Exploring vectorcardiography: An extensive vectocardiogram analysis across age, sex, BMI, and cardiac conditions.

BACKGROUND: The vectocardiogram (VCG) offers a three-dimensional view of the heart's electrical activity, yet many VCG parameters remain unexplored in diverse clinical contexts. OBJECTIVES: This study aims to explore the relationships between various VCG parameters and specific patient characteristics. METHODS: ECG signals from adults were transformed into VCGs utilizing the Kors matrix, yielding 315 parameters per patient from the P, QRS and T loops. Univariable analysis, circular statistics, and stepwise logistic regression were employed to examine the relationships between VCG parameters and factors such as age, sex, BMI, hypertension, echocardiographic ischemic heart disease (Echo-IHD), and left ventricular hypertrophy (Echo-LVH). RESULTS: We included 664 adults and considered an alpha value of 0.05 and a power of 90%. The study revealed significant associations, such as age with P loop roundness index (RI) (OR = 3.825, 95% confidence interval [95%CI] = 2.079-7.04), male sex with QRS loop RI (OR = 6.08, 95%CI = 1.835-20.153), abnormal BMI with the T loop's RI (OR = 0.544, 95%CI = 0.325-0.909), hypertension with the T loop planarity index (PI) (OR = 8.01, 95%CI = 2.134-30.117), Echo-IHD with QRS loop curvature at the 4/10th segment (OR = 7.58, 95%CI = 1.954-29.458), and Echo-LVH with the T loop lag-1/10 dihedral angle (OR = 10.3, 95%CI = 1.822-58.101). In the study, several additional VCG parameters demonstrated statistically significant, albeit smaller, associations with patient demographics and cardiovascular conditions. CONCLUSIONS: The findings enhance our understanding of the intricate relationships between VCG parameters and patient characteristics, emphasizing the potential role of VCG analysis in assessing cardiovascular diseases. These insights may guide future research and clinical applications in cardiology.

Present results and methods of vectorcardiographic diagnostics of ischemic heart disease.

This article presents an overview of existing approaches to perform vectorcardiographic (VCG) diagnostics of ischemic heart disease (IHD). Individual methodologies are divided into categories to create a comprehensive and clear overview of electrical cardiac activity measurement, signal pre-processing, features extraction and classification procedures. An emphasis is placed on methods describing the electrical heart space (EHS) by several features extraction techniques based on spatiotemporal characteristics or signal modelling and signal transformations. Performance of individual methodologies are compared depending on classification of extent of ischemia, acute forms - myocardial infarction (MI) and myocardial scars localization. Based on a comparison of imaging methods, the advantages of VCG over the standard 12-leads ECG such as providing a 3D orthogonal leads imaging, better performance, and appropriate computer processing are highlighted. The issues of electrical cardiac activity measurements on body surface, the lack of VKG databases supported by a more accurate imaging method, possibility of comparison with the physiology of individual cases are outlined as potential reserves for future research.

Spatiotemporal repolarization dispersion before and after exercise in patients with long QT syndrome type 1 versus controls: probing into the arrhythmia substrate.

Congenital long QT syndrome (LQTS) carries an increased risk for syncope and sudden death. QT prolongation promotes ventricular extrasystoles, which, in the presence of an arrhythmia substrate, might trigger ventricular tachycardia degenerating into fibrillation. Increased electrical heterogeneity (dispersion) is the suggested arrhythmia substrate in LQTS. In the most common subtype LQT1, physical exercise predisposes for arrhythmia and spatiotemporal dispersion was therefore studied in this context. Thirty-seven patients (57% on ß-blockers) and 37 healthy controls (mean age, 31 vs. 35; range, 6-68 vs. 6-72 yr) performed an exercise test. Frank vectorcardiography was used to assess spatiotemporal dispersion as Tampl, Tarea, the ventricular gradient (VG), and the Tpeak-end interval from 10-s signal averages before and 7 ± 2 min after exercise; during exercise too much signal disturbance excluded analysis. Baseline and maximum heart rates as well as estimated exercise intensity were similar, but heart rate recovery was slower in patients. At baseline, QT and heart rate-corrected QT (QTcB) were significantly longer in patients (as expected), whereas dispersion parameters were numerically larger in controls. After exercise, QTpeakcB and Tpeak-endcB increased significantly more in patients (18 ± 23 vs. 7 ± 10 ms and 12 ± 17 vs. 2 ± 6 ms; P < 0.001 and P < 0.01). There was, however, no difference in the change in Tampl, Tarea, and VG between groups. In conclusion, although temporal dispersion of repolarization increased significantly more after exercise in patients with LQT1, there were no signs of exercise-induced increase in global dispersion of action potential duration and morphology. The arrhythmia substrate/mechanism in LQT1 warrants further study.NEW & NOTEWORTHY Physical activity increases the risk for life-threatening arrhythmias in LQTS type 1 (LQT1). The arrhythmia substrate is presumably altered electrical heterogeneity (a.k.a. dispersion). Spatiotemporal dispersion parameters were therefore compared before and after exercise in patients versus healthy controls using Frank vectorcardiography, a novelty. Physical exercise prolonged the time between the earliest and latest complete repolarization in patients versus controls, but did not increase parameters reflecting global dispersion of action potential duration and morphology, another novelty.

BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis.

BACKGROUND AND OBJECTIVES: Electrocardiographic (ECG) and vectorcardiographic (VCG) analyses are used to diagnose current cardiovascular disease and for risk stratification for future adverse cardiovascular events. With increasing use of digital ECGs, research into novel ECG/VCG parameters has increased, but widespread computer-based ECG/VCG analysis is limited because there are no currently available, open-source, and easily customizable software packages designed for automated and reproducible analysis. METHODS AND RESULTS: We present BRAVEHEART, an open-source, modular, customizable, and easy to use software package implemented in the MATLAB programming language, for scientific analysis of standard 12-lead ECGs acquired in a digital format. BRAVEHEART accepts a wide variety of digital ECG formats and provides complete and automatic ECG/VCG processing with signal denoising to remove high- and low-frequency artifact, non-dominant beat identification and removal, accurate fiducial point annotation, VCG construction, median beat construction, customizable measurements on median beats, and output of measurements and results in numeric and graphical formats. CONCLUSIONS: The BRAVEHEART software package provides easily customizable scientific analysis of ECGs and VCGs. We hope that making BRAVEHART available will allow other researchers to further the field of ECG/VCG analysis without having to spend significant time and resources developing their own ECG/VCG analysis software and will improve the reproducibility of future studies. Source code, compiled executables, and a detailed user guide can be found at http://github.com/BIVectors/BRAVEHEART. The source code is distributed under the GNU General Public License version 3.

Automated Localization of Myocardial Infarction From Vectorcardiographic via Tensor Decomposition.

OBJECTIVE: Myocardial infarction (MI) causes rapid and permanent damage to the heart muscle. Therefore, it can deteriorate the myocardial structure and function if not timely diagnosed and treated. However, it is difficult to determine the precise localization of MI based on vectorcardiogram (VCG) due to the existing studies ignore the spatiotemporal features of VCG. METHODS: In this paper, a precise MI localization method was proposed based on Tucker decomposition. The multi-scale characteristics of wavelet transform and the spatiotemporal characteristics of VCG were used to construct the VCG tensor containing the local and the spatiotemporal information. The VCG tensor was compressed in the time dimension based on Tucker decomposition to remove redundant information and extract the local spatiotemporal features. The features were fed back to the TreeBagger classifier. RESULTS: The proposed method achieved a total accuracy of 99.80% for 11 types of MI on the benchmark Physikalisch-Technische Bundesanstalt database. The area under the receiver operating characteristic curves and precision-recall curves of each kind of VCG signal was more than 0.88. CONCLUSION: The proposed algorithm effectively realized the classification of normal and 11 categories of MI using VCG. SIGNIFICANCE: Therefore, this study provides new ideas for the intelligent diagnosis of MI based on VCG.

[On the history of vectorcardiography: past, present, future].

The vector concept in the analysis of the electrical signals of the heart began to be used at the dawn of the development of electrocardiology. For several decades, vectorcardiography has developed in parallel with electrocardiography; reached its peak in the 60s, and after a period of cooling experienced a resurgence since the early 90s, when it became possible to mathematically synthesize vectorcardiograms (VCG) from digital electrocardiograms in 12 leads. VCG reflects the same phenomena as electrocardiography, but allows you to calculate and visualize a number of three-dimensional characteristics of the electrical signals of the heart. The article describes the main milestones in the development of the VCG, the history of international cooperation in this area, the contribution of domestic scientists to this field of science. Modern promising areas of research related to the vector concept of the analysis of the electrical signals of the heart are briefly reflected.

Noninvasive electrophysiological differences between women and men: differences in body size not an explanation.

There are numerous sex-related differences in cardiac electrophysiology and arrhythmia propensity but very little knowledge about the reasons. Difference in body size has been proposed as one reason and was tested in this study of >20 cardiac electrophysiology parameters in 319 (158 women) apparently healthy 50- to 64-yr-old subjects from a randomly enrolled population sample, the pilot SCAPIS (Swedish Cardiopulmonary Bioimaging Study), using Frank vectorcardiography. We studied conventional conduction intervals, parameters reflecting electrical heterogeneity (dispersion) in the ventricles, QRS- and T-vector directions, spatial QRS-T angles, and T-vector loop morphology. Body surface area (BSA; 2 methods) and lean body mass (LBM), both estimated from body weight and height, were used as body size parameters. According to multivariable linear regression analysis adjusted for sex, there was no association between electrophysiological parameters and body size apart from QRS duration and QRSarea. In conclusion, most electrophysiological parameters assessed completely noninvasively and showing statistically significant differences between women and men on the group level show no association with BSA or LBM. Scaling (indexing) the electrophysiological parameters for body size parameters is therefore not an option. Consequently, the explanation for the sex-related electrophysiological differences should be sought along other lines.NEW & NOTEWORTHY We sought explanations for sex-related differences in >20 cardiac electrophysiology parameters including conventional conduction intervals in 319 (158 women) apparently healthy 50- to 64-yr-old subjects using Frank vectorcardiography, a novelty. Our hypothesis that body size was partly explanatory for such differences had to be refuted apart from QRS duration and QRSarea. Scaling (indexing) electrophysiological parameters for body size is therefore not an option and explanations for electrophysiological sex-related differences are to be sought elsewhere.

Statistical Evaluation of Transformation Methods Accuracy on Derived Pathological Vectorcardiographic Leads.

Objective: Vectorcardiography (VCG) as an alternative form of ECG provides important spatial information about the electrical activity of the heart. It achieves higher sensitivity in the detection of some pathologies such as myocardial infarction, ischemia and hypertrophy. However, vectorcardiography is not commonly measured in clinical practice, and for this reason mathematical transformations have been developed to obtain derived VCG leads, which in application in current systems and subsequent analysis can contribute to early diagnosis and obtaining other useful information about the electrical activity of the heart. Methods and procedures: The most frequently used transformation methods are compared, namely the Kors regression method, the Inverse Dower transformation, QLSV and the Quasi-orthogonal transformation. These transformation methods were used on 30 randomly selected records with a diagnosis of myocardial infarction from the Physikalisch-Technische Bundesanstalt (PTB) database and their accuracy was evaluated based on the calculation of the mean square error (MSE). MSE was subjected to statistical evaluation at a significance level of 0.05. Results: Based on statistical testing using the nonparametric multiselective Kruskall-Wallis test and subsequent post-hoc analysis using the Dunn method, the Kors regression as a whole method achieved the most accurate transformation. Conclusion: The results of statistical analysis provide an evaluation of the accuracy of several transformation methods for deriving orthogonal leads, for possible application in measuring and evaluation systems, which may contribute to the correct choice of method for subsequent analysis of electrical activity of the heart at orthogonal leads to predict various diseases.

Vectorcardiography-derived index allows a robust quantification of ventricular electrical synchrony.

Alteration of muscle activation sequence is a key mechanism in heart failure with reduced ejection fraction. Successful cardiac resynchronization therapy (CRT), which has become standard therapy in these patients, is limited by the lack of precise dyssynchrony quantification. We implemented a computational pipeline that allows assessment of ventricular dyssynchrony by vectorcardiogram reconstruction from the patient's electrocardiogram. We defined a ventricular dyssynchrony index as the distance between the voltage and speed time integrals of an individual observation and the linear fit of these variables obtained from a healthy population. The pipeline was tested in a 1914-patient population. The dyssynchrony index showed minimum values in heathy controls and maximum values in patients with left bundle branch block (LBBB) or with a pacemaker (PM). We established a critical dyssynchrony index value that discriminates electrical dyssynchronous patterns (LBBB and PM) from ventricular synchrony. In 10 patients with PM or CRT devices, dyssynchrony indexes above the critical value were associated with high time to peak strain standard deviation, an echocardiographic measure of mechanical dyssynchrony. Our index proves to be a promising tool to evaluate ventricular activation dyssynchrony, potentially enhancing the selection of candidates for CRT, device configuration during implantation, and post-implant optimization.

Using QRS loop descriptors to characterize the risk of sudden cardiac death in patients with structurally normal hearts.

The predictive value of non-invasive electrocardiographic examination findings for the risk of sudden cardiac death (SCD) in populations with structurally normal hearts remains unclear. This study aimed to investigate the characteristics of the QRS vectorcardiography of surface electrocardiography in patients with structurally normal hearts who experienced SCD. We consecutively enrolled patients who underwent vectorcardiography between March 2017 and December 2018 in a tertiary referral medical center. These patients didn't have structural heart diseases, histories of congestive heart failure, or reduced ejection fraction, and they were classified into SCD (with aborted SCD history and cerebral performance category score of 1) and control groups (with an intervention for atrioventricular node reentrant tachycardia and without SCD history). A total of 162 patients (mean age, 54.3±18.1 years; men, 75.9%), including 59 in the SCD group and 103 in the control group, underwent propensity analysis. The baseline demographic variables, underlying diseases, QRS loop descriptors (the percentage of the loop area, loop dispersion, and inter-lead QRS dispersion), and other electrocardiographic parameters were compared between the two groups. In the univariate and multivariate analyses, a smaller percentage of the loop area (odds ratio, 0.0003; 95% confidence interval, 0.00-0.02; p<0.001), more significant V4-5 dispersion (odds ratio, 1.04; 95% confidence interval, 1.02-1.07; p = 0.002), and longer QRS duration (odds ratio, 1.05; 95% confidence interval, 1.00-1.10; p = 0.04) were associated with SCD. In conclusion, the QRS loop descriptors of surface electrocardiography could be used as non-invasive markers to identify patients experiencing aborted SCD from a healthy population. A decreased percentage of loop area and elevated V4-5 QRS dispersion values assessed using vectorcardiography were associated with an increased risk of SCD in patients with structurally normal hearts.

QRS area as a predictor of cardiac resynchronization therapy response: A systematic review and meta-analysis.

BACKGROUND: QRS area, a three-dimensional QRS complex, is a novel vectorcardiography method of measuring the magnitude of electrical forces in the heart. Hypothetically, a greater QRS area denotes higher dyssynchrony and indicates potential benefits from cardiac resynchronization therapy (CRT). Previous studies suggest a positive correlation between QRS area and the degree of response to CRT, but its clinical use remains unclear. We performed a meta-analysis of the relationship between QRS area and survival benefit following CRT. METHODS: We comprehensively searched the MEDLINE, EMBASE, and Cochrane databases from inception to August 2021. We included studies with prospective and retrospective cohort designs that reported QRS area before CRT and total mortality. Data from each study were analyzed using a random-effects model. The results were reported as a hazard ratio (HR) and 95% confidence intervals. RESULTS: Five observational studies including 4931 patients were identified. The cut-off values between large and small QRS areas ranged from 102 to 116 µVs. Our analysis showed a larger QRS area was statistically associated with increased 5-year survival in patients implanted with CRT (HR pooled 0.48, 95% CI 0.46-0.51, I2  = 54%, p < .0001). Greater QRS area reduction (pre- and post-implantation) were associated with a lower total mortality rate (HR pooled 0.45, 95% CI 0.38-0.52, I2  = 0%, p < .0001). CONCLUSION: Larger pre-implantation QRS area was associated with increased survival after CRT. QRS area reduction following CRT implantation was also associated with lower mortality. QRS area may potentially become an additional selection criterion for CRT implantations.

Is derived vectorcardiography a potential screening tool for pulmonary hypertension?

BACKGROUND: Patients with atrial septal defects and pulmonary hypertension would benefit from early identification and treatment of pulmonary hypertension prior to closure. Noninvasive screening tools for pulmonary hypertension are inadequate. Electrocardiography, though readily available, has so far been of limited screening utility in patients with pulmonary hypertension. We hypothesize that derived vectorcardiographic parameters will aid in identifying increased right ventricular afterload and thus provide an additional screening tool for pulmonary hypertension in patients with secundum atrial septal defects. OBJECTIVE: Establish whether vectorcardiography can be used to screen for pulmonary hypertension. METHODS: A retrospective review of patients with secundum atrial septal defects (ASD) who underwent cardiac catheterization at the University of Minnesota from 2012 to 2020 was performed. We excluded patients with other congenital heart diagnoses, insufficient hemodynamic data, or lacking sinus rhythm electrocardiogram at time of cardiac catheterization. Parameters analyzed included: Sokolow-Lion right ventricular hypertrophy criteria, PR duration, QRS duration, corrected QT intervals, QRS and T wave frontal plane axes, rSR', R' amplitude, as well as vectorcardiographic parameters (Kors regression-related method), the QRS vector magnitude, T wave vector magnitude, and the spatial QRS-T angle. These were compared to measures of pulmonary hypertension obtained at cardiac catheterization. RESULTS: The spatial QRS-T angle significantly differentiated ASD patients with pulmonary hypertension (median 104 degrees, interquartile range 55-137 degrees) from ASD patients without pulmonary hypertension (median 37 degrees, interquartile range 21-63 degrees, p-value of 0.002). At a cut-off of 124 degrees, the positive and negative predictive values for identification of pulmonary hypertension were 36.4% and 96.4%, respectively, with an odds ratio of 13.4 (95% confidence interval of 2.9 to 63.7). The positive predictive value was significantly improved when combined with echocardiographic data to screen for pulmonary hypertension. CONCLUSION: The spatial QRS-T angle is associated with pulmonary hypertension in patients with secundum atrial septal defects.

Spatial Feature Extraction of Vectorcardiography via Minimum Volume Ellipsoid Enclosure in Classifying Left Ventricular Hypertrophy.

The voltage criteria used to diagnose left ventricular hypertrophy (LVH) in the chest and limb leads are by no means absolute. In addition to QRS voltages, QRS axis and duration, and P wave characteristics, repolarization (STT) changes have been focused attention due to their representing left ventricular overload. Vectorcardiography (VCG) has been studied specifically on its repolarization abnormality. The present study aims to devise spatial feature extraction of VCG and assess it in the LVH classification task. A minimum volume ellipsoid enclosure was applied to six segments obtained from upstroke and downstroke of each P, QRS, and T loops of a single-beat VCG. For the evaluation, VCG and 12 lead ECG dataset along with LVH labels of 61 subjects were derived from public open data, PTB-XL. These classification performances were compared with the LVH diagnosis criteria in the standard 12 lead ECG. As a result, the Random Forest classifier trained by the proposed spatial VCG feature resulted in accuracy of 0.904 (95% confidence interval: 0.861-0.947) when the classbalanced dataset was evaluated, which slightly exceeded the feature of 12 lead ECG. The feature importance analysis provided the quantitative ranking of the spatial feature of VCG, which were practically similar to those of ECG in the LVH classification task. Since the VCG are spatially comparable with three-dimensional data of CT, MRI, or Echocardiography, VCG will shed light on the spatial behavior of electrical depolarization and repolarization abnormalities in cardiac diseases.

Adaptation of ventricular repolarization dispersion during heart rate increase in humans: A roller coaster process.

BACKGROUND: Regional differences in ventricular activation sequence and action potential duration and morphology result in dispersion in ventricular repolarization (VR). VR dispersion is a key factor in arrhythmogenesis. We studied the adaptation of global VR dispersion in humans during normal and abnormal ventricular activation, and the relation to the QT adaptation (hysteresis). METHODS: We measured global VR dispersion as T amplitude, T area, and ventricular gradient (VG), using continuous Frank vectorcardiography, in response to abrupt and sustained atrial (AP) or ventricular pacing (VP) aiming at 120 bpm, in 21 subjects with permanent pacemakers. RESULTS: Following pacing start, VR adaptation showed an initially rapid and complex tri-phasic pattern, most pronounced for T amplitude. There were major differences in the patterns of VR dispersion adaptation following abrupt AP vs VP, confirming that the adaptation pattern is activation dependent. In response to AP, an instantaneous decrease in VR dispersion occurred, followed by an increase and then a slow decrease, all at a lower level than baseline. In contrast, following VP there was an immediate increase to ~4× baseline in T amplitude and T area (but not in VG), with a subsequent biphasic adaptation lasting longer during VP than AP. The initial rapid changes occurred within the time for QT adaptation to reach steady-state. CONCLUSIONS: Our results corroborate and expand data from animal and invasive human studies, showing similarities of the adaptation pattern on different scales. The initial rapidly changing VR adaptation phase presumably reflects a window of increased vulnerability to arrhythmias.

Vectorcardiography as a prognostic tool in hypertrophic cardiomyopathy.

BACKGROUND: Vectorcardiography (VCG) has demonstrated diagnostic value in the assessment of hypertrophic cardiomyopathy (HCM), however, determining its prognostic value over time has not yet been investigated. This study sought to assess the correlation of VCG parameters with the progression of HCM. METHODS: A retrospective chart review of 119 pediatric patients with diagnosis of HCM at the University of Minnesota. Eighty-three cases were excluded because of age, presence of congenital heart disease, not meeting criteria for HCM or negative phenotype. Sample was divided into 2 groups based on the presence or not of cardiac events (ventricular tachycardia, cardiac arrest, ventricular assist device, heart transplant). Derived vectorcardiography from standard 12­lead ECG was obtained for the first ECG and last available or prior to sentinel event. RESULTS: Of the 36 cases that met inclusion criteria, 9 (25%) developed a sentinel event. The median age for the event group was 10.1 ± 7.5 years and for the non-event group was 8.7 ± 6.35 years. There was no significant difference in age or sex between the groups. The T wave vector magnitude value was significantly smaller in the event group than in the non-event group (0.302 ± 0.146 mV Vs. 0.561 ± 0.305 mV, p 0.002), with a hazard ratio of 0.651 (95% CI 0.463 to 0.915). No other parameter showed significant difference between the two groups. CONCLUSIONS: The T wave vector magnitude may predict sentinel events in HCM. Prospective studies are necessary to evaluate the utility of the evolution of VCG parameters.

Short duration Vectorcardiogram based inferior myocardial infarction detection: class and subject-oriented approach.

Myocardial infarction (MI) happens when blood stops circulating to an explicit segment of the heart causing harm to the heart muscles. Vectorcardiography (VCG) is a technique of recording direction and magnitude of the signals that are produced by the heart in a 3-lead representation. In this work, we present a technique for detection of MI in the inferior portion of heart using short duration VCG signals. The raw signal was pre-processed using the median and Savitzky-Golay (SG) filter. The Stationary Wavelet Transform (SWT) was used for time-invariant decomposition of the signal followed by feature extraction. The selected features using minimum-redundancy-maximum-relevance (mRMR) based feature selection method were applied to the supervised classification methods. The efficacy of the proposed method was assessed under both class-oriented and a more real-life subject-oriented approach. An accuracy of 99.14 and 89.37% were achieved respectively. Results of the proposed technique are better than existing state-of-art methods and used VCG segment is shorter. Thus, a shorter segment and a high accuracy can be helpful in the automation of timely and reliable detection of MI. The satisfactory performance achieved in the subject-oriented approach shows reliability and applicability of the proposed technique.

Strain Tensor Imaging: Cardiac-induced brain tissue deformation in humans quantified with high-field MRI.

The cardiac cycle induces blood volume pulsations in the cerebral microvasculature that cause subtle deformation of the surrounding tissue. These tissue deformations are highly relevant as a potential source of information on the brain's microvasculature as well as of tissue condition. Besides, cyclic brain tissue deformations may be a driving force in clearance of brain waste products. We have developed a high-field magnetic resonance imaging (MRI) technique to capture these tissue deformations with full brain coverage and sufficient signal-to-noise to derive the cardiac-induced strain tensor on a voxel by voxel basis, that could not be assessed non-invasively before. We acquired the strain tensor with 3 mm isotropic resolution in 9 subjects with repeated measurements for 8 subjects. The strain tensor yielded both positive and negative eigenvalues (principle strains), reflecting the Poison effect in tissue. The principle strain associated with expansion followed the known funnel shaped brain motion pattern pointing towards the foramen magnum. Furthermore, we evaluate two scalar quantities from the strain tensor: the volumetric strain and octahedral shear strain. These quantities showed consistent patterns between subjects, and yielded repeatable results: the peak systolic volumetric strain (relative to end-diastolic strain) was 4.19⋅10-4 ± 0.78⋅10-4 and 3.98⋅10-4 ± 0.44⋅10-4 (mean ± standard deviation for first and second measurement, respectively), and the peak octahedral shear strain was 2.16⋅10-3 ± 0.31⋅10-3 and 2.31⋅10-3 ± 0.38⋅10-3, for the first and second measurement, respectively. The volumetric strain was typically highest in the cortex and lowest in the periventricular white matter, while anisotropy was highest in the subcortical white matter and basal ganglia. This technique thus reveals new, regional information on the brain's cardiac-induced deformation characteristics, and has the potential to advance our understanding of the role of microvascular pulsations in health and disease.

Heart Size Corrected Electrical Dyssynchrony and Its Impact on Sex-Specific Response to Cardiac Resynchronization Therapy.

BACKGROUND: Women are less likely to receive cardiac resynchronization therapy, yet, they are more responsive to the therapy and respond at shorter QRS duration. The present study hypothesized that a relatively larger left ventricular (LV) electrical dyssynchrony in smaller hearts contributes to the better cardiac resynchronization therapy response in women. For this, the vectorcardiography-derived QRS area is used, since it allows for a more detailed quantification of electrical dyssynchrony compared with conventional electrocardiographic markers. METHODS: Data from a multicenter registry of 725 cardiac resynchronization therapy patients (median follow-up, 4.2 years [interquartile range, 2.7-6.1]) were analyzed. Baseline electrical dyssynchrony was evaluated using the QRS area and the corrected QRS area for heart size using the LV end-diastolic volume (QRSarea/LVEDV). Impact of the QRSarea/LVEDV ratio on the association between sex and LV reverse remodeling (LV end-systolic volume change) and sex and the composite outcome of all-cause mortality, LV assist device implantation, or heart transplantation was assessed. RESULTS: At baseline, women (n=228) displayed larger electrical dyssynchrony than men (QRS area, 132±55 versus 123±58 µVs; P=0.043), which was even more pronounced for the QRSarea/LVEDV ratio (0.76±0.46 versus 0.57±0.34 µVs/mL; P<0.001). After multivariable analyses, female sex was associated with LV end-systolic volume change (ß=0.12; P=0.003) and a lower occurrence of the composite outcome (hazard ratio, 0.59 [0.42-0.85]; P=0.004). A part of the female advantage regarding reverse remodeling was attributed to the larger QRSarea/LVEDV ratio in women (25-fold change in ß from 0.12 to 0.09). The larger QRSarea/LVEDV ratio did not contribute to the better survival observed in women. In both volumetric responders and nonresponders, female sex remained strongly associated with a lower risk of the composite outcome (adjusted hazard ratio, 0.59 [0.36-0.97]; P=0.036; and 0.55 [0.33-0.90]; P=0.018, respectively). CONCLUSIONS: Greater electrical dyssynchrony in smaller hearts contributes, in part, to more reverse remodeling observed in women after cardiac resynchronization therapy, but this does not explain their better long-term outcomes.