ECG Imaging to Detect the Site of Ventricular Ischemia Using Torso Electrodes: A Computational Study

Abstract

Electrocardiography provides some information useful for ischemic diagnosis. However, more recently there has been substantial growth in the area of ECG imaging, which by solving the inverse problem of electrocardiography aims to produce high-resolution mapping of the electrical and magnetic dynamics of the heart. Most inverse studies use the full resolution of the body surface potential (BSP) to reconstruct the epicardial potentials, however using a limited number of torso electrodes to interpolate the BSP is more clinically relevant and has an important effect on the reconstruction which must be quantified. A circular ischemic lesion on the right ventricle lateral wall 27 mm in radius is reconstructed using three Tikhonov methods along with 6 different electrode configurations ranging from 32 leads to 1,024 leads. The 2nd order Tikhonov solution performed the most accurately (~80% lesion identified) followed by the 1st (~50% lesion identified) and then the 0 order Tikhonov solution performed the worst with a maximum of ~30% lesion identified regardless of how many leads were used. With an increasing number of leads the solution produces less error, and the error becomes more localised around the lesion for all three regularisation methods. In noisy conditions, the relative performance gap of the 1st and 2nd order Tikhonov solutions was reduced, and determining an accurate regularisation parameter became relatively more difficult. Lesions located on the left ventricle walls were also able to be identified but comparatively to the right ventricle lateral wall performed marginally worse with lesions located on the interventricular septum being able to be indicated by the reconstructions but not successfully identified against the error. The quality of reconstruction was found to decrease as the lesion radius decreased, with a lesion radius of <20 mm becoming difficult to correctly identify against the error even when using >512 torso electrodes.

Generalization and Regularization for Inverse Cardiac Estimators

“…A recent study was devoted to analyze with detail the impact of signal processing techniques on the reconstructions of single-site pacing data on a torso-tank experimental setup [47], which mostly used elbow detection on the L-curve. Other studies proposing additional approaches in some setting also used elbow profiling [48]- [51]. The excellent review of the ECGI techniques by Gulrajani [52] stated that in general it is enough to retain the lowest regularization parameter which makes the solution stable.…”

Non‐invasive reconstruction of dynamic myocardial transmembrane potential with graph‐based total variation constraints

“…The most classic method is Tikhonov regularisation [8], which imposes a neighbourhood smoothing constraint and provides a solution with compromise accuracy. In recent years, combined with the sparsity and piece‐wise smoothness of the potential on the heart, reconstruction methods based on sparse expression have been proposed, such as total variation (TV) minimisation [9].…”