Background: Detection of myocardial ischemia was studied with multichannel exercise magnetocardiography (MCG). A surface gradient method was applied to analyze cardiac magnetic fields.Methods: We studied 27 patients with single vessel coronary artery disease (CAD) and 17 healthy volunteers. The MCG was recorded over anterior chest during supine bicycle ergometry. The two-dimensional direction of the maximum spatial magnetic field gradient was determined during the ST segment and at the T-wave apex at different phases of stress test.Results: The CAD patient group was separated from controls by the orientation of the magnetic field gradient during the ST segment at cessation of exercise (CAD 167 ? 68" vs controls 106 ? 49"; P < 0.005) and at 4 minutes postexercise, but not at rest. The CAD patient group was separated from controls also by the orientation of the magnetic field gradient at the T-wave apex at 4 minutes postexercise (CAD 87 ? 60" vs controls 58 +-18"; P < 0.05), but not at rest. The change in the orientation of the field gradient at the T-wave apex 4 minutes postexercise, compared to baseline, was greater in CAD patients (31 +-43") than in controls (9 ? 8"; P < 0.05). This change was larger in the patient group with stenosis in the right than in the left coronary artery (P < 0.05).Conclusions: Transient acute myocardial ischemia causes well-recognizable changes in the magnetocardiogram at the ST segment and the T wave. The orientation of the maximum spatial gradient of the magnetic field can be used as a parameter to determine these changes.

Studies of weak magnetic fields are generally influenced by magnetic noise emanating from thermal agitation of electric charge (Johnson noise) in electrically conducting materials surrounding the magnetic-field sensor. In this article, the thermal magnetic noise fields generated by slabs with high electric conductivity (copper, aluminum) or high magnetic permeability (mu metal) are studied. The analysis is based both on a previously published phenomenological model and on measurements with an ultrasensitive superconducting magnetometer. Both the spectral densities and spatial correlations of the magnetic field fluctuations are evaluated. The computed correlation coefficients are utilized to develop a practical method for estimating the thermal noise due to thin conducting foils, such as thermal radiation shields in a cryogenic measurement Dewar. Also experiments to reduce the Dewar noise are reported. Finally, estimations are presented for the thermal noise fields arising in the walls of a magnetically shielded room. In practice, thermal magnetic noise, particularly due to the superinsulation in cryogenic Dewars, can be the limiting factor of sensitivity in measurements of weak biomagnetic signals arising in the human heart and brain. The results are useful in the estimation and minimization of the contribution of thermal noise.

This study identified magnetocardiographic and BSPM recording locations which are sensitive for detecting transient myocardial ischemia by evaluation of the ST segment as well as the T-wave. These locations strongly depend on ischemic regions and are outside the conventional 12-lead ECG recording sites.

QT dispersion is a measure of heterogeneity in ventricular repolarization. Increased ECG QT dispersion is associated with life-threatening ventricular arrhythmias. We studied if magnetocardiographic (MCG) measures of QT dispersion can separate postmyocardial infarction patients with and without susceptibility to sustained VT. Manual dispersion measurements were compared to a newly adapted automatic QT interval analysis method. Ten patients with a history of sustained VT (VT group) and eight patients without ventricular arrhythmias (Controls) were studied after a remote myocardial infarction. Single-channel MCGs were recorded from 42 locations over the frontal chest area and the signals were averaged. QT dispersion was defined as maximum-minimum or standard deviation of measured QT intervals. VT group showed significantly more QT and JT dispersion than Controls. QTapex dispersions were 127 +/- 26 versus 83 +/- 21 ms (P = 0.004) and QTend dispersions 130 +/- 37 versus 82 +/- 37 ms (P = 0.013), respectively. Automatic method gave comparable values. Their relative differences were 9% for QTapex and 27% for QTend dispersion on average. In conclusion, increased MCG QT interval dispersion seems to be associated with a susceptibility to VT in postmyocardial infarction patients. MCG mapping with automated QT interval analysis may provide a user independent method to detect nonhomogeneity in ventricular repolarization.