Purpose: To assess respiratory motion models for coronary magnetic resonance angiography (CMRA). In this study various motion models that describe the respiration-induced 3D displacements and deformations of the main coronary arteries were compared. Materials and Methods:Multiple high-resolution 3D coronary MR images were acquired in healthy volunteers using navigator-based respiratory gating, each depicting the coronary vessels at different respiratory motion states. In the images representing the different inspiratory states the displacements and deformations of the main coronary vessels with respect to the end-expiratory state were determined, by means of elastic registration. Several correction models (superior-inferior (SI) translation, 3D translation, and 3D affine transformation) were tested and compared with respect to their ability to map a selected inspiratory to the end-expiratory motion state.Results: 3D translation was found to be superior over SI translation, which is commonly used for prospective motion correction in CMRA. The 3D affine transformation was found to be the best correction model considered in this study. Furthermore, a large intersubject variability of the model parameters was observed. Conclusion:The results of this study indicate that a patient-adapted 3D correction model (3D translation or better 3D affine) will considerably improve prospective motion correction in CMRA.

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Image processing was used as a fundamental tool to derive motion information from magnetic resonance (MR) images, which was fed back into prospective respiratory motion correction during subsequent data acquisition to improve image quality in coronary MR angiography (CMRA) scans. This reduces motion artifacts in the images and, in addition, enables the usage of a broader gating window than commonly used today to increase the scan efficiency. The aim of the study reported in this paper was to find a suitable motion model to be used for respiratory motion correction in cardiac imaging and to develop a calibration procedure to adapt the motion model to the individual patient. At first, the performance of three motion models [one-dimensional translation in feet-head (FH) direction, three-dimensional (3-D) translation, and 3-D affine transformation] was tested in a small volunteer study. An elastic image registration algorithm was applied to 3-D MR images of the coronary vessels obtained at different respiratory levels. A strong intersubject variability was observed. The 3-D translation and affine transformation model were found to be superior over the conventional FH translation model used today. Furthermore, a new approach is presented, which utilizes a fast model-based image registration to extract motion information from time series of low-resolution 3-D MR images, which reflects the respiratory motion of the heart. The registration is based on a selectable global 3-D motion model (translation, rigid, or affine transformation). All 3-D MR images were registered with respect to end expiration. The resulting time series of model parameters were analyzed in combination with additionally acquired motion information from a diaphragmatic MR pencil-beam navigator to calibrate the respiratory motion model. To demonstrate the potential of a calibrated motion model for prospective motion correction in coronary imaging, the approach was tested in CMRA examinations in five volunteers.

The C-MAC videolaryngoscope was suitable for prehospital emergency endotracheal intubations with complicated airway conditions, such as maxillo-facial trauma. The option to perform direct laryngoscopy and videolaryngoscopy with the same device appears to be exceptionally important in the prehospital setting.

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