Biomedical subjects

Matti Stenroos

Publications and source records attributed to Matti Stenroos.

2 recordsLinked to original sources

PubMed2005

Spatial repolarization abnormalities in old myocardial infarction.

Conventional electrocardiogram criteria for myocardial infarction (MI) rely on QRS features, but ST-T segment is also affected. We recorded body surface potential mapping in 24 patients with prior MI and in 24 controls. T-wave maximum amplitude and QRS and ST-T integrals were automatically determined. Old MI was verified by magnetic resonance imaging. ST-T integral and T-wave maximum amplitude outperformed QRS integral in detecting MI, with area under receiver operating characteristic curve of 94%, 95%, and 83%, respectively. ST-T integral performed better in non-Q-wave than Q-wave MI, with area under receiver operating characteristic curve of 97% and 92%, respectively. QRS integral correlated negatively with ST-T integral in patients with MI (r = -0.58, P < .001) and positively in controls (r = 0.45, P < .001). In conclusion, ST-T integral proved equal to QRS integral in old MI detection. Inclusion of ventricular repolarization phase and development of electrocardiographic analysis over larger chest area may improve the QRS-based diagnosis of old myocardial infarction.

Adult↗

PubMed2003

Spatiotemporal characterization of paced cardiac activation with body surface potential mapping and self-organizing maps.

In this study self-organizing maps (SOM) were utilized for spatiotemporal analysis and classification of body surface potential mapping (BSPM) data. Altogether 86 cardiac depolarization (QRS) sequences paced by a catheter in 18 patients were included. Spatial BSPM distributions at every 5 ms over the QRS complex were first presented to an untrained SOM. The learning process of the SOM units organized the maps in such a way that similar BSPMs are represented in particular areas of the SOM network. Thereafter, time trajectories and distance maps were created on the trained SOM from sequential maps in a selected paced QRS. The trajectories and distance maps can be applied as such for the localization of abnormal ventricular activation, as well as quantitative input for statistical classification. The results indicate that the method has potential for locating endocardial sites of abnormal ventricular activation, despite the patient material being too limited to provide a reliable statistical evaluation of the source localization accuracy.

Algorithms↗