Parallel imaging in cardiovascular MRI: methods and applications.
Cardiovascular MR imaging (CVMR) has become a valuable modality for the non-invasive detection and characterization of cardiovascular diseases. CVMR requires high imaging speed and efficiency, which is fundamentally limited in conventional cardiovascular MRI studies. With the introduction of parallel imaging, alternative means for increasing acquisition speed beyond these limits have become available. In parallel imaging some image data are acquired simultaneously, using RF detector coil sensitivities to encode simultaneous spatial information that complements the information gleaned from sequential application of magnetic field gradients. The resulting improvements in imaging speed can be used in various ways, including shortening long examinations, improving spatial resolution and/or anatomic coverage, improving temporal resolution, enhancing image quality, overcoming physiological constraints, detecting and correcting for physiologic motion, and streamlining work flow. Examples of each of these strategies will be provided in this review. First, basic principles and key concepts of parallel MR are described. Second, practical considerations such as coil array design, coil sensitivity calibrations, customized pulse sequences and tailored imaging parameters are outlined. Next, cardiovascular applications of parallel MR are reviewed, ranging from cardiac anatomical and functional assessment to myocardial perfusion and viability to MR angiography of the coronary arteries and the large vessels. Finally, current trends and future directions in parallel CVMR are considered.
Niendorf
Thoralf
T
Department of Diagnostic Radiology, University Hospital, RWTH Aachen, Pauwelsstrasse 30, 52057 Aachen, Germany.
Sodickson
Daniel K
DK
D000465:Algorithms; D000818:Animals; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000295:instrumentation / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods*; D009206:Myocardium / Q000473:pathology*; D009716:Numerical Analysis, Computer-Assisted; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation