Performance of an ST dipole model for description of ST deviations in myocardial ischemia.
BACKGROUND
Recent studies have proposed to include both ST depression and ST elevation in the diagnosis of myocardial ischemia, hence, considering all ST deviations relevant. In this study, we examined to which extent an ST dipole model accounts for the measured ST deviations in acute ischemia patients using 2 different sets of lead vectors.


METHODS
12-Lead electrocardiograms (ECGs) were recorded from 45 patients with occlusive single-vessel disease with thrombolysis in myocardial infarction (TIMI) flow 0/1 (15 anterior descending artery, 15 right coronary artery, 15 left circumflex artery), and ST deviations were measured in the J point in all leads. The dipole model was established by considering ST deviations as projections of a single dipole onto a set of lead vectors. A set of simplified unit length lead vectors and a set of lead vectors from the Dower transformation were compared. For each ECG and model, the best-fitting dipole was estimated by minimizing the sum of squared errors between measured and projected ST deviations across all leads.


RESULTS
The goodness-of-fit metric (R(2)) for all recordings showed strong agreement between measured and projected ST deviations for both dipole models with R(2) of 0.77 to 0.83 (95% confidence interval [CI]) for the simplified model and R(2) of 0.91 to 0.93 (95% CI) for the Dower-based model. The Dower-based model showed superior performance for the whole population and for each of the occlusion artery subgroups (P < .05), but only small differences were seen between the estimated ST dipoles from the 2 models.


CONCLUSIONS
A simple dipole model may be a useful descriptor of ST-segment deviations, reducing ST deviation measurements from 12 leads to a single 3-dimensional vector.
Andersen
Mads P
MP
Department of Health Science and Technology, Aalborg University, DK-9220 Aalborg, Denmark. mpa@hst.aau.dk
Terkelsen
Christian J
CJ
Sørensen
Jacob T
JT
Struijk
Johannes J
JJ
D000368:Aged; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006329:Heart Conduction System / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D017202:Myocardial Ischemia / Q000175:diagnosis* / Q000503:physiopathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity