Identification of best electrocardiographic leads for diagnosing acute myocardial ischemia.
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Adult↗
Biomedical subjects
F Kornreich
Publications and source records attributed to F Kornreich.
Effect of electrode positioning on ECG interpretation by computer.
The aim of this study was to assess the variability in automated electrocardiogram (ECG) interpretation due to electrode positioning variations. Such variations were simulated by using a set of 746 body surface potential mappings from apparently healthy individuals and patients with myocardial infarction or left ventricular hypertrophy. Four types of electrode position changes were simulated, and the effect on ECG measurements and diagnostic classifications was determined by a computer program. At most 6% of the cases showed important changes in classification for longitudinal shifts. Transversal shifts causes less than 1.5% of important changes. An expert cardiologist, who analyzed a subset of 80 cases, agreed with the computer in 38 of 40 cases in which it made no change. In the 40 cases with large diagnostic changes, the cardiologist made no change in 18 cases. The effect of electrode position changes on ECG classification by an expert cardiologist was about half of the effect determined by computerized ECG classification. The effects on classification are significant; therefore, correct placement of chest electrodes remains mandatory.
Clinical Competence↗
Estimating ECG distributions from small numbers of leads.
The utility of body surface potential mapping to improve interpretation of electrocardiographic information lies in the presentation of thoracic surface distributions to characterize underlying electrophysiology less ambiguously than that afforded by conventional electrocardiography. Localized cardiac disease or abnormal electrophysiology presents itself electrocardiographically on the body surface in a manner in which pattern plays an important role for identifying or characterizing these abnormalities. Thus, in myocardial infarction, transient myocardial ischemia, Wolff-Parkinson-White syndrome, or ventricular ectopy, observation of electrocardiographic potential patterns, their extrema, and their magnitudes permits localization and quantization of the abnormal activity. Conventional electrocardiography assesses pattern information incompletely and does not use information of distribution extrema locations or magnitudes. Thus, increases or decreases in the magnitudes of electrocardiographic features (ST-segment potential displacement, amplitude, or morphology of Q, R, S, or T waves) associated with changes in cardiac sources (ischemia, infarction, conduction abnormalities, etc.) as measured from fixed leads have a high likelihood of being misinterpreted if the distribution itself is changing. In this study, the authors demonstrate the utility of estimating distributions from small numbers of optimally selected leads, including conventional leads, to reduce uncertainty in the interpretation of electrocardiographic information. This issue is highly relevant when thresholds are used to detect significance of potential levels (exercise testing, detection of myocardial infarction, and continuous monitoring to assess ST-segment changes). Significance of this work lies in improved detection and characterization of abnormal electrophysiology using conventional or enhanced leadsets and methods to estimate thoracic potential distributions.
Angioplasty, Balloon, Coronary↗
Interpolation of body surface potential maps.
The performance of four methods for interpolation of body surface potential maps (BSPMs) for different electrode grid densities was assessed. This study is part of a research project on the influence of the variability of 12-lead electrocardiograms on computer interpretation due to small electrode position changes. Interpolated BSPMs can be used to simulate this variability. The set of BSPMs studied, derived from a 117-electrode grid with relatively many electrodes on the left precordial part of the thorax, consisted of 232 cases without abnormalities, 277 with infarction, and 237 with left ventricular hypertrophy. The interpolation methods used were fast Fourier transforms, Chebyshev polynomials, linear functions, and cubic splines (CS). In the horizontal plane, a reference signal was first interpolated and, thereafter, resampled using 11 different sets of electrodes with the number of electrodes ranging from 18 down to 8. In the vertical direction, five grids with electrodes only on the front of the thorax and nine grids with electrodes on the front and back were examined. As a performance measure for interpolation, mean absolute error (MAE) was used: the absolute differences between the reference signal and the interpolated signal, averaged over the QRS on all maps. All methods showed deteriorating performance for decreasing grid density. In the horizontal direction, CS proved to be slightly superior to other methods for the left precordial electrodes for all but the densest grid (e.g., MAE = 22.8 microV vs MAE > 24.8 microV for a 12-electrode grid). For electrodes not in that area, CS performed the best as well (MAE = 16.1 microV for the same grid), with differences with the other methods being small (MAE > 16.4 microV). In the vertical direction, CS showed the best results on the front, both for the dense nonperiodic (MAE = 19.1 microV vs MAE > 26.6 microV for a 6-electrode grid) and periodic grids (MAE = 25.1 microV vs MAE > 26.6 microV for a 12-electrode grid). Linear functions performed best for sparse nonperiodic grids and sparse periodic grids for electrodes on the back, with the difference with CS for the last case being small. The method CS performed best overall, and is recommended for interpolating BSPMs.
Algorithms↗
Map representation and diagnostic performance of the standard 12-lead ECG.
The diagnostic information contained in the standard 12-lead electrocardiogram was assessed by comparing the classification results produced by the standard leads for various clinical settings, such as normal versus myocardial infarction or versus left ventricular hypertrophy to those achieved by 120-lead data or body surface potential maps (BSPMs). Separately, optimal signal leads were extracted from the BSPM by ranking all leads in function of their capability of reconstructing the BSPM. Ranking was achieved by deriving eigenvalues from the covariance matrix calculated from all leads and corresponding measurements. Thus, while comparing the results from the standard leads (diagnostic leads) to those from the original raw map data, a comparison was also performed with respect to the best signal leads, namely the four best and the eight best. From the results observed for all bi- and multigroup classifications, it appeared that the diagnostic yield of the 12 standard leads matched those obtained with a number of signal leads lying between 4 and 8. This indicated that a large overlap still existed between the leads composing the 12-lead ECG (in fact, only 8 independent leads). Another interesting observation resulted from this investigation: although classifiers (discriminating variables) used for classification were identical, whether they originated from the raw standard leads (derived from the raw maps) or from standard leads reconstructed with four or eight signal leads, reconstructed measurements performed better than original measurements. This paradox can be explained by looking at the respective F values. Indeed, since increased F values result from higher ratios between the difference of group means and the composite variance from the pooled groups, higher differences and/or smaller variances produce larger ratios and hence, better group separations.
Body Surface Potential Mapping↗
Analysis of PTCA-induced ischemia using an ECG inverse solution or the wavelet transform.
In patients without significant collaterals, percutaneous transluminal coronary angioplasty (PTCA) produces acute transient ischemia that is detectable in both standard electrocardiograms (ECG) and body surface potential maps (BSPMs). Control recordings made before or between inflations provide personalized baselines, which isolate the effects of ischemia from interpatient differences, such as torso shape and electrode location. In this study, two methods of evaluating PTCA-induced ischemia from BSPM recordings are presented. In the first method, an ECG inverse solution that estimates epicardial potentials from body surface signals using a realistic model of torso geometry is applied. The strength of this method lies in its potential ability to localize areas of cardiac ischemia on the epicardial surface. In the second approach, wavelet transforms were used to perform a multiresolution decomposition of the BSPM data into different frequency bands. The basis functions of the wavelet transform are time-limited and narrow band and hence can be expected to be sensitive to features of the BSPM that originate in discrete electrophysiologic events, such as intrusion of the activation front onto regions of ischemia or arrhythmias due to local conduction abnormalities. The method also offers a means of temporal and frequency localization of cardiac events related to the initiation of injury currents and abnormal conduction due to PTCA-induced ischemia. The inverse solution and the wavelet transform each offer new views of the spatial and temporal courses of acute ischemia potentially leading to new diagnostic insights in ECG patient examination.
Angioplasty, Balloon, Coronary↗
QRST changes during and after percutaneous transluminal coronary angioplasty.
This study reports preliminary results on 45 patients who underwent percutaneous transluminal coronary angioplasty (PTCA); 120-lead data (including the 12-lead standard electrocardiogram [ECG]) were recorded before, during, and after balloon inflation. Twenty-one patients underwent PTCA for left anterior descending coronary disease, 13 for right coronary artery disease, and 10 for left circumflex; 1 patient had combined left anterior descending and right coronary artery disease. In each patient, voltage data recorded during the various phases of the procedure were compared with the patient's own baseline data. In 18 patients, 120 leads were also recorded 24 hours after PTCA. In this study, the usefulness of the standard 12-lead ECG was investigated in locating the coronary artery being occluded, in elucidating the mechanisms of the QRS changes, and in identifying changes occurring 24 hours after completion of the procedure. Results indicate that the observation of ST elevation in the 12-lead ECG may lead to ambiguous interpretation. Also, limiting observation to ST-T patterns alone instead of including QRS changes further hampers correct identification of the involved vessel. QRS modifications during inflation are interpreted as conduction disturbances, although other mechanisms are evoked: study of surface maps may contribute to the understanding of these mechanisms. Changes present 24 hours later are visible in the standard leads, but again, in the absence of the thoracic potential distribution, these are difficult to interpret. These changes were different from those observed after cessation of inflation at the end of the procedure. It is hypothesized that next-day changes may reflect reperfusion injury and/or represent myocardial stunning. Presence of injury and reversibility of changes require further investigation. Also, biochemical markers such as creatine kinase-MB mass, creatine kinase-MB activity, myoglobin, and troponin-T may help elucidate the significance of these findings.
Angioplasty, Balloon, Coronary↗
Body surface potential mapping of ST segment changes in acute myocardial infarction. Implications for ECG enrollment criteria for thrombolytic therapy.
BACKGROUND: Several large, randomized clinical trials have shown that early thrombolytic therapy substantially reduces early mortality after acute myocardial infarction (MI). In most trials, eligibility criteria include typical chest pain and diagnostic ST segment elevation in two or more contiguous leads of the standard 12-lead ECG. Unfortunately, large areas of the thoracic surface are left unexplored by the standard electrode positions. As a consequence, acute MI patients with ST elevation in regions not interrogated by the conventional electrodes may not receive reperfusion therapy and its attendant benefits. METHODS AND RESULTS: The present study compares 120-lead body surface potential map (BSPM) data from 131 patients with acute MI and 159 normal control subjects (N). The MI population was stratified according to the location of ventricular wall motion abnormalities evidenced by radionuclide imaging into 76 patients with anterior MI (AMI), 32 patients with inferior MI (IMI), and 23 patients with posterior MI (PMI). BSPM were recorded within 24 hours of admission. Group mean BSPM of the ST segment were obtained for N, AMI, IMI, and PMI by sampling the time-normalized ST-T waveform at 18 equal intervals and averaging the voltages at each electrode site over the first five of these 18 ST-T time instants. Corresponding discriminant maps were also computed for each pairwise comparison (AMI versus N, IMI versus N, and PMI versus N) by subtracting the normal group mean voltages from each MI group mean voltages and by further dividing each resulting difference by the composite standard deviation calculated from the pooled groups. Discriminant analysis for each bigroup classification was also performed using as measurements the ST magnitudes in 120 electrode sites from each individual. Finally, the number of patients in each MI group with ST changes outside the 95% normal range was calculated for each electrode position. The following results were obtained: 1) In each MI group, ST depression departs more significantly from normal values than ST elevation. 2) The most significant ST changes (both ST elevation and ST depression) are observed in IMI, the least significant in AMI. 3) For each pairwise comparison, measurements from two lead sites are entered into the stepwise discriminant procedure: the first measurement is ST depression, the second ST elevation. Classification rates are 82% for AMI, 93% for PMI, and 100% for IMI at a specificity level of 95%. 4) From the six leads selected for optimal classification of the three MI groups, five are outside the area sampled by the conventional precordial electrodes. 5) The use of site-dependent thresholds for ST measurements based on 95% normal range yields the best compromise between sensitivity and specificity. A fixed threshold of 1 mm for ST elevation or ST depression produces increased sensitivity in AMI at the cost of marked loss in specificity and reduces sensitivity in both IMI and PMI with no benefit in specificity. CONCLUSIONS: Analysis of BSPM identifies areas on the torso where the most significant ST changes most frequently occur in acute MI. Two leads from areas with the most abnormal ST changes achieve optimal classification in each MI class. Of these six leads, five are outside the standard precordial lead positions. ST depression is the most potent discriminator for each MI group and contains information independent from ST elevation. Quantitative analysis of ST magnitude at each electrode site allows determination of best thresholds for ECG criteria. Appropriate selection of ECG leads may help remove inconsistencies in current ECG selection criteria and improve comparability of treatment results.
Adult↗
Location and magnitude of ST changes in acute myocardial infarction by analysis of body surface potential maps.
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Adult↗
Discriminant analysis of the standard 12-lead ECG for diagnosing non-Q wave myocardial infarction.
Discriminant analysis was performed on 12 standard lead data from 159 normal subjects (N) and 304 patients with first myocardial infarction (MI): the latter group consisted of 543 patients with acute non-Q wave MI (NQMI-group A), 68 patients with acute Q wave MI (QMI-group B) and 183 patients (group C) with recent (29) or old (154) QMI. A discriminant function was computed to separate optimally the larger group of QMI patients (group C) from N. A total of 7 features accounted for a specificity of 92% and a sensitivity of 89%. The classification model was then tested on patients with acute MI, regardless of the presence of Q waves (groups A and B); rates of correct classification were 72% for acute NQMI and 85% for acute QMI. The best measurements were voltages in the late portion of the T wave in aVR, V1 and V5, in early and late QRS in V2, at mid-QRS in lead II and in the second half of the P wave in V1. A weighted combination of these features with the coefficients of the discriminant function produced individual discriminant scores for each subject. Group-mean scores were 1.82 for N, -1.27 for acute QMI, -1.14 for old QMI and -.44 for acute NQMI, indicating that acute NQMI was "closer" to N than both acute and old QMI. QRS measurements from the 12-lead ECG were also used to derive the 45 criteria/33 point Selvester score in 53 patients with NQMI: 32% of NQMI were classified as MI with a score of 3 points or more (corresponding to a posterior probability greater than .50). These results were compared with those achieved by multivariate analysis using only QRS measurements: 56% of NQMI were classified as MI with a posterior probability threshold greater than .50. Associating a point score greater than or equal to 1 with criteria for ST-T abnormalities yielded a sensitivity of 72% at a specificity level of 95%. The results emphasize the presence of diagnostic information outside the initial part of QRS, the power of multivariate statistical procedures applied on continuous measurements and the potential benefit of discriminant scores for quantitative assessment of myocardial infarction.
Discriminant Analysis↗
Identification of first acute Q wave and non-Q wave myocardial infarction by multivariate analysis of body surface potential maps.
BACKGROUND: Patients with acute non-Q wave myocardial infarction (NQMI) appear to have more jeopardized residual myocardium at high risk for subsequent angina, reinfarction, or malignant arrhythmias than patients with acute Q wave myocardial infarction (QMI). Unfortunately, conventional electrocardiographic (ECG) criteria have limited utility in recognizing NQMI. METHODS AND RESULTS: The present study combines the increased information content of body surface potential maps (BSPM) over the 12-lead ECG with the power of multivariate statistical procedures to identify a practical subset of leads that would allow improved diagnosis of NQMI. Discriminant analysis was performed on 120-lead data recorded simultaneously in 159 normal subjects and 308 patients with various types of myocardial infarction (MI) by using instantaneous voltages on time-normalized P, PR, QRS, and ST-T waveforms as well as the duration of these waveforms as features. Leads and features for optimal separation of 159 normals from 183 patients with recent or old QMI (group A) were selected. A total of six features from six torso sites accounted for a specificity of 96% and a sensitivity of 94%. All lead positions were outside the conventional electrode sites and selected features were voltages at mid-P, early and mid-QRS, and before and after the peak of the T wave. The discriminant function was then tested on 57 patients with acute NQMI (group B) and 68 patients with acute QMI (group C): Rates of correct classification were 91% and 93%, respectively. Because of the possible deterioration of the results caused by ST-T abnormalities also present in other clinical entities, a second classification model including an independent group of 116 patients with left ventricular hypertrophy (LVH) but without MI was developed. Two additional measurements were required, namely, P wave duration and a mid-QRS voltage on a lead located 10 cm below V1. Testing the model on both acute MI groups produced correct classification rates of 88% for acute NQMI and 93% for acute QMI. Group mean BSPM were plotted for the three MI groups at successive instants throughout the PQRST waveform. Typical patterns for each MI group were identified during PQRST by removing the corresponding normal variability at each electrode site from sequential MI maps. These standardized maps or discriminant maps provided information on the capability of each measurement at each electrode site and at each instant to separate each class of MI from the normal group (N). Striking similarities were observed between the three MI groups, particularly at mid-QRS and throughout ST-T. The closest resemblance was between acute NQMI and old QMI. Discriminant analysis was also performed on the 12-lead ECG: The first classification model (N versus MI) produced correct classification rates of 85% for acute QMI and 70% for NQMI. With the second model (MI versus N or LVH), correct rates were 81% and 65%, respectively. CONCLUSIONS: Diagnosis of acute NQMI and QMI (also in the presence of LVH) can be improved substantially by appropriate selection of ECG leads and features. Comparison of discriminant maps from groups A, B, and C does not support the concept of acute NQMI as a distinct ECG entity but rather as a group with infarcts of smaller size. However, pathophysiological and clinical differences between acute NQMI and acute QMI influence long-term risks and may define different therapeutic approaches.
Adult↗
Improved prediction of left ventricular mass by regression analysis of body surface potential maps.
Electrocardiographic left ventricular (LV) hypertrophy involving ST-T abnormalities, in addition to high QRS voltages, is associated with increased risk of cardiovascular disease mortality. Unfortunately, conventional electrocardiographic criteria have limited utility in the quantitative assessment of LV hypertrophy. Body surface potential maps, which contain diagnostic information not present in commonly used lead systems, were recorded from 117 thoracic sites and 3 limb electrodes in 72 normal subjects and 84 patients with LV hypertrophy. Multiple regression analysis was performed separately for 54 women and 102 men on 120-lead data, using as features instantaneous voltages on time-normalized P, PR, QRS and ST-T waveforms. Leads and features for optimal prediction of echocardiographically determined LV mass were selected. A total of 6 features from 3 torso sites in men, and from the same 3 sites plus 2 others in women, yielded correlations between echocardiographic and electrocardiographic estimates of LV mass of 0.89 and 0.88, respectively. The standard errors of the estimate (SEE), or average errors in predicting LV mass from the regression equations, were 31 and 22 g, respectively. The single most potent predictor in both sexes was a mid-QRS voltage measured on a lead positioned 10 cm below V1; QRS duration, late QRS and early-to-mid T-wave amplitudes recorded in the lower left flank contributed significantly to the performance of both regression models. The optimal electrode sites for electrocardiographic prediction of LV mass were outside the conventional lead locations.(ABSTRACT TRUNCATED AT 250 WORDS)
Adult↗
Diagnostic features of body surface potential maps in patients with myocardial ischemia and normal resting 12-lead electrocardiograms.
Body surface maps recorded from 35 ischemic patients with normal resting 12-lead electrocardiograms were compared with those obtained from 36 age- and sex-matched normal subjects. From instantaneous maps of each subject 187 variables were derived relating to the configuration (80 variables) and magnitude (104 variables) of the potential distribution and duration of the electrocardiographic intervals (3 variables). By using stepwise discriminant analysis we selected 3 variables whose linear combination enabled us to correctly allocate 91% of the study population (jacknife procedure; specificity 92%, sensitivity 91%). To substantiate the validity of the results the discriminant function was tested on a new independent population consisting of 27 ischemic patients and 54 normal subjects from another laboratory. A proper allocation was obtained in 86% of the cases (specificity 87%, sensitivity 85%). The large number of correctly classified ischemic patients and the repeatability of the results indicate that the adopted criteria are good markers of ischemic heart disease.
Adult↗
Diagnostic body surface potential map patterns in left ventricular hypertrophy during PQRST.
Body surface potential maps were recorded from 117 thoracic sites and 3 limb electrodes in 173 normal subjects older than 30 years of age and 122 patients with clinically "pure" left ventricular (LV) hypertrophy. Typical LV hypertrophy map patterns were identified at successive instants during the PQRST waveform by removing from sequential LV hypertrophy maps the corresponding normal variability range at each electrode site. The presence in individual patients of 1 or more patterns typical in time and location of LV hypertrophy allowed retrospective assignment to the LV hypertrophy group. The most consistent discriminant patterns were excessive negative voltages in the anterior torso with reciprocal excess of positive voltages in the upper right chest during the second half of the P wave, excessive negative voltages in the lower right anterior torso at mid-QRS and excessive negative voltages in the left precordium with reciprocal excess of positive voltages in the upper right chest throughout ST-T. Best classification results were achieved with ST-T features, followed by features from the P wave, the QRS waveform and the PR segment. Cumulative use of ST-T and P features yielded a specificity of 94% with a sensitivity of 88%. Little improvement was obtained by the addition of QRS and PR information. The discriminant map criteria were applied to body surface potential maps from 169 new subjects (77 normal subjects ages 20 to 30 years and 92 patients with complicated LV hypertrophy). Little modification in specificity (93%) and sensitivity (90%) was observed. The performance of commonly used standard lead criteria was also tested.(ABSTRACT TRUNCATED AT 250 WORDS)
Action Potentials↗
Multigroup diagnosis of the standard 12-lead electrocardiogram.
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Adult↗
Multigroup diagnosis of body surface potential maps.
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Adult↗
[The diagnostic use of isopotential maps in cardiology].
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Electrocardiography↗
Identification of best electrocardiographic leads for diagnosing left ventricular hypertrophy by statistical analysis of body surface potential maps.
In view of the increased risk of cardiovascular mortality associated with left ventricular (LV) hypertrophy, early recognition and quantitation of LV hypertrophy are important clinical goals. The standard 12-lead electrocardiogram is the easiest and most widely used noninvasive method for the diagnosis of LV hypertrophy; unfortunately, the diagnostic accuracy of commonly used electrocardiographic criteria remains unsatisfactory. Body surface potential maps contain diagnostic information not present in conventional lead systems. The present investigation combines the increased information content of surface maps with the power of multivariate statistical techniques in order to identify practical subsets of electrocardiographic leads that would allow improved diagnosis of LV hypertrophy. Discriminant analysis was performed on 120-lead data simultaneously recorded in 250 normal subjects and 214 patients with LV hypertrophy using as features instantaneous voltages on time-normalized P, PR, QRS and ST-T waveforms as well as the duration of these waveforms. Leads and features for optimal separation of 173 normal subjects aged greater than or equal to 30 years from 122 patients with pure LV hypertrophy were selected. A total of 6 features from 5 torso sites accounted for a specificity of 97% and a sensitivity of 94%. The single most potent discriminator was the duration of the P wave; voltages were measured in mid and late P on leads located in the lower left parasternal area, the left precordial region and the upper right back, in mid-QRS on a lead positioned 10 cm below V1 and slightly before the peak of the T wave on a lead in the lower left flank.(ABSTRACT TRUNCATED AT 250 WORDS)
Adult↗