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Improved bulk myocardial motion suppression for navigator‐gated coronary magnetic resonance imaging
Author(s) -
Jahnke Cosima,
Nehrke Kay,
Paetsch Ingo,
Schnackenburg Bernhard,
Gebker Rolf,
Fleck Eckart,
Nagel Eike
Publication year - 2007
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.21078
Subject(s) - translation (biology) , affine transformation , magnetic resonance imaging , breathing , medicine , nuclear medicine , motion (physics) , mathematics , computer science , radiology , artificial intelligence , anatomy , geometry , biochemistry , chemistry , messenger rna , gene
Purpose To evaluate the impact of a new, cross‐correlation based method for compensation of respiratory induced motion of the heart using an individually adapted three‐dimensional (3D) translation or affine transformation approach. Materials and Methods A total of 32 patients underwent a routine cardiac MR examination. In each patient, a calibration scan was performed during free‐breathing to register breathing‐related motion within a 3D ellipsoid registration kernel covering the entire heart. Three navigators were employed for all three spatial dimensions (feet‐head, anterior‐posterior, and left‐right) and the optimal translatory correction factors for each spatial dimension were determined. In addition, the cross‐correlations for different motion models (no compensation, fixed 1D‐translation, adapted 3D‐translation, and affine transformation) were calculated. Results The mean correction factor for the feet‐head direction was 0.45 ± 0.13. Though the mean correction factors for the anterior‐posterior and left‐right direction were nearly zero (–0.01 ± 0.08 and 0.02 ± 0.09, respectively), the correction factors exceeded the amount of 0.1 in 12 (19%) and in 19 patients (30%), respectively. All motion compensation models showed significantly higher cross‐correlations when compared to “no compensation” ( P < 0.05). In particular, the affine transformation algorithm achieved the highest cross‐correlation values (88.3 ± 5.1%) with a significant increase compared to fixed 1D translation (84.7 ± 6.5%, P < 0.05). Conclusion A considerable number of patients demonstrated relevant breathing‐related movement of the heart in the anterior‐posterior or left‐right direction in addition to the predominant breathing‐related movement in the feet‐head direction. Thus, it is recommended to compensate for all three spatial dimensions. The affine transformation algorithm combined with three navigators significantly improved breathing‐related cardiac motion compensation when compared to the conventionally applied 1D translation with a fixed correction factor. J. Magn. Reson. Imaging 2007;26:780–786. © 2007 Wiley‐Liss, Inc.