Assessment of myocardial infarct size with body surface potential mapping: validation against contrast-enhanced cardiac magnetic resonance imaging.

BACKGROUND: Assessment of myocardial infarct (MI) size is important for therapeutic and prognostic reasons. We used body surface potential mapping (BSPM) to evaluate whether single-lead electrocardiographic variables can assess MI size. METHODS: We performed BSPM with 120 leads covering the front and back chest (plus limb leads) on 57 patients at different phases of MI: acutely, during healing, and in the chronic phase. Final MI size was determined by contrast-enhanced cardiac magnetic resonance imaging (DE-CMR) and correlated with various computed depolarization- and repolarization-phase BSPM variables. We also calculated correlations between BSPM variables and enzymatic MI size (peak CK-MBm). RESULTS: BSPM variables reflecting the Q- and R wave showed strong correlations with MI size at all stages of MI. R width performed the best, showing its strongest correlation with MI size on the upper right back, there representing the width of the "reciprocal Q wave" (r = 0.64-0.71 for DE-CMR, r = 0.57-0.64 for CK-MBm, P < 0.0001). Repolarization-phase variables showed only weak correlations with MI size in the acute phase, but these correlations improved during MI healing. T-wave variables and the QRSSTT integral showed their best correlations with DE-CMR defined MI size on the precordial area, at best r = -0.57, P < 0.0001 in the chronic phase. The best performing BSPM variables could differentiate between large and small infarcts at all stages of MI. CONCLUSIONS: Computed, single-lead electrocardiographic variables can estimate the final infarct size at all stages of MI, and differentiate large infarcts from small.

Predicting recovery of myocardial function by electrocardiography after acute infarction.

BACKGROUND: In acute ischemic left ventricular (LV) dysfunction, distinguishing viable myocardium is clinically important. METHODS: Body surface potential mapping (Electrocardiography [ECG] with 123 leads), was recorded in 62 patients with acute coronary syndrome (ACS). ECG variables were computed from de- and repolarization phases. LV segmental wall motion was assessed by echocardiography acutely and after 1 year. RESULTS: The number of dysfunctional segments (DFS) diminished during follow-up in 37 patients (recovery group) and remained the same or increased in 25 patients (nonrecovery group). Acutely, DFS was 5.7 ± 2.1 versus 4.4 ± 2.4 (P = 0.02), and peak CK-MBm 141 ± 157 versus 156 ± 167 µg/L (P = 0.78) in the recovery versus nonrecovery group. At follow-up, DFS was 1.9 ± 1.7 versus 6.5 ± 2.6 (P < 0.001). The best ECG variable to predict decrease in DFS depended on the region of acute LV dysfunction: The best variable in the left anterior descending region was the integral of the first QRS integral (area under the curve [AUC] 0.82, P = 0.002); in the right coronary artery region, this was the integral of the ST segment (AUC 0.98, P = 0.003); and in the left circumflex region, the area including the ST segment and the T wave (AUC 0.97, P = 0.006). CONCLUSIONS: In ACS patients, computed ECG variables predict recovery of LV function from ischemic myocardial injury, even in the presence of comparable CK-MBm release and LV dysfunction.

Can strain rate imaging predict recovery of contraction after acute myocardial infarction?

AIMS: To assess whether strain rate imaging (SRI) can serve to evaluate myocardial viability in patients with acute coronary syndrome (ACS). METHODS AND RESULTS: In 23 patients with ACS, we measured longitudinal tissue Doppler strain and strain rate values from left ventricular basal, mid, and apical segments (n = 414). These segments were grouped according to their acute end-systolic strain values (S(ES)) into those with normocontraction (S(ES)≤-13%), hypocontraction (S(ES) between -13 and -7%), and severe contraction abnormality (S(ES)>-7%). At 8 months, we evaluated the recovery of contraction: Segments with acutely severe contraction abnormality that improved their strain values to ≤-7% were defined as viable, and those that failed to do so as non-viable. In the acute phase, S(ES), post-systolic strain, as well as systolic, early, and late diastolic strain rate values were significantly better in the viable than in the non-viable segments. Post-systolic strain had the best AUC 0.78, and a cut-off value of -3.8% predicted recovery from severe contraction abnormality with a sensitivity of 85% and specificity of 62%. The transmurality of the infarction, assessed by magnetic resonance imaging with delayed enhancement, was significantly larger in the non-viable than in the viable segments (P = 0.006). Acute global S(ES) and systolic strain rate showed the best correlations with final global S(ES) and global infarction percentage after recovery. CONCLUSION: SRI can serve to evaluate myocardial viability in patients with ACS, and to assess the recovery of segmental as well as global left ventricular function.

Tissue Doppler strain-mapping in the assessment of the extent of chronic myocardial infarction: validation using magnetic resonance imaging.

AIMS: The distribution of myocardial strain values can be visualized by colour-coded strain images. We examined for the first time if this strain-mapping function can be used to study the extent of prior myocardial infarction. METHODS AND RESULTS: Echocardiography and cardiac magnetic resonance imaging with delayed contrast enhancement were performed in 26 patients with chronic myocardial infarction. Two-dimensional strain images of the left ventricle were obtained in all standard apical views. Myocardial segments (n = 416) were assigned a score ranging from one to four based on the strain-coded colour of the segment, with higher scores representing worse myocardial function. Strain-mapping scores and quantitative strain values averaged, respectively, 1.3 +/- 0.6 and -16.4 +/- 7.6% in segments without infarction, 1.7 +/- 1.0 and -15.0 +/- 8.6% in non-transmural infarctions, and 2.8 +/- 1.2 and -6.5 +/- 8.6% in transmural infarctions. Strain-mapping had a sensitivity of 60% and a specificity of 95% in detecting segments with transmural myocardial infarction. Corresponding values for echocardiographic wall motion analysis were 50 and 96%. Strain-mapping was possible in 80% of the segments and inter-observer agreement was substantial (kappa = 0.63). CONCLUSION: Strain-mapping is a clinically applicable method for the assessment of regional myocardial function in post-myocardial infarction patients. Strain-mapping has reasonable feasibility and is more sensitive in detecting infarction damage than routine wall motion analysis.