Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals

Zettinig, Oliver; Mansi, Tommaso; Neumann, Dominik; Georgescu, Bogdan; Rapaka, Saikiran; Seegerer, Philipp; Kayvanpour, Elham; Sedaghat‐Hamedani, Farbod; Amr, Ali; Haas, Jan; Steen, Henning; Katus, Hugo A.; Meder, Benjamin; Navab, Nassir; Kamen, Ali; Comanicìu, Dorin

doi:10.1016/j.media.2014.04.011

Cited by 44 publications

(49 citation statements)

References 53 publications

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“…[28][29][30] Patients with similar average or longest QRS duration may have different QRS duration distributions among the 12 leads. 31) QRS duration has been reported to closely associate with left ventricular dyssynchrony via the tissue Doppler image study.…”

Section: Discussionmentioning

confidence: 99%

The Shortest QRS Duration of an Electrocardiogram Might Be an Optimal Electrocardiographic Predictor for Response to Cardiac Resynchronization Therapy

2017

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SummaryQRS duration has been associated with the response to cardiac resynchronization therapy (CRT). However, the methods for defining QRS duration to predict the outcome of CRT have discrepancies in previous reports. The aim of this study was to determine an optimal measurement of QRS duration to predict the response to CRT.Sixty-one patients who received CRT were analyzed. All patients had class III-IV heart failure, left ventricular ejection fraction not more than 35%, and complete left bundle branch block. The shortest, longest, and average QRS durations from the 12 leads of each electrocardiogram (ECG) were measured. The responses to CRT were determined using the changes in echocardiography after 6 months. Thirty-five (57.4%) patients were responders and 26 (42.6%) patients were non-responders. The pre-procedure shortest, average, and longest QRS durations and the QRS shortening (ΔQRS) of the shortest QRS duration were significantly associated with the response to CRT in a univariate logistic regression analysis (P = 0.002, P = 0.03, P = 0.04 and P = 0.04, respectively). Based on the measurement of the area under curve of the receiver operating characteristic curve, only the pre-procedure shortest QRS duration and the ΔQRS of the shortest QRS duration showed significant discrimination for the response to CRT (P = 0.002 and P = 0.038, respectively). Multivariable logistic regression showed the pre-procedure shortest QRS duration is an independent predictor for the response to CRT.The shortest QRS duration from the 12 leads of the electrocardiogram might be an optimal measurement to predict the response to CRT. (Int Heart J 2017; 58: 530-535) Key words: Heart failure C ardiac resynchronization therapy (CRT) is a wellknown procedure for improving left ventricular function via reverse remodeling in patients with heart failure.1) The QRS durations before implantation and at follow-up may predict the patient's response to CRT, especially in the presence of left bundle branch block (LBBB).2-8) However, the QRS durations are usually different and diverse among the 12-lead electrocardiogram (ECG). 9) Additionally, in previous reports, the methods to define the QRS duration in predicting a CRT patient's outcome have discrepancies and lack standardization of QRS duration measurement.10) Many different methods for QRS duration measurement have been used in previous studies, including the QRS duration of one selected lead, 11,12) the longest QRS duration, 13) the average QRS duration of 12 leads, 14) and undefined. 6,15,16) International guidelines for heart failure management also have not recommended a preferred standard measurement technique for QRS duration for CRT.2,10,17,18) Lack of standard measurement in the QRS duration might have a significant influence on the conclusions of different studies.10) Thus, this is the crucial reason why the recommended QRS duration for CRT implantation was different and variable in previous reports. However, the decision-making for suggesting that a patient receive a CRT implanta...

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Section: Discussionmentioning

confidence: 99%

The Shortest QRS Duration of an Electrocardiogram Might Be an Optimal Electrocardiographic Predictor for Response to Cardiac Resynchronization Therapy

2017

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“…Logically, τ close varies very little, since it is directly linked to the QT duration, that is not much affected by fibre orientation. Finally, the observed variabilities should be compared to the intrinsic uncertainty due to the parameter estimation process (quantified as high as 45% for c RV in some cases) [4].…”

Section: Uncertainty On the Model Parameters And Discussionmentioning

confidence: 99%

“…Cardiac electrophysiology (EP) is modelled using the approach presented in [4]. Cardiac transmembrane potentials are calculated according to the mono-domain Mitchell-Schaeffer (MS) model as it offers a good compromise between model observability and fidelity (The equations are recalled in the supplementary material).…”

Section: Personalised Cardiac Electrophysiology Modelmentioning

confidence: 99%

“…We model fast regional diffusivity for the left c LV and right c RV endocardium to mimic the fast conducting Purkinje network, and slower diffusivity c myo ≤ c LV , c myo ≤ c RV , for the myocardium. Transmembrane potentials are calculated using LBM-EP, a Lattice-Boltzmann method, which is coupled to a boundary element method approach to calculate the 12-lead cardiac electrocardiogram (ECG) resulting from the cardiac potentials [4]. The model is finally personalised like in [8,9].…”

Section: Personalised Cardiac Electrophysiology Modelmentioning

confidence: 99%

“…cardiac resynchronization therapy, or radiofrequency ablation). In order to impact clinical practice, generic models have to be adjusted to a given patient, which is personalisation [1][2][3][4]. This is still a challenging part, and often computationally demanding, therefore most of the approaches are deterministic.…”

Section: Introductionmentioning

confidence: 99%

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Abstract. Computer models of the heart are of increasing interest for clinical applications due to their discriminative and predictive power. However the personalisation step to go from a generic model to a patientspecific one is still a scientific challenge. In particular it is still difficult to quantify the uncertainty on the estimated parameters and predicted values. In this manuscript we present a new pipeline to evaluate the impact of fibre uncertainty on the personalisation of an electromechanical model of the heart from ECG and medical images. We detail how we estimated the variability of the fibre architecture among a given population and how the uncertainty generated by this variability impacts the following personalisation. We first show the variability of the personalised simulations, with respect to the principal variations of the fibres. Then discussed how the variations in this (small) healthy population of fibres impact the parameters of the personalised simulations.

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How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post‐infarction patients

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Precision Cardiology is a targeted strategy for cardiovascular disease prevention and treatment that accounts for individual variability. Computational heart modeling is one of the novel approaches that have been developed under the umbrella of Precision Cardiology. Personalized computational modeling of patient hearts has made strides in the development of models that incorporate the individual geometry and structure of the heart as well as other patient‐specific information. Of these developments, one of the potentially most impactful is the research aimed at noninvasively predicting the targets of ablation of lethal arrhythmia, ventricular tachycardia (VT), using patient‐specific models. The approach has been successfully applied to patients with ischemic cardiomyopathy in proof‐of‐concept studies. The goal of this paper is to review the strategies for computational VT ablation guidance in ischemic cardiomyopathy patients, from model developments to the intricacies of the actual clinical application. To provide context in describing the road these computational modeling applications have undertaken, we first review the state of the art in VT ablation in the clinic, emphasizing the benefits that personalized computational prediction of ablation targets could bring to the clinical electrophysiology practice. This article is characterized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine

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Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals

Cited by 44 publications

References 53 publications

The Shortest QRS Duration of an Electrocardiogram Might Be an Optimal Electrocardiographic Predictor for Response to Cardiac Resynchronization Therapy

The Shortest QRS Duration of an Electrocardiogram Might Be an Optimal Electrocardiographic Predictor for Response to Cardiac Resynchronization Therapy

Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study

How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post‐infarction patients

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