Inner volume echo planar imaging (IV-EPI) is feasible and useful for cardiac diffusion tensor imaging and arterial spin labelling . IV-EPI inherently provides velocity-selective saturation caused by the crusher gradients around the 180º refocusing-pulse. In this study, we characterize this velocity-dependent effect on myocardial signal in systolic and diastolic cardiac phases. We find that a simple velocity distribution model fits the data well, and that the data from our experiments allows us to make recommendation for designing gradients to avoid myocardial signal loss for diastolic and systolic IV-EPI imaging.
Imaging: Three healthy subjects (2M/1F,Age: 23-26) were scanned on a GE 3T Signa HDxt scanner using single-shot partial-Fourier IV-EPI , shown in Fig. 2A; one subject was scanned twice on separate days, resulting in four datasets. The imaging sequence consisted of a 90º spectral-spatial excitation3, zonal refocusing to reduce FOVy4 and partial Fourier EPI (5/8th) to reduce the echo-time and readout duration. TE/TR/FA=51.3/95ms/90, matrix size=128x64, partial-fourier=5/8th , and readout time=40ms. TE was fixed at 51.3ms based on the largest crusher gradients shown in Fig. 2A.
Experiment: A plethysmograph (PG) gated cine bSSFP scan was used to visually determine stable systolic and diastolic phases shown in Fig 1. Trigger-delays were set as ratios of the RR duration to place the imaging at the center of these periods. Eleven images were acquired for each of 14 kv values ( between 0.0125-0.5s/cm) during both systole and diastole, where kv= γAT, γ is the gyromagnetic-ratio, A is the area of each crusher gradient in Fig. 2A, and T is the separation between them.
Reconstruction: Ramp-sampled partial-Fourier EPI data was re-gridded and phase corrected using GE Orchestra then reconstructed using projection over convex sets5 (POCS). Data was then converted to SNR units for analysis6. Images for all kv were aligned using advanced normalization tools7 (ANTs). One image for each subject was manually segmented, with the ROI propagated to all aligned images. The myocardium was divided into 6 segments8 as shown in Fig. 2B and the data for each segment was fitted to the model of velocity-selective modulation of image signal9.
Modeling: The model used here was borrowed from velocity-selective arterial spin labeling literature9, originally developed for capillary blood flow. This assumes that the velocity of spins within a voxel is uniformly distributed from 0 to 2vz , where vz is the average longitudinal-velocity in cm/s . Using this model the velocity-selective modulation of signal amplitude in IV-EPI is given by: $$$S=\vert{M_osinc(2k_v v_z)}\vert$$$, where S is the measured signal, Mo is the scaling term in SNR units . The first zero-crossing of sinc is $$$V_{cut}=1/2k_v$$$ in cm/s and spins moving at velocities faster than Vcut are saturated. 14 Vcut values of 1.0-40cm/s (that correspond to kv values of 0.0125–0.5s/cm) were used for this experiment.
Results are shown in Figs. 3,4 and 5. The estimated average vz of the myocardium was 0.3-1.6cm/s during stable-diastole and 0.9–4.3cm/s during stable-systole. The residue for the fitting (not shown here) was uniform and low for both systole and diastole. Subject 1 had a higher HR of 70-85 (vs subject 2 and 3 with HR of 50-55 and 60-65) and had higher estimated diastolic and systolic velocities. The segment-by-segment variation in SNR was consistent between subjects and the average is shown in Fig. 2C.
Fig. 4 contains representative images from Subject 2 and shows that the model fits the data well for both diastolic and systolic images. Fig. 5. shows a scatter plot of normalized signal from all segments and all subjects plotted. This can be used to infer the choice of Vcut that minimizes the myocardial velocity-saturation.
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