Evaluation of an edge-based registration method: application to magnetic resonance first-pass myocardial perfusion data.

Purpose: Quantification of cardiac magnetic resonance (CMR) myocardial perfusion remains time consuming since it requires manual interventions to compensate for motion. Thus, the aim of this study was to evaluate a semiautomated registration method.

Materials And Methods: A rigid edge-based registration algorithm was applied on 10 patients who had rest and stress CMR acquisitions on three slice levels (apical, midventricular and basal slices). Registration efficiency was assessed qualitatively by evaluating the quality of k-means maps in terms of symmetry and heart structures identification before and after registration and quantitatively by estimating noise amplitude within the myocardium. Finally, residual registration errors were manually estimated.

Results: Before registration, k-means maps were satisfactory for 15 of 30 slices at rest and for only 5 of 30 slices during stress. After registration, the k-means maps quality was satisfactory for 29 of 30 slices at rest and for 30 of 30 slices during stress. Moreover, registration reduced noise amplitude from 49±26 to 29±11 at rest (P<.01) and from 52±14 to 30±10 during stress (P<.01). The residual horizontal and vertical shifts were 0.06±0.12 and 0.04±0.08 mm at rest and 0.32±0.69 and 0.28±0.53 mm at stress.

Conclusion: The registration was successfully tested on rest and stress CMR perfusion data. It provides a valuable basis for quantitative evaluation of myocardial perfusion.