Electrocardiologic and related methods of non-invasive detection and risk stratification in myocardial ischemia: state of the art and perspectives

Abstract

Background: Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia.

Objectives: To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods.

Methods: In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology.

Results: Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients.

Conclusions: There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.

Keywords: body surface potential mapping; cardiogoniometry; exercise electrocardiography; functional imaging; heart rate variability; resting electrocardiography.

Table 1. Selected electrocardiography-based methods for the detection of myocardial ischemia and CAD in stable and acute phases

Table 2. Selected electrocardiography-based methods for arrhythmic risk detection and stratification for ACD

Figure 1. Overview of electrocardiologic and related methods including their intended applications

Figure 2. Electrocardiographic phases of STEMI adapted from the Pschyrembel database [13]

Figure 3. Nonpathologic (top) and pathologic (bottom) exercise ECG reactions adapted from Pschyrembel database [13]

Figure 4. Overview of the guidelines issued by the European Society of Cardiology (ESC) and German Society of Cardiology (DGK) considering electrocardiologic and related methods concerning acute and stable ischemic situations and risk stratification

Figure 5. Example for high-resolution ECG

Top: Sum vector, Bottom: 3 dimensional frequency spectrum; Left: Patient with late potentials at high risk for sudden cardiac death with prolonged QRS in sum vector (low-amplitude electrical signal which occurs in the terminal QRS complex or within the ST segment) and enhanced high frequency components in the spectrum. Right: Patient with low risk profile and no late potentials, see also [22].

Figure 6. Corrected body surface potential map at the time point 260 ms (cursor position)

Eleven amplitude levels from S11 to S1 in mV are shown (V - front view; H - back of the sphere and the heart). With the kind permission of [28].

Figure 7. Principles of cardiogoniometry

A) Four electrodes are placed at four points on the patient’s thorax as follows: Point 1 (green) at point V4 of Wilson, i.e. in the 5^th intercostal space in the mid-clavicular line; point 2 (white) sagittal to electrode 1 on the back (point V8 of Wilson); point 3 (yellow) is located perpendicularly above electrode 1 at 0.7 times the distance between points 1 and 2; point 4 (red) is placed to the right of point 3 at the same distance as between points 1 and 3. The leads are defined as follows: 4-2 D (dorsal), 4-1 A (anterior), 2-1 I (inferior), 4-3 Ho (horizontal), 3-1 Ve (vertical). B) Points 4-2-1 define the oblique sagittal plane OSP (red); points 4-3-1 define the frontal plane (yellow). The third plane (blue) is orthogonal to the two other planes and contains point 3; it is the sagittal plane perpendicular to the OSP. Projection x is oriented in an antero-dorsal direction and lies in the OSP and the sagittal plane perpendicular to the OSP. Projection y is oriented in a baso-apical direction and lies in the OSP (4-2-1) and the frontal plane (4-3-1). Projection z is oriented in a supero-inferior direction relative to the OSP and lies in the frontal plane (4-3-1) and the sagittal plane perpendicular to the OSP. C) Vector loops from projections x, y and z can be calculated within a Cartesian coordinate system. Figure shows R-Loops (blue) and T-loops (green) of 12 heart cycles and maximum vectors of both (red), calculated on median cycle.

Figure 8. Poincaré plots calculated from HRV (tachogram, a-c), from BPV (systolic d-f SYS; diastolic g-i DIA) blood pressure time series of a healthy subject (top row), a DCM patient with low risk (middle row) and a DCM patient with high risk (bottom row), see also [83]