Spatially Adaptive Multi-Scale Optimization for Local Parameter Estimation in Cardiac Electrophysiology.

To obtain a patient-specific cardiac electro-physiological (EP) model, it is important to estimate the 3-D distributed tissue properties of the myocardium. Ideally, the tissue property should be estimated at the resolution of the cardiac mesh. However, such high-dimensional estimation faces major challenges in identifiability and computation. Most existing works reduce this dimension by partitioning the cardiac mesh into a pre-defined set of segments. The resulting low-resolution solutions have a limited ability to represent the underlying heterogeneous tissue properties of varying sizes, locations, and distributions. In this paper, we present a novel framework that, going beyond a uniform low-resolution approach, is able to obtain a higher resolution estimation of tissue properties represented by spatially non-uniform resolution. This is achieved by two central elements: 1) a multi-scale coarse-to-fine optimization that facilitates higher resolution optimization using the lower resolution solution and 2) a spatially adaptive decision criterion that retains lower resolution in homogeneous tissue regions and allows higher resolution in heterogeneous tissue regions. The presented framework is evaluated in estimating the local tissue excitability properties of a cardiac EP model on both synthetic and real data experiments. Its performance is compared with optimization using pre-defined segments. Results demonstrate the feasibility of the presented framework to estimate local parameters and to reveal heterogeneous tissue properties at a higher resolution without using a high number of unknowns.

Examining the Impact of Prior Models in Transmural Electrophysiological Imaging: A Hierarchical Multiple-Model Bayesian Approach.

Noninvasive cardiac electrophysiological (EP) imaging aims to mathematically reconstruct the spatiotemporal dynamics of cardiac sources from body-surface electrocardiographic (ECG) data. This ill-posed problem is often regularized by a fixed constraining model. However, a fixed-model approach enforces the source distribution to follow a pre-assumed structure that does not always match the varying spatiotemporal distribution of actual sources. To understand the model-data relation and examine the impact of prior models, we present a multiple-model approach for volumetric cardiac EP imaging where multiple prior models are included and automatically picked by the available ECG data. Multiple models are incorporated as an Lp-norm prior for sources, where p is an unknown hyperparameter with a prior uniform distribution. To examine how different combinations of models may be favored by different measurement data, the posterior distribution of cardiac sources and hyperparameter p is calculated using a Markov Chain Monte Carlo (MCMC) technique. The importance of multiple-model prior was assessed in two sets of synthetic and real-data experiments, compared to fixed-model priors (using Laplace and Gaussian priors). The results showed that the posterior combination of models (the posterior distribution of p) as determined by the ECG data differed substantially when reconstructing sources with different sizes and structures. While the use of fixed models is best suited in situations where the prior assumption fits the actual source structures, the use of an automatically adaptive set of models may have the ability to better address model-data mismatch and to provide consistent performance in reconstructing sources with different properties.

Race- and sex-associated differences in rate-adjusted QT, QTpeak, ST elevation and other regional measures of repolarization: the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: Data are limited about race-and sex-associated differences in prognostically important ECG measures of regional repolarization. METHODS AND RESULTS: The normal reference group from the Atherosclerosis Risk in Communities (ARIC) study included 8,676 white and African-American men and women aged 40-65 years. Exclusion criteria included cardiovascular disease, hypertension, diabetes and major ECG abnormalities. Notable sex differences (p<0.001) were observed in the upper 98% limits for rate-adjusted QTend (QTea) which was 435 ms in white and African-American men and 445 ms in white and African-American women, and for left ventricular epicardial repolarization time (RTepi) which was 345 ms in white and African-American men and 465 ms in white and African-American women. These sex differences reflect earlier onset and end of repolarization in men than in women. Upper normal limits for STJ amplitude in V2-V3 were 100 µV in white and African-American women, 150 µV in white men and 200 µV in African-American men (p<0.001 for sex differences), and for other chest leads, aVL and aVF 50 µV in white women, 100 µV in African-American women, 100 µV in white men and 150 µV in African-American men (p<0.001 for sex and race differences). CONCLUSIONS: Shorter QTea and RTepi in men than in women reflect earlier onset and end of repolarization in men. STJ amplitudes in African-American men were higher than in other subgroups by race and sex. These sex and race differences need to be considered in clinical and epidemiological applications of normal standards.

Normal standards for computer-ECG programs for prognostically and diagnostically important ECG variables derived from a large ethnically diverse female cohort: the Women's Health Initiative (WHI).

BACKGROUND: Substantial new information has emerged recently about the prognostic value for a variety of new ECG variables. The objective of the present study was to establish reference standards for these novel risk predictors in a large, ethnically diverse cohort of healthy women from the Women's Health Initiative (WHI) study. METHODS AND RESULTS: The study population consisted of 36,299 healthy women. Racial differences in rate-adjusted QT end (QT(ea)) and QT peak (QT(pa)) intervals as linear functions of RR were small, leading to the conclusion that 450 and 390 ms are applicable as thresholds for prolonged and shortened QT(ea) and similarly, 365 and 295 ms for prolonged and shortened QT(pa), respectively. As a threshold for increased dispersion of global repolarization (T(peak)T(end) interval), 110 ms was established for white and Hispanic women and 120 ms for African-American and Asian women. ST elevation and depression values for the monitoring leads of each person with limb electrodes at Mason-Likar positions and chest leads at level of V1 and V2 were first computed from standard leads using lead transformation coefficients derived from 892 body surface maps, and subsequently normal standards were determined for the monitoring leads, including vessel-specific bipolar left anterior descending, left circumflex artery and right coronary artery leads. The results support the choice 150 µV as a tentative threshold for abnormal ST-onset elevation for all monitoring leads. Body mass index (BMI) had a profound effect on Cornell voltage and Sokolow-Lyon voltage in all racial groups and their utility for left ventricular hypertrophy classification remains open. CONCLUSIONS: Common thresholds for all racial groups are applicable for QT(ea), and QT(pa) intervals and ST elevation. Race-specific normal standards are required for many other ECG parameters.

Susceptibility for ventricular tachycardia and the correlation between depolarization and orthogonal components of repolarization.

OBJECTIVE: There is a continuing need of methods to identify subgroups of patients at high risk of ventricular arrhythmias, in particular after myocardial infarction (MI). METHODS: We performed a singular value decomposition of repolarization potentials in individual recordings in 134 healthy males, in 203 males with old MI and without documented sustained ventricular tachycardia (VT) and in 104 MI males with documented VT. We considered the absolute correlation coefficient between the first orthogonal component, constructed by matrix multiplication of the first left and right singular vectors and the QRS integral (RT1) and a similar index for the second component (RT2). RESULTS: Abnormally high (more than two standard deviations above the mean) value of the RT1 had a 89% specificity for VT in MI patients. Abnormally low RT2 had specificity of 87%. Both indices combined had a 97% specificity. However, sensitivity of the combined indices was only 13%. CONCLUSION: Abnormalities in the correlation of orthogonal components of repolarization with depolarization are highly specific for a small group of patients with old myocardial infarction at high risk of ventricular tachycardia.