricular activation sequence was computed with a bidomain theory-based heart model to solve this inverse problem. Noninvasive imaging of cardiac electrophysiology was performed in 7 patients with WPW syndrome undergoing catheter ablation of the accessory pathway. The position error of NICE was defined as the distance between the site of earliest activation computed by NICE and the successful ablation site identified by electroanatomic mapping (CARTO; Biosense Webster, Diamond Bar, California) for normal atrioventricular (AV) conduction as well as for adenosine-induced AV block.

RESULTS

The error introduced by geometric coupling of the CARTO data and the NICE model was 5 +/- 3 mm (model discretization 10 mm). All ventricular accessory pathway insertion sites were identified with an accuracy of 18.7 +/- 5.8 mm (baseline) and 18.7 +/- 6.4 mm (adenosine).

CONCLUSIONS

The individual cardiac anatomy model obtained for each patient enables accurate noninvasive electrocardiographic imaging of ventricular pre-excitation in patients with WPW syndrome. Noninvasive imaging of cardiac electrophysiology might be used as a complementary noninvasive approach to localize the origin and help identify and understand the underlying mechanisms of cardiac arrhythmias.

Semiautomatic volume conductor modeling pipeline for imaging the cardiac electrophysiology noninvasively

In this paper we present an approach for extracting patient individual volume conductor models (VCM) using volume data acquired from Magnetic Resonance Imaging (MRI) for computational biology of electrical excitation in the patient's heart. The VCM consists of the compartments chest surface, lung surfaces, the atrial and ventricular myocardium, and the blood masses. For each compartment a segmentation approach with no or little necessity of user interaction was implemented and integrated into a VCM segmentation pipeline to enable the inverse problem of electrocardiography to become clinical applicable. The segmentation pipeline was tested using volume data from ten patients with structurally normal hearts.