Characterisation of acute myocardial ischaemia in a canine model based on principal component analysis of unipolar endocardial electrograms

The study presents a method for identifying endocardial electrical features relevant to local ischaemia detection at rest. The method consists of, fir st, normalisation of electrograms to a uniform representation; secondly, th e use of principal component analysis to reduce the dimensionality of the e lectrogram vector space; and, thirdly, a search for a classification axis t hat matches the degree of ischaemia present in the tissue. Left ventricular myocardial states were assessed by echocardiography and NOGA (TM) mapping in eight dogs at baseline and then immediately after, 5h after and 3 days a fter occlusion of the left anterior descending coronary artery. Five princi pal components were required to approximate electrograms with an average er ror of less than 10% of the peak-to-peak amplitude. Correlations of 0.77, 0 .80 and 0.84 were obtained between the principal component-based parameters and the echocardiography scores at the three ischaemic stages, respectivel y. Expression of these parameters in the time domain showed that the major changes occurred in the depolarisation segment of the endocardial electrogr am as well as in the ST-segment. In conclusion, the proposed method provide s a suitable alternative co-ordinate system for the classification of ischa emic regions and highlights signal segments that change as a result of path ology.