Magnetic Resonance–Guided Coronary Artery Stent Placement in a Swine Model
Magnetic Resonance–Guided Coronary Artery Stent Placement in a Swine Model
复制标题
磁共振引导下猪模型冠状动脉支架置入术
DOI:
10.1161/hc0702.104165
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发表时间:
2002
期刊:
影响因子:
--
通讯作者:
A. Buecker
中科院分区:
文献类型:
--
作者:
E. Spuentrup;A. Ruebben;T. Schaeffter;W. Manning;R. Günther;A. Buecker
Background—Magnetic resonance (MR)–guided coronary artery stent placement is a challenging vascular intervention because of the small size of the coronary arteries combined with incessant motion during the respiratory and cardiac cycles. These obstacles necessitate higher temporal and higher spatial resolution real-time MR imaging techniques when compared with interventional peripheral MR angiography. Methods and Results—A new, ultrafast, real-time MR imaging technique that combines steady-state free precession (SSFP) for high signal-to-noise ratio and radial k-space sampling (rSSFP) for motion artifact suppression was implemented on a 1.5-T clinical whole-body interventional MR scanner. The sliding window reconstruction technique yielded a frame rate of 15/s allowing for data acquisition during free breathing and without cardiac triggering. Eleven balloon-expandable stainless steel coronary stents were placed in both coronary arteries of 7 pigs (40 to 70 kg body weight) using a nitinol guidewire and passive device visualization. Position of the coronary stents was controlled by a navigator-gated free-breathing ECG–triggered three-dimensional SSFP coronary MRA sequence and confirmed visually on the ex vivo heart. The presented real-time MR imaging sequence reliably allowed for high-quality coronary MR fluoroscopy without motion artifacts in all pigs. Ten of 11 coronary stents were correctly placed under MR guidance. One stent dislodged proximally from the left main coronary artery because of too-small balloon size. Stent dislocation was correctly predicted during real-time MR imaging. Conclusion—The presented approach allows for real-time MR-guided coronary artery stent placement in a swine model.
影响因子:
158.5
作者:
Kim, RJ;Wu, E;Judd, RM
通讯作者:
Judd, RM
影响因子:
37.8
作者:
Lardo, AC;McVeigh, ER;Halperin, HR
通讯作者:
Halperin, HR