Abstract
PURPOSE: Diastolic function evaluation requires estimates of early and late diastolic mitral filling velocities (E and A) and of mitral annulus tissue velocity (e'). We aimed to develop an MRI method for simultaneous all-in-one diastolic function evaluation in a single scan by generating a 2D phase-contrast (PC) sequence with balanced steady-state free precession (bSSFP) contrast (PC-SSFP). E and A could then be measured with PC, and e' estimated by valve tracking on the magnitude images, using an established deep learning framework. METHODS: Our PC-SSFP used in-plane flow-encoding, with zeroth and first moment nulling over each TR. For further acceleration, different k-t principal component analysis (PCA) methods were investigated with both retrospective and prospective undersampling. PC-SSFP was compared to separate balanced SSFP cine and PC-gradient echo acquisitions in phantoms and in 10 healthy subjects. RESULTS: Phantom experiments showed that PC-SSFP measured accurate velocities compared to PC-gradient echo (r = 0.98 for a range of pixel-wise velocities -80 cm/s to 80 cm/s). In subjects, PC-SSFP generated high SNR and myocardium-blood contrast, and excellent agreement for E (limits of agreement [LOA] 0.8 ± 2.4 cm/s, r = 0.98), A (LOA 2.5 ± 4.1 cm/s, r = 0.97), and e' (LOA 0.3 ± 2.6 cm/s, r = 1.00), versus the standard methods. The best k-t PCA approach processed the complex difference data and substituted in raw k-space data. With prospective k-t PCA acceleration, higher frame rates were achieved (50 vs. 25 frames per second without k-t PCA), yielding a 13% higher e'. CONCLUSION: The proposed PC-SSFP method achieved all-in-one diastolic function evaluation.