Milan B. Horacek

Identification of best electrocardiographic leads for diagnosing anterior and inferior myocardial infarction by statistical analysis of body surface potential maps

In view of the increasing interest in quantifying and modifying the size of myocardial infarction (MI), it is important to look for clinically practical subsets of electrocardiographic leads that allow the earliest and most accurate diagnosis of the presence and electrocardiographic type of MI. A practical approach is described, taking advantage of the increased information content of body surface potential maps over standard electrocardiographic techniques for facilitating clinical use of body surface potential maps for such a purpose. Multivariate analysis was performed on 120-lead electrocardiographic data, simultaneously recorded in 236 normal subjects, 114 patients with anterior MI and 144 patients with inferior MI, using as features instantaneous voltages on time-normalized QRS and ST-T waveforms. Leads and features for optimal separation of normal subjects from, respectively, anterior MI and inferior MI patients were selected. Features measured on leads originating from the upper left precordial area, lower midthoracic region and the back correctly identified 97% of anterior MI patients, with a specificity of 95%; in patients with inferior MI, features obtained from leads located in the lower left back, left leg, right subclavicular area, upper dorsal region and lower right chest correctly classified 94% of the group, with specificity kept at 95%. Most features were measured in early and mid-QRS, although very potent discriminators were found in the late portion of the T wave.(ABSTRACT TRUNCATED AT 250 WORDS)

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)

Qualitative and quantitative analysis of characteristic body surface potential map features in anterior and inferior myocardial infarction

Body surface potential maps were recorded from 120 electrode sites in 236 normal subjects and 258 patients with initial evidence of either anterior myocardial infarction (MI) or inferior MI to identify characteristic map patterns in both groups. After time normalization, averaged map distributions were displayed at 18 equal time intervals during both QRS and ST-T waveforms from the normal, anterior MI and inferior MI groups. At each time instant, the 120-point averaged normal map was subtracted in turn from the corresponding anterior and inferior MI maps; the resulting differences at each electrode site were divided by the pooled standard deviation and the obtained values (discriminant indexes), plotted as contour lines with 1 standard deviation increments, producing discriminant maps for each bi-group comparison. The most consistent discriminant patterns in 114 patients with anterior MI were observed in early QRS in the upper left anterior chest where abnormal negative voltages reflected loss of electric potentials while reciprocal changes were noticed in the lower back; by mid-QRS, both distributions had moved jointly and vertically, the former in the lower torso on the midsternal line, the latter in the upper back. In 144 patients with inferior MI, abnormal positive distributions were observed in early QRS in the upper back, followed later by excessive negative voltages in the inferior right anterior chest; at mid-QRS, both distributions had migrated horizontally, the former proceeding toward the upper anterior torso, the latter to the lower left dorsal area.(ABSTRACT TRUNCATED AT 250 WORDS)

Multigroup diagnosis of the standard 12-lead electrocardiogram.

Most studies on diagnostic classification of the electrocardiogram (ECG) deal with only two diagnostic categories at once, for example normals versus anterior myocardial infarction, normals versus inferior myocardial infarction, or normal versus left ventricular hypertrophy. ~-5 Such procedures can be helpful for selecting optimal measurements and providing better insight in diagnostic criteria, and in some important applications, such as monitoring patients with acute myocardial infarction, a normal versus myocardial infarction setting may suffice. Bigroup comparisons, however, are not realistic in clinical practice, where often more than two diagnostic entities must be considered. 6 The multigroup approach was first developed by Pipberger et al. 7 Other investigators have since then applied multivariate statistical techniques for classification of both the vectorcardiogram (VCG) and the ECG in a multigroup setting. 8-1~ The set of measurements to be entered into the multigroup classification scheme generally results from pooling the most disciminating variables selected from each pairwise comparison. The total accuracy--percentage of correctly classified subjects--has varied from 63% to 87%, depending on the lead system, the number of groups, and whether prior probabilities were used. Most reports have placed greater emphasis on the

Multivariate analysis of body surface potential maps in left ventricular hypertrophy

Discriminant analysis was performed on ECG data simultaneously recorded using 120 leads for 250 normal subjects and 214 patients with left ventricular hypertrophy (LVH). Instantaneous voltages on time-normalized P, PR, QRS, and ST-T waveforms as well as the durations of these waveforms were used as features. A total of six features from five 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, in mid QRS, and slightly before the peak of the T wave. The optimal sites for LVH diagnosis were in general outside the conventional ECG lead locations. In comparison, multivariate analysis on the standard 12 leads correctly classified 86% of pure LVH patients and 83% of complicated LVH cases at specificity rates of 94% and 93%, respectively.<<ETX>>