HyperQ™ Technology- A Reliable Non-invasive Tool for Ischemia Detection
Conventional ECG interpretation is performed by inspecting the ECG in the 0.05-100 Hz frequency band. Detection of ischemia relies upon recognition of abnormal alterations in the repolarization phase of the cardiac cycle, manifested as changes in the ST segment of the ECG. However, significant research efforts during the last decade have shown that ischemia also induces changes to the depolarization phase. These changes can be detected by examining the high-frequency content of the mid-QRS complex (HFQRS). These high frequency components, resulting from the fragmented waveform of electrical activation of the myocardium, can be filtered from high resolution ECG signals in the 150 to 250 Hz frequency band. As these components are very low in amplitude (measured in µV), sophisticated computer analysis is required to reliably extract them.
Figure 1: Frequency band of standard ECG components is typically 0.05-100Hz. HFQRS represents subtle changes in the 150-250Hz band, resulting from the fragmented waveform of electrical activation of the myocardium
The HyperQ™ Signal Analysis
High-resolution ECG acquisition hardware, employing a sampling rate of 1000Hz and using standard, conventionally-placed ECG electrodes, is used to record the ECG signal.
HyperQ™ technology uses a multifaceted process to interpret the information acquired by the ECG hardware. This process includes identification of the QRS complex, rejection of corrupted signals, several alignment procedures, signal to noise enhancement, and filtering.
The HyperQ analysis can be used for several clinical processes. First, it can be used in a stress ECG test to improve the diagnosis of Coronary Artery Disease (CAD). In this case, it can accurately detect the development of demand ischemia by monitoring the changes of the HFQRS throughout the exercise – from the resting phase, through peak exercise until the recovery phase, when the patient returns to her baseline signal. Second, it can be used in a resting ECG test to improve the diagnosis of Acute Coronary Syndrome (ACS) most markedly in the case of Non ST elevation ACS, where conventional ECG is often equivocal. Other cases include continuous ECG monitoring both for bed-side and Holter monitoring, monitoring signals from electrodes of implantable
cardiac devices and even telemonitoring applications for home care patients. Below we will focus on the stress and rest applications of HyperQ.
The HyperQ analysis process consists of the following steps (Figure 2):
Detection of valid complexes
Alignment and averaging of detected QRS complexes to improve signal-to-noise ratio
Detection of QRS boundaries
Band-pass filtering (150-250Hz) to obtain HFQRS
Extraction of intensity and morphology indices from HFQRS to produce a HyperQ trend line or a color-coded HFQRS map (HyperMap™).
Figure 2: HyperQ Signal Analysis
Using HyperQ™ for better diagnosis of ischemic heart disease
Recent studies have shown that the high-frequency component of the ECG signal provides a unique insight into the patient’s ischemic condition.
Figure 3: HyperQ™ versus classical ECG for an IHD patient, during a stress test
Figure 3 presents a typical example of the HyperQ™ signal during different stages of an exercise stress test of an ischemic patient. The first row in the figure indicates the heart rate. The second row presents the standard ECG signal and the third row presents the corresponding HyperQ™ signal. The HyperQ™ signal shows a significant change as the exercise test progresses. The marked decrease in the signal’s amplitude is particularly notable. The trend line of HyperQ during the exercise test (Figure 4), demonstrates significant reduction in HyperQ intensity in multiple leads, which is indicative of ischemic heart disease.
Figure 4: A positive HyperQ stress response
Figure 5: HyperQ™ versus classical ECG for non-ischemic subject, during a stress test
In comparison, the HyperQ™ signal in a non-ischemic patient as shown in figure 5 retains similar amplitude under different conditions of stress, and the HyperQ trend lines (Figure 6) exhibit moderate changes, classified as a non-ischemic response.
Figure 6: A negative HyperQ stress response
HyperMap™ : Visual Representation of HyperQ
BSP’s HyperMap™ color graph provides a major diagnostic advantage by helping the physician understand the patient’s condition at a glance. The HyperMap™ graphic is an efficient presentation of the dynamic changes of the HyperQ™ signal during stress, which shows the patient’s ischemic status, by depicting the proportion of high amplitude sections of the signal to low amplitude sections.
Figure 7: HyperMap™, BSP’s novel method for the presentation of HyperQ™ signal. Filtered QRS signals are converted into colored columns. Different colors are assigned to different amplitudes, where red represents high amplitude and blue low amplitude
Accurate horizontal alignment of the QRS color columns produces the charts shown below. In the resulting time-time-amplitude chart, Y-axis represents time along the QRS, X-axis represents running time and the hue represents the signal’s amplitude.
HyperMap™ offers a convenient depiction of the changing signal during continuous measurement, such as exercise stress ECG testing. The ease of use and unique graphical representation of the HyperQ™ technology, along with its clear clinical advantages, provide an unbeatable combination for ECG testing and analysis.
Figure 8: 12-lead HyperMap™ obtained during a stress test
The HyperQ Rest analysis process consists of the following steps (Figure 9):
Detection of valid QRS complexes
Alignment and averaging of detected QRS complexes to improve signal-to-noise ratio and detection of QRS boundaries
Band-pass filtering to obtain HFQRS
Extraction of HFQRS envelope and detection of Reduced Amplitude Zones (RAZ)
Quantification of RAZ to produce an index of ischemia
Figure 9: HyperQ Rest Signal Analysis
Improved ACS diagnosis using HyperQ Rest
Although Resting ECG tests are one of the most important tools available for Emergency Department staff for diagnosing patients that present with acute chest pain, it is well known that not all ACS patients can be accurately diagnosed with conventional ECG. Specifically, Non ST elevation MI (NSTEMI) patients may often present with equivocal or even normal ECG. HyperQ can dramatically change this scenario by helping the physician reach a definite conclusion much faster than today.
Figure 10: Conventional ECG results for a 62 yo female (patient A) presenting to the ER with chest pain. Interpretation of this test demonstrates normal ECG results.
Figures 10 – 12 demonstrate a typical case of a NSTEMI patient presenting to the Emergency Room with chest pain. The conventional ECG results, as shown in figures 10 and 11, are normal and give no hint to the actual condition of the patient. The HyperQ results in figure 12 however, show very clearly that this is not a normal test. Six out of the 12 leads depict significant Reduced Amplitude Zones and are clearly marked by the system as such.
Figures 13-15 and 16-18 give two additional examples of NSTEMI patients with equivocal conventional ECG tests and a clear indication of ACS in the HyperQ results.
Figure 11: Full disclosure view of the ECG results for patient A above.
Figure 12: HyperQ results for patient A above show significant HyperQ changes, as indicated by the automatic interpretation.
Figure 13: Conventional ECG results for a 69 yo male (patient B) presenting to the ER with chest pain.
Figure 14: Full disclosure view of the ECG results for patient B above.
Figure 15: HyperQ results for patient B above show significant HyperQ changes, as indicated by the automatic interpretation.
Figure 15 does not show any high frequency data for lead V4. This sometimes occurs when the noise level is too high, despite the multiple signal processing techniques employed for enhancing the signal and limiting the noise. Insufficient signal quality may be caused by excessive motion of the patient during the test, detached or loosely connected electrodes and rarely, also external electronic interference.
Figure 16: Conventional ECG results for a 57 yo male (patient C) presenting to the ER with chest pain.
Figure 17: Full disclosure view of the ECG results for patient C above.
Figure 18: HyperQ results for patient C above show significant HyperQ changes, as indicated by the automatic interpretation.