Prediction of myocardial signal during CINE balanced SSFP imaging

To develop a signal model for accurate prediction of myocardial signal during cine-balanced steady-state free precession (bSSFP) imaging.

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.

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.

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.