Prediction of myocardial signal during CINE balanced SSFP imaging

摘要

Object: To develop a signal model for accurate prediction of myocardial signal during cine-balanced steady-state free precession (bSSFP) imaging. Methods: We present a signal model that takes into account the effects of non-ideal slice profile, off-resonance, and radio-frequency transmit variation on myocardial signal behavior. Each of the three factors was examined over the range of imaging parameters routinely used in cine bSSFP cardiac imaging at 3 Tesla. Results: In five healthy volunteers and over a wide range of prescribed flip angles, the conventional on-resonance signal model exhibited 28.9 ± 3.9% error, while the proposed model exhibited only 2.9 ± 1.4% error, and therefore more accurate predictions of myocardial signal behavior. Slice profile effects were found to be significant and accounted for most of the improvement. Off-resonance and RF transmit inhomogeneity effects were less significant but did produce more accurate signal prediction. Conclusions: The proposed signal model produced more accurate predictions of myocardial signal compared to existing models and can be used for the optimization of pulse sequences and protocols.