Background Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) enables the estimation of myocardial infarct (MI) extent. Nevertheless, manual quantification is time consuming and subjective. We sought to assess MI volume with different quantitative methods in both acute (AMI) and chronic MI (CMI). Methods CMR was performed 50±21 h after MI in 52 patients and was repeated 100±21 days later in a subgroup of 34 patients. Then, necrosis volumes were quantified using: 1) manual delineation, 2) automated fuzzy c-means method, and 3) +2 to 6SD thresholding approaches. Results were compared against peak values of serum Troponin I (TnI), creatine kinase (CK) and left ventricular (LV) functional parameters: LV ejection fraction (LVEF), indexed end-diastolic (EDVi), end-systolic volumes (ESVi) and the number of hypokinetic segments (NbHk). Results For CMI, quantitative evaluation of infarct size using manual, +2SD, +3SD and fuzzy c-means provided equivalent results in terms of correlation coefficients for comparisons of MI volumes against LV function parameters (LVEF: r>0.79, p<0.0001; ESVi: r>0.82, p<0.0001, EDVi: r>0.67, p<0.0001, NbHk: r>0.54, p<0.0009). For AMI, +2SD and fuzzy c-means approaches provided higher correlations for comparisons of AMI volumes against biochemical markers (CK: r>0.79, p<0.0001,TnI: r>0.77, p<0.0001) and chronic LV function parameters (LVEF: r>0.82, p<0.0001, NbHk: r>0.59, p<0.0002). Conclusions The fuzzy c-means and 2SD methods provided highest correlations with biochemical MI quantification as well as LV function parameters. The fuzzy c-means approach which does not require an arbitrary identification of the remote myocardium is fast and reproducible. It may be clinically useful in the evaluation of patients with MI.

We sought to assess myocardial infarct (MI) volume with different quantitative methods in both acute (AMI) and chronic MI (CMI) from CMR late Gadolinium Enhancement images. CMR exam was performed 50±21 hours after MI in 52 patients and was repeated 100±21 days later in a subgroup of 34 patients. Necrosis volumes were quantified using: 1) manual delineation, 2) automated fuzzy c-means method, and 3) +2 to 6SD thresholding approaches. Results were compared against peak values of serum Troponin I (TnI), creatine kinase (CK) and LV functional parameters. For CMI, quantitative evaluation of infarct size using manual, +2SD, +3SD and fuzzy c-means provided equivalent results for comparisons of MI volumes against LV function parameters (r>;0.79, p<;0.0001). For AMI, +2SD and fuzzy c-means approaches provided higher correlations for comparisons of AMI volumes against biochemical markers (r>;0.77, p<;0.0001) and chronic LV function parameters (r>;0.59, p<;0.0002). The fuzzy c-means and +2SD methods provided highest correlations with biochemical MI quantification as well as LV function parameters. The fuzzy c-means approach which does not require an arbitrary identification of the remote myocardium is fast and reproducible. It may be clinically useful in the evaluation of patients with MI.

Quantification of cardiac magnetic resonance (CMR) myocardial perfusion remains time consuming since it requires manual intervention to compensate for motion. Thus, the aim of this study was to test an automated registration method. We studied 10 patients who had rest and stress CMR perfusion exams. For both exams, three short-axis slices were selected. Then, a rigid edge based registration algorithm was performed. Its quality was assessed 1) qualitatively by comparing the k-means clustering maps obtained before and after registration. 2) quantitatively by estimating noise amplitude within the myocardium. Registration substantially improved myocardial symmetry and heart structures identification on the k-means maps in 12/16 slices at rest and 22/27 slices at stress. It reduced noise amplitude from 48±26 to 28±10 at rest (p≪0.05) and from 53±13 to 31±10 during stress (p≪0.05). Our method performed successfully on both rest and stress CMR perfusion data.

Quantification of myocardial edema and necrosis during acute myocardial infarct (MI) is crucial for patientpsilas prognosis. The aim of this study was to evaluate these two parameters from MRI late gadolinium enhancement (LGE) and T2 weighted short Tau inversion recovery (STIR) black-blood sequences acquired in 22 patients with MI. To estimate the necrosis and edema volumes, a clustering method based on a fuzzy c-means algorithm was used. Results were compared against a manual delimitation and a semi-automatic thresholding currently reported in the literature. The proposed estimation of the necrosis volume was strongly correlated with both the semi automatic method and the manual delineation (r>0.9). For the quantification of the edema, the approach was valid, except for small size infarcts. Thus the automated quantification of necrosis is reliable compared to conventional approaches, and the method is encouraging for the quantification of edema.