Beyond the 12 lead: review of the use of additional leads for the early electrocardiographic diagnosis of acute myocardial infarction

Evaluating Morphological Features of Electrocardiogram Signals for Diagnosing of Myocardial Infarction Using Classification-Based Feature Selection

Background:

Cardiovascular disease (CVD) is the first cause of world death, and myocardial infarction (MI) is one of the five primary disorders of CVDs which the patient electrocardiogram (ECG) analysis plays a dominant role in MI diagnosis. This research aims to evaluate some extracted features of ECG data to diagnose MI.

Methods:

In this paper, we used the Physikalisch-Technische Bundesanstalt database and extracted some morphological features, such as total integral of ECG, integral of the T-wave section, integral of the QRS complex, and J-point elevation from a cycle of normal and abnormal ECG waveforms. Since the morphology of healthy and abnormal ECG signals is different, we applied integral to different ECG cycles and intervals. We executed 100 of iterations on a 10-fold and 5-fold cross-validation method and calculated the average of statistical parameters to show the performance and stability of four classifiers, namely logistic regression (LR), simple decision tree, weighted K-nearest neighbor, and linear support vector machine. Furthermore, different combinations of proposed features were employed as a feature selection procedure based on classifier's performance using the aforementioned trained classifiers.

Results:

The results of our proposed method to diagnose MI utilizing all the proposed features with an LR classifier include 90.37%, 94.87%, and 86.44% for accuracy, sensitivity, specificity, respectively. Also, we calculated the standard deviation value for the accuracy of 0.006.

Conclusion:

Our proposed classification-based method successfully classified and diagnosed MI using different combinations of presented features. Consequently, all proposed features are valuable in MI diagnosis and are praiseworthy for future works.

The Importance of the 15-lead Versus 12-lead ECG Recordings in the Diagnosis and Treatment of Right Ventricle and Left Ventricle Posterior and Lateral Wall Acute Myocardial Infarctions

Introduction

The 12-lead ECG at admission of patients suffering from acute myocardial infarction (AMI) is mandatory for accurate diagnosis and prompt therapeutic measures, mainly reperfusion. It has been shown that recording additional ECG leads may improve the diagnostic accuracy and therefore, the prognosis of selected cases.

Aim

The aim of the study was to assess the usefulness of the 15-lead ECG (12 classic plus 3 posterior leads) in the management of chest pain patients, especially when 12-lead ECG is not diagnostic of AMI.

Methods

Total amount of 186 consecutive patients (127 men, 59 women, mean age 69.7±13.8 years) were admitted with an acute coronary syndrome. The initial ECG recorded the 12 classic leads, and subsequently, the 3 additional posterior leads. Demographic and clinical data, including ECG alterations and selected treatment strategy, were also studied. The cumulative impact of the 15-lead ECG on the diagnosis and management of AMI were, overall, evaluated.

Results

The 12-lead ECG was diagnostic of ST-elevation AMI (STEMI) in 158 patients (Group A-84.5%) who were promptly reperfused. On the other hand, the interpretation of the posterior leads was required in 28 patients (Group B-15.1%) to establish the STEMI diagnosis warranting reperfusion therapy. Multivariate analysis illustrated that the 15-lead ECG was the only factor associated with achieving the STEMI diagnosis in non-conclusive 12-lead ECG cases (OR=2.43-p=0.04).

Conclusion

The use of the 15-lead ECG contributes to a faster and more accurate diagnosis of STEMI, particularly in the Emergency Department, facilitating the prompt reperfusion therapy.

Capacitive ECG system with direct access to standard leads and body surface potential mapping

Capacitive electrodes provide the same access to the human electrocardiogram (ECG) as galvanic electrodes, but without the need of direct electrical skin contact and even through layers of clothing. Thus, potential artifacts as a result of poor electrode contact to the skin are avoided and preparation time is significantly reduced. Our system integrates such capacitive electrodes in a 15 sensor array, which is combined with a Tablet PC. This integrated lightweight ECG system (cECG) is easy to place on the chest wall and allows for simultaneous recordings of 14 ECG channels, even if the patient is slightly dressed, e.g., with a t-shirt. In this paper, we present preliminary results on the performance of the cECG regarding the capability of recording body surface potential maps (BSPMs) and obtaining reconstructed standard ECG leads including Einthoven, Goldberger and, with some limitations, Wilson leads. All signals were measured having the subject lie in a supine position and wear a cotton shirt. Signal quality and diagnostic ECG information of the extracted leads are compared with standard ECG measurements. The results show a very close correlation between both types of ECG measurements. It is concluded that the cECG lends itself to rapid screening in clinically unstable patients.

Electrocardiographic body surface mapping: potential tool for the detection of transient myocardial ischemia in the 21st century?

Coronary artery disease (CAD) is one of the leading causes of cardiovascular mortality and morbidity worldwide. CAD presents as a wide spectrum of clinical disease from stable angina to ST segment elevation myocardial infarction. The 12-lead electrocardiogram (ECG) has been the main tool for the diagnosis of these events for almost a century but is limited in its diagnostic ability. For patients with suspected angina, the exercise tolerance test is often used to provoke and detect stress-induced ischemia but does not provide a definitive answer in a substantial proportion of patients. Body surface mapping (BSM) is a technique that samples multiple points around the thorax to provide a more comprehensive electrocardiographic data set than the conventional 12-lead ECG. Moreover, recent preliminary data demonstrate that BSM can detect and display transient regional myocardial ischemia in an intuitive fashion, employing subtraction color mapping, making it potentially valuable for diagnosing CAD causing transient regional ischemia. Research is ongoing to determine the full extent of its utility.

Micro-Magnetocardiography System With a Single-Chip SQUID Magnetometer Array for QT Analysis and Diagnosis of Myocardial Injury in Small Animals

Development of drugs requires electrophysiological studies of small animals like mice, rats or guinea pigs. Electrocardiography (ECG) of hirsute animals is time-consuming. We have developed a micro magnetometer array with a 9-channel superconducting quantum interference device (SQUID) with a 2.5-mm diameter pickup-coil for noncontacting measurement of magnetocardiograms (MCGs) in small animals. The micro-MCG successfully recorded the PQRST complex in mice, rats and guinea pigs. A regional myocardial injury was made in rat hearts with a cryoinjury probe, and the characteristic pattern of the injury was recorded in the MCG. An anterior myocardial injury created a QS pattern in the MCG, and a posterior myocardial injury created a QR pattern in the MCG. Quinidine-induced QT prolongation was successfully detected by micro-MCG in mice and rats. Simultaneous recording of ECG and MCG was conducted after intraperitoneal administration of quinidine (60 mg/kg) in guinea pigs. QT interval corrected for heart rate (QTc) in both ECG and MCG correlated well. The newly developed micro-MCG may facilitate electrophysiological studies of small animals, and may enable high-throughput screening of drug-induced QT abnormality.

Selection of optimal recording sites for limited lead body surface potential mapping in myocardial infarction and left ventricular hypertrophy

A lead selection algorithm was applied to find optimal recording sites for limited lead body surface potential maps. The studied population consisted of a set of 117 lead body surface potential maps recorded from 744 subjects (229, normal; 278, with myocardial infraction [MI]; and 237, with left ventricular hypertrophy [LVH]). One generic lead set derived from all disease groups was found. Also found were 3 disease-specific lead sets (normal, MI, and LVH) and one specific to abnormal subjects (MI and LVH combined). The performance of each lead set in estimating data from other disease groups was largely similar. This was with the exception of leads specific to LVH in the estimation of normal data and normal leads in the estimation of LVH data. Here, the difference was found to be significant (P < .001). The top 6 recording sites in each lead set did not occupy the same positions as the 6 precordial leads. Although disease-specific lead sets are of limited practical use, this study has illustrated that, largely, there is little difference between the performance of different lead sets. The suboptimality of the 6 precordial leads has also been illustrated.

Optimizing the 12-lead electrocardiogram: a data driven approach to locating alternative recording sites

BACKGROUND

Despite its widespread use, the limitations of the 12-lead electrocardiogram (ECG) are undisputed. The main deficiency is that just a small area of the precordium is interrogated and for some abnormalities information may be transmitted to a region of the body surface where information is not recorded. In this study, we attempted to optimize the 12-lead ECG by using a data-driven approach to suggest alternate recording sites.

METHODS

A sequential lead selection algorithm was applied to a set of 744 body surface potential maps (BSPMs), consisting of recordings from subjects with myocardial infarction, left ventricular hypertrophy, and no apparent disease. A number of scenarios were investigated in which pairs of precordial leads were repositioned; these pairs were V3 and V5, V4 and V5, and V4 and V6. The algorithm was also used to find optimal positions for all 6 precordial leads.

RESULT

Through estimation of entire surface potential distributions it was found that each of the scenarios, with 2 leads repositioned, captured more information than the standard 12-lead ECG. The scenario with V4 and V6 repositioned performed best with a root mean square error of 22.3 microvolts and a correlation coefficient of 0.967. This configuration also fared favorably when compared to the scenario where all 6 precordial leads were repositioned as optimizing all 6 leads offered no significant improvement.

CONCLUSION

This study demonstrated the use of a lead selection algorithm in enhancing the 12-lead ECG. The results also indicated that repositioning just 2 precordial leads can provide the same level of information capture as that observed when all precordial leads are optimally placed.

Diagnosing Old MI by Searching for a Linear Boundary in the Space of Principal Components

Body surface potential mapping (BSPM) is a technique employing multiple electrodes to capture, via noninvasive means, an indication of the heart's condition. An inherent problem with this technique is the resulting high-dimensional recordings and the subsequent problems for diagnostic classifiers. A data set, recorded from a 192-lead BSPM system, containing 74 records is investigated. QRS isointegral maps, offering a summary of the information obtained during ventricular depolarization, were derived from 30 old inferior myocardial infarction and 44 normal recordings. Principal component analysis was applied to reduce the dimensionality of the recordings and a linear classifier was employed for classification. This perceptron-based classifier has been adapted so that the final weight and bias values are estimated prior to the learning process. This estimation process, referred to as the linear hyperplane approach (LHA), derives the estimated weights from a bisector hyperplane, placed orthogonal to the means of two class distributions in an n-dimensional Euclidean space. Estimating weights encourages a network to exhibit better generalization ability. Utilizing a number of different principal components as input features, the LHA achieved an average sensitivity and specificity of 79.58% and 76.45%, respectively, across all experiments. The average accuracy of 76.73% achieved with this approach was significantly better than the other benchmark classifiers evaluated against it.

Body surface mapping versus the standard 12 lead ECG in the detection of myocardial infarction amongst emergency department patients: a Bayesian approach

OBJECTIVE

To determine if body surface mapping (BSM) is better than the standard 12 lead ECG in the diagnosis of acute myocardial infarction amongst emergency department patients.

SETTING

A University affiliated inner-city emergency department.

PARTICIPANTS

People presenting to an emergency department with symptoms compatible with myocardial ischaemia/infarction.

MAIN OUTCOME MEASURES

Myocardial infarction as defined by either standard 12 lead ECG changes with associated cardiac marker rise, Troponin T >0.1 microg/ml at > 12 h or autopsy/surgical findings of fresh macroscopic infarction.

RESULTS

BSM had an overall sensitivity of 47.1% versus 40% for the 12 lead ECG (P < 0.001). Specificity for the BSM was 85.6% versus 93.7% for the 12 lead ECG (P < 0.001). These findings were consistent for low/moderate and high risk subgroups. Bayesian analysis demonstrates that indiscriminate use of BSM would result in a clinically important overdiagnosis of myocardial infarction amongst emergency department patients.

CONCLUSIONS

BSM has a higher sensitivity, but a lower specificity for the diagnosis of myocardial infarction.

Mining for diagnostic information in body surface potential maps: a comparison of feature selection techniques

BACKGROUND

In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM) acquisition process has prohibited its acceptance in clinical practice. For this reason there is an interest in striking a compromise between the minimum number of electrocardiographic recording sites required to sample the maximum electrocardiographic information.

METHODS

In the current study, several techniques widely used in the domains of data mining and knowledge discovery have been employed to mine for diagnostic information in 192 lead BSPMs. In particular, the Single Variable Classifier (SVC) based filter and Sequential Forward Selection (SFS) based wrapper approaches to feature selection have been implemented and evaluated. Using a set of recordings from 116 subjects, the diagnostic ability of subsets of 3, 6, 9, 12, 24 and 32 electrocardiographic recording sites have been evaluated based on their ability to correctly asses the presence or absence of Myocardial Infarction (MI).

RESULTS

It was observed that the wrapper approach, using sequential forward selection and a 5 nearest neighbour classifier, was capable of choosing a set of 24 recording sites that could correctly classify 82.8% of BSPMs. Although the filter method performed slightly less favourably, the performance was comparable with a classification accuracy of 79.3%. In addition, experiments were conducted to show how (a) features chosen using the wrapper approach were specific to the classifier used in the selection model, and (b) lead subsets chosen were not necessarily unique.

CONCLUSION

It was concluded that both the filter and wrapper approaches adopted were suitable for guiding the choice of recording sites useful for determining the presence of MI. It should be noted however that in this study recording sites have been suggested on their ability to detect disease and such sites may not be optimal for estimating body surface potential distributions.