Methods for presenting and visualising electrocardiographic data: From temporal signals to spatial imaging

Body Surface Potential Mapping during Ventricular Depolarization in Athletes with Prolonged PQ Interval after Exercise

BACKGROUND

Prolongation of the PQ interval, generally associated with an atrioventricular conduction delay, may be related to changes in intraventricular impulse spreading.

OBJECTIVE

To assess, using body surface potential mapping (BSPM), the process of ventricular depolarization in athletes with prolonged PQ intervals at rest and after exercise.

METHODS

The study included 7 cross-country skiers with a PQ interval of more than 200 ms (Prolonged-PQ group) and 7 with a PQ interval of less than 200 ms (Normal-PQ group). The BSPM from 64 unipolar torso leads was performed before (Pre-Ex) and after the bicycle exercise test (Post-Ex). Body surface equipotential maps were analyzed during ventricular depolarization. The significance level was 5%.

RESULTS

Compared to Normal-PQ athletes, the first and second periods of the stable position of cardiac potentials on the torso surface were longer, and the formation of the "saddle" potential distribution occurred later, at Pre-Ex, in Prolonged-PQ athletes. At Post-Ex, the Prolonged-PQ group showed a shortening of the first and second periods of stable potential distributions and a decrease in appearance time of the "saddle" phenomenon relative to Pre-Ex (to the values near to those of the Normal-PQ group). Additionally, at Post-Ex, the first inversion of potential distributions and the total duration of ventricular depolarization in Prolonged-PQ athletes decreased compared to Pre-Ex and with similar values in Normal-PQ athletes. Compared to Normal-PQ athletes, the second inversion was longer at Pre-Ex and Post-Ex in Prolonged-PQ athletes.

CONCLUSION

Prolonged-PQ athletes had significant differences in the temporal characteristics of BSPM during ventricular depolarization both at rest and after exercise as compared to Normal-PQ athletes.

Designing an ECG curriculum for residents: Evidence-based approaches to improving resident ECG interpretation skills

Residents enter their training with variable comfort and competency in electrocardiogram (ECG) interpretation. Accurately interpreting an ECG is a fundamental skill in medicine and resident physicians would benefit from a longitudinal, dedicated ECG curriculum as part of their training to enhance interpretation skills and improve patient outcomes. Educators currently employ a wide array of methodologies to teach their trainees proper ECG interpretation skills, with no single modality established as the gold-standard for teaching this crucial skill. We present evidence-based guidance on how educators may develop and implement an effective ECG interpretation curriculum as part of residency training.

3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads

Objective.The objective of this study is to explore new imaging techniques with the use of the deep learning method for the identification of cardiac abnormalities present in electrocardiogram (ECG) signals with 2, 3, 4, 6 and 12-lead in the framework of the PhysioNet/Computing in Cardiology Challenge 2021. The training set is a public database of 88,253 twelve-lead ECG recordings lasting from 6 s to 60 s. Each ECG recording has one or more diagnostic labels. The six-lead, four-lead, three-lead, and two-lead are reduced-lead versions of the original twelve-lead data.Approach.The deep learning method considers images that are built from raw ECG signals. This technique considers innovative 3D display of the entire ECG signal, observing the regional constraints of the leads, obtaining time-spatial images of the 12 leads, where the x-axis is the temporal evolution of ECG signal, the y-axis is the spatial location of the leads, and the z-axis (color) the amplitude. These images are used for training Convolutional Neural Networks with GoogleNet for ECG diagnostic classification.Main results.The official results of the classification accuracy of our team named 'Gio_new_img' received scores of 0.4, 0.4, 0.39, 0.4 and 0.4 (ranked 18th, 18th, 18th,18th, 18th out of 39 teams) for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead versions of the hidden test set with the Challenge evaluation metric.Significance.The results indicated that all these algorithms have similar behaviour in the various lead groups, and the most surprising and interesting point is the fact that the 2-lead scores are similar to those obtained with the analysis of 12 leads. It permitted to test the diagnostic potential of the reduced-lead ECG recordings. These aspects can be related to the pattern recognition capacity and generalizability of the deep learning approach and/or to the fact that the characteristics of the considered cardiac abnormalities can be extracted also from a reduced set of leads.

Body Surface Potential Mapping During Heart Ventricular Repolarization in Male Swimmers and Untrained Persons Under Hypoxic and Hypercapnic Hypoxia

Ivonina, Natalya I., Andrey A. Fokin, and Irina M. Roshchevskaya. Body surface potential mapping during heart ventricular repolarization in male swimmers and untrained persons under hypoxic and hypercapnic hypoxia. High Alt Med Biol. 00:000-000, 2021. Background: In swimmers, as a result of prolonged breath-holding during swimming, first hypoxic hypoxia (HH) and then hypercapnic hypoxia (HCH) occurs, which may influence the electrical activity of the heart (EAH). What type of normobaric hypoxia more strongly affects the EAH-normocapnic HH or HCH? Methods: The electrical activity of swimmers' hearts (n = 7) and untrained persons (n = 10) was studied by using electrocardiography (ECG) and body surface potential mapping (BSPM) during the period of ventricular repolarization at baseline, at normocapnic HH, at HCH, and in the recovery period. Results: HH led to more significant changes in the EAH in all participants in comparison with HCH. There was no change in the amplitude of T wave_ECG at hypoxic and HCH, but a change in the amplitude of the minimum was noted in BSPM. The minimum in athletes changed by the end of the exposure (from -0.40 ± 0.12 mV to -0.26 ± 0.11 mV, p = 0.001); in the control, it decreased earlier (after 8 minutes of exposure to HH, the amplitude of the minimum was -0.24 ± 0.08 mV, p = 0.026). With HH, the duration of the QT interval in athletes was shortened due to the shortening of the J-Tpeak (from 250 to 188 ms, p = 0.001) and the Tpeak-Tend (from 98 to 86 ms) intervals. In controls, the decrease in the QT interval was due to the J-Tpeak shortening only (from 280 to 200 ms, p = 0.026). Conclusions: In the study of the effect of hypoxia on the EAH during ventricular repolarization, the use of the BSPM has proven to be more informative than the use of traditional ECG. When using potential mapping, more significant changes in ventricular repolarization at HH than at HCH were revealed, whereas the parameters changed less in swimmers compared with the baseline than in controls during both exposures.

Systematic Review of Clinical Decision Support Systems for Prehospital Acute Coronary Syndrome Identification

OBJECTIVES

Timely prehospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the prehospital environment. The review aim was to describe the accuracy of CDSS and individual components in the prehospital ACS management.

METHODS

This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the prehospital setting, the influence of computer-aided decision-making and of 4 components: electrocardiogram, biomarkers, patient history, and examination findings. The impact of these components on sensitivity, specificity, and positive and negative predictive values was assessed.

RESULTS

A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. CDSS which incorporated all 4 components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values.

CONCLUSIONS

Although heterogeneity precluded meta-analysis, this review emphasizes the potential of ACS CDSS in prehospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.

Eventogram: A Visual Representation of Main Events in Biomedical Signals

Biomedical signals carry valuable physiological information and many researchers have difficulty interpreting and analyzing long-term, one-dimensional, quasi-periodic biomedical signals. Traditionally, biomedical signals are analyzed and visualized using periodogram, spectrogram, and wavelet methods. However, these methods do not offer an informative visualization of main events within the processed signal. This paper attempts to provide an event-related framework to overcome the drawbacks of the traditional visualization methods and describe the main events within the biomedical signal in terms of duration and morphology. Electrocardiogram and photoplethysmogram signals are used in the analysis to demonstrate the differences between the traditional visualization methods, and their performance is compared against the proposed method, referred to as the “eventogram” in this paper. The proposed method is based on two event-related moving averages that visualizes the main time-domain events in the processed biomedical signals. The traditional visualization methods were unable to find dominant events in processed signals while the eventogram was able to visualize dominant events in signals in terms of duration and morphology. Moreover, eventogram-based detection algorithms succeeded with detecting main events in different biomedical signals with a sensitivity and positive predictivity >95%. The output of the eventogram captured unique patterns and signatures of physiological events, which could be used to visualize and identify abnormal waveforms in any quasi-periodic signal.

Coronary vasospasm is an unlikely cause of Takotsubo syndrome, although we should keep an open mind

This viewpoint pertains to the still elusive pathophysiology of the Takotsubo syndrome (TTS), maintaining the position that this affliction is not the result of coronary vasospasm (CV) involving one or more coronary arteries. Although CV has been rarely encountered in the acute stage of TTS, or elicited via provocative testing in the subacute stage of the disease, it does not appear to be the cause of TTS as shown by the bulk of the published relevant literature. The author provides some speculations to explain the spontaneous appearance of CV, or its artificial elicitation, in some patients with TTS. However while we are striving to unravel the pathophysiology of TTS, we should keep an open mind about a possible role for CV in the causation of TTS.

Transient attenuation of the amplitude of the QRS complexes in the diagnosis of Takotsubo syndrome

BACKGROUND AND OBJECTIVES

Currently, there are no specific diagnostic electrocardiogram (ECG) signs for Takotsubo syndrome (TTS) to differentiate it from acute coronary syndromes (ACS). Myocardial oedema has been detected by cardiac magnetic resonance imaging in patients with TTS. Recently it has been postulated that myocardial oedema may be the cause of low QRS voltage (LQRSV) in the admission ECG and attenuation of the amplitude of the QRS complexes (AAQRS) in serial ECGs, noted in a few published cases of patients with TTS. The objective of this study was to evaluate whether the admission ECG of patients with documented TTS reveals LQRSV and whether AAQRS is found when serial ECGs are compared in such patients.

METHODS

This study evaluated the prevalence of LQRSV in the admission ECG and AAQRS in serial ECGs in patients with TTS. ECGs of 368 patients with TTS from published reports in the international literature were evaluated for LQRSV (≤5 mm in limb leads and/or ≤10 mm in precordial leads) and AAQRS in serial ECGs.

RESULTS

LQRSV was seen in 91.5% of 200 patients with TTS and one ECG, with a distribution of 49.0, 42.8, 51.0, 52.0, and 46.9%, in lead aVR, and inferior, anterior, lateral, and high lateral ECG lead groups, respectively. AAQRS was seen in 93.5% of 168 patients with TTS and two or more ECGs, with a distribution of 78.3, 74.5, 60.1, 70.7, and 74.5% in lead aVR, and inferior, anterior, lateral, and high lateral ECG lead groups, respectively.

CONCLUSIONS

LQRSV and AAQRS are highly prevalent ECG signs in patients with TTS, and should be useful in aiding in its diagnosis and differentiation from ACS, on first contact with the patient on admission to the hospital, and the ensuing 24 hours, in conjunction with echocardiography and coronary arteriography.