In a pilot study, cardiogoniometry (CGM), a further 3D development of the classical 2D ECG, proved very sensitive in discovering myocardial ischemia.
Cardiogoniometry uses five electrodes to record three-dimensional measurements of the heart’s electrical activity. It requires no physical exercise on a bicycle or the likes. Graphic presentations of the data obtained enable fast localization of the site of any myocardial damage. In a pilot study, the diagnostic value of CGM and classical ECG was compared with that of stress cardiac MRI, the gold standard of non-invasive ischemia diagnostics, in 40 patients with presumed CAD. Here, CGM achieved a sensitivity of 70% and a specificity of 95% in detecting ischemia and scarring in the myocardium; its positive predictive value was 93%. The sensitivity of the classical ECG lagged far behind this (see Table).
Help for patients with unclear symptoms of angina pectoris.
The study non-selectively enrolled patients who underwent a CGM examination as part of their routine diagnostics prior to a stress cardiac MRI. The CGM findings were compared against perfusion deficits or the presence of late enhancement (MRI image of scarring). Patients with normal perfusion and without late enhancement formed the reference group.
Both its high specificity and high positive predictive value suggest that CGM is suitable for CAD screening. According to Dr. Ralf Birkemeyer of Villingen-Schwenningen, CGM will yield good diagnostic findings in patients presenting with unclear symptoms of angina pectoris in outpatient settings. Should the results of the pilot study be confirmed, then CGM will be a conceivable alternative when a stress EKG is contraindicated. The results of the pilot study are currently being verified in the CGM@MRT study on around 100 patients. It is anticipated that the initial data will be presented at conferences starting in April 2012.
|Compared to cardio MRI
||2) ECG Q wave/
|3) ECG Neg. T waves/
|4) ECG combination
of 2) + 3)
|Sensitivity||70 %||25 %||15 %||35 %|
|Specifity||95 %||100 %||95 %||95 %|
|Positive predictive value||93 %||100 %||75 %||88 %|
|Negative predictive value||76 %||56 %||51 %||58 %|