Vectorcardiography identifies patients with electrocardiographically concealed long QT syndrome

Vectorgastrogram: dynamic trajectory and recurrence quantification analysis to assess slow wave vector movement in healthy subjects

Functional gastric disorders entail chronic or recurrent symptoms, high prevalence and a significant financial burden. These disorders do not always involve structural abnormalities and since they cannot be diagnosed by routine procedures, electrogastrography (EGG) has been proposed as a diagnostic alternative. However, the method still has not been transferred to clinical practice due to the difficulty of identifying gastric activity because of the low-frequency interference caused by skin-electrode contact potential in obtaining spatiotemporal information by simple procedures. This work attempted to robustly identify the gastric slow wave (SW) main components by applying multivariate variational mode decomposition (MVMD) to the multichannel EGG. Another aim was to obtain the 2D SW vectorgastrogram VGGSW from 4 electrodes perpendicularly arranged in a T-shape and analyse its dynamic trajectory and recurrence quantification (RQA) to assess slow wave vector movement in healthy subjects. The results revealed that MVMD can reliably identify the gastric SW, with detection rates over 91% in fasting postprandial subjects and a frequency instability of less than 5.3%, statistically increasing its amplitude and frequency after ingestion. The VGGSW dynamic trajectory showed a statistically higher predominance of vertical displacement after ingestion. RQA metrics (recurrence ratio, average length, entropy, and trapping time) showed a postprandial statistical increase, suggesting that gastric SW became more intense and coordinated with a less complex VGGSW and higher periodicity. The results support the VGGSW as a simple technique that can provide relevant information on the "global" spatial pattern of gastric slow wave propagation that could help diagnose gastric pathologies.

Decreased vector magnitudes may help identify events in patients with Long QT syndrome

INTRODUCTION

All Long QT syndrome (LQTS) patients are at elevated risk for channelopathy-induced delayed myocardial repolarization and consequently potentially life-threatening cardiac events with 90% of initial cardiac events occurring between preteen and 40 years old. Utilizing ECG and derived vectorcardiographic parameters, including T wave Vector Magnitude (TwVM) measurement data, this study attempts to determine whether TwVM from baseline ECGs is effectively predictive of future cardiac events for genotype-positive LQTS patients.

METHODS

Verified carriers of established LQTS disease-causing genotypes were selected from University of Minnesota patient encounters between 2010 and 2020 for inclusion in this retrospective study. Baseline and predictive ECG and derived vectorcardiographic parameter evaluation, clinical data, and statistical analysis were compared between patients with and patients without cardiac events. First recorded ECG was at presentation to our hospital and final ECG is defined as ECG just prior to cardiac event (event defined below in Methods) or the most final documented ECG before cut-off year of 2020 for the event-free group.

RESULTS

Of 41 participants, 15 experienced cardiac events and 26 did not. While many baseline electrocardiographic parameter measurements did not show significant differences between patient groups, vectorcardiographic parameters at baseline, specifically the QRS vector magnitude (QRSVM) and azimuth of the spatial ventricular gradient, showed significance. Additionally, final vectorcardiographic parameters, particularly the QRSVM, TwVM, and azimuth of the spatial ventricular gradient showed significant differences between patient groups. Final T-wave frontal axis was significantly larger in those without cardiac events. Significant Kaplan-Meier curve separation between patient groups was noted based on a QRSVM of 1.43 mV or lower, with additional consideration to patient age, genotype, and beta blocker use.

CONCLUSION

This study shows evidence of ECG and derived vectorcardiographic parameters, including TwVM, being effective in early prediction of cardiac events in genotype-positive LQTS patients.

Review of Processing Pathological Vectorcardiographic Records for the Detection of Heart Disease

Vectorcardiography (VCG) is another useful method that provides us with useful spatial information about the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common nowadays, mainly due to the well-established 12-lead ECG system. However, VCG leads can be derived from standard 12-lead ECG systems using mathematical transformations. These derived or directly measured VCG records have proven to be a useful tool for diagnosing various heart diseases such as myocardial infarction, ventricular hypertrophy, myocardial scars, long QT syndrome, etc., where standard ECG does not achieve reliable accuracy within automated detection. With the development of computer technology in recent years, vectorcardiography is beginning to come to the forefront again. In this review we highlight the analysis of VCG records within the extraction of functional parameters for the detection of heart disease. We focus on methods of processing VCG functionalities and their use in given pathologies. Improving or combining current or developing new advanced signal processing methods can contribute to better and earlier detection of heart disease. We also focus on the most commonly used methods to derive a VCG from 12-lead ECG.

Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part I: Cardiac Signals

Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today's clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.

Monitoring and Synchronization of Cardiac and Respiratory Traces in Magnetic Resonance Imaging: A Review

Synchronization of human vital signs, namely the cardiac cycle and respiratory excursions, is necessary during magnetic resonance imaging of the cardiovascular system and the abdominal cavity to achieve optimal image quality with minimized artifacts. This review summarizes techniques currently available in clinical practice, as well as methods under development, outlines the benefits and disadvantages of each approach, and offers some unique solutions for consideration.

Biomarkers of pre-existing risk of Torsade de Pointes under Sotalol treatment

INTRODUCTION

Antiarrhythmic drugs therapies are currently going through a turning point. The high risk that exists during the treatments has led to an ongoing search for new non-invasive toxicity risk biomarkers.

METHODS

We propose the use of spatial biomarkers obtained through the quaternion algebra, evaluating the dynamics of the cardiac electrical vector in a non-invasive way in order to detect abnormal changes in ventricular heterogeneity. In groups of patients with and without history of Torsade de Pointes undergoing a Sotalol challenge, we compute the radius and the linear and angular velocities of QRS complex and T-wave loops. From these signals we extract significant features in order to compute a risk patient classifier.

RESULTS

Using machine learning techniques and statistical analysis, the combinations of few indices reach a pair of sensitivity/specificity of 100%/100% when separating patients with arrhythmogenic substrate. Several biomarkers not only measure drug-induced changes significantly but also observe differences in at-risk patients outperforming current standards.

DISCUSSION

Alternative biomarkers were able to describe pre-existing risk of patients. Given the high levels of significance and performance, these results could contribute to a better understanding of the torsadogenic substrate and to the safe development of drug therapies.

Quantitative T-wave morphology assessment from surface ECG is linked with cardiac events risk in genotype-positive KCNH2 mutation carriers with normal QTc values

INTRODUCTION

Long QT syndrome (LQTS) mutation carriers have elevated the risk of cardiac events even in the absence of QTc prolongation; however, mutation penetrance in patients with normal QTc may be reflected in abnormal T-wave shape, particularly in KCNH2 mutation carriers. We aimed to assess whether the magnitude of a three-dimensional T-wave vector (TwVM) will identify KCNH2-mutation carriers with normal QTc at risk for cardiac events.

METHODS

Adult LQT2 patients with QTc < 460 ms in men and <470 ms in women (n = 113, age 42 ± 16 years, 43% male) were compared with genotype-negative family members (n = 1007). The TwVM was calculated using T-wave amplitudes in leads V6, II, and V2 as the square root of (TV6²  + TII²  + (0.5*TV2)² ). Cox regression analysis adjusted for gender and time-dependent beta-blocker use was performed to assess cardiac event (CE) risk, defined as syncope, aborted cardiac arrest, implantable cardioverter-defibrillator therapy, or sudden death.

RESULTS

Dichotomized by median of 0.30 mV, lower TwVM was associated with elevated CE risk compared to those with high TwVM (HR = 2.95, 95% CI, 1.25-6.98, P = .014) and also remained significant after including sex and time-dependent beta-blocker usage in the Cox regression analysis (HR = 2.64, 95% CI, 1.64-4.24, P < .001). However, these associations were found only in women but not in men who had low event rates.

CONCLUSION

T-wave morphology quantified as repolarization vector magnitude using T-wave amplitudes retrieved from standard 12-lead electrocardiogram predicts cardiac events risk in LQT2 women and appears useful for risk stratification of KCNH2-mutation carriers without QTc prolongation.

Risk Stratification of Type 2 Long-QT Syndrome Mutation Carriers With Normal QTc Interval: The Value of Sex, T-Wave Morphology, and Mutation Type

BACKGROUND

Long-QT (LQT) syndrome mutation carriers have higher risk of cardiac events than unaffected family members even in the absence of QTc prolongation. Changes in T-wave morphology may reflect penetrance of LQT syndrome mutations. We aimed to assess whether T-wave morphology may improve risk stratification of LQT2 mutation carriers with normal QTc interval.

METHODS

LQT2 mutation carriers with QTc <460 ms in men and <470 ms in women (n=154) were compared with unaffected family members (n=1007). Baseline ECGs recorded at age ≥18 years underwent blinded assessment. Flat, notched, or negative T waves in leads II or V₅ were considered abnormal. Cox regression analysis was performed to assess the association between T-wave morphology, the presence of mutations in the pore region of KCNH2, and the risk of cardiac events defined as syncope, aborted cardiac arrest, defibrillator therapy, or sudden cardiac death. Sex-specific associations were estimated using interactions terms.

RESULTS

LQT2 female carriers with abnormal T-wave morphology had significantly higher risk of cardiac events compared with LQT2 female carriers with normal T waves (hazard ratio, 3.31; 95% confidence interval, 1.68-6.52; P=0.001), whereas this association was not significant in men. LQT2 men with pore location of mutations have significantly higher risk of cardiac events than those with nonpore mutations (hazard ratio, 6.01; 95% confidence interval, 1.50-24.08; P=0.011), whereas no such association was found in women.

CONCLUSIONS

The risk of cardiac events in LQT2 carriers with normal QTc is associated with abnormal T-wave morphology in women and pore location of mutation in men. The findings further indicate sex-specific differences in phenotype and genotype relationship in LQT2 patients.

Comparison of Different Electrocardiography with Vectorcardiography Transformations

This paper deals with transformations from electrocardiographic (ECG) to vectorcardiographic (VCG) leads. VCG provides better sensitivity, for example for the detection of myocardial infarction, ischemia, and hypertrophy. However, in clinical practice, measurement of VCG is not usually used because it requires additional electrodes placed on the patient's body. Instead, mathematical transformations are used for deriving VCG from 12-leads ECG. In this work, Kors quasi-orthogonal transformation, inverse Dower transformation, Kors regression transformation, and linear regression-based transformations for deriving P wave (PLSV) and QRS complex (QLSV) are implemented and compared. These transformation methods were not yet compared before, so we have selected them for this paper. Transformation methods were compared for the data from the Physikalisch-Technische Bundesanstalt (PTB) database and their accuracy was evaluated using a mean squared error (MSE) and a correlation coefficient (R) between the derived and directly measured Frank's leads. Based on the statistical analysis, Kors regression transformation was significantly more accurate for the derivation of the X and Y leads than the others. For the Z lead, there were no statistically significant differences in the medians between Kors regression transformation and the PLSV and QLSV methods. This paper thoroughly compared multiple VCG transformation methods to conventional VCG Frank's orthogonal lead system, used in clinical practice.

The congenital long QT syndrome Type 3: An update

Congenital long QT syndrome type 3 (LQT3) is the third in frequency compared to the 15 forms known currently of congenital long QT syndrome (LQTS). Cardiac events are less frequent in LQT3 when compared with LQT1 and LQT2, but more likely to be lethal; the likelihood of dying during a cardiac event is 20% in families with an LQT3 mutation and 4% with either an LQT1 or an LQT2 mutation. LQT3 is consequence of mutation of gene SCN5A which codes for the Nav1.5 Na+ channel α-subunit and electrocardiographically characterized by a tendency to bradycardia related to age, prolonged QT/QTc interval (mean QTc value 478 ± 52 ms), accentuated QT dispersion consequence of prolonged ST segment, late onset of T wave and frequent prominent U wave because of longer repolarization of the M cell across left ventricular wall.