A total of 10 healthy subjects were imaged, five male and five female, with an average age of 30 ± 8 years, average weight of 67 ± 13 kg, and an average heart rate of 60 ± 9 beats per minute. All subjects provided informed consent consistent with the Internal Review Board of our institution. The volunteers were imaged with the 2D FT SSFP technique and the 3D PR SSFP technique.
Imaging was performed with a GE 1.5-T Excite scanner. A commercially provided 3D SSFP sequence was modified to collect projections in the x-y plane and partitions in the slice dimension, as shown in . Modifications provided for a prospective ECG-gated, segmented, multiphase acquisition using projections. Scan parameters for the 3D PR were: 192 readout points (Nr) (full echoes) × 36–48 projections (Np) × 12–14 Nz, flip = 45°, TR/TE = 3.4/1.5 msec, ±125 kHz receiver bandwidth, 8–10 mm slices zero-filled to 4–5 mm, FOV = 32 cm, 21–24 views per segment, 71–82 msec temporal resolution, 24 heartbeat breath-hold, 12 cardiac phases, and no view-sharing. Zero-filling was used for reconstructing the 3D acquisitions because it allows better visualization of the acquired slice resolution (15
The 3D PR SSFP acquires projections in the x-y plane, and partitions in z.
Interleaved projection sets were acquired in alternate cardiac phases as in the UNFOLD or reduced field of view (rFOV) methods (14
). In the rFOV method, two interleaved sets of projections are acquired, e.g., 72 projections are obtained, split into two interleaved sets of 36 Np each. The first or second interleaved set (36 Np each) are obtained in alternate cardiac phases. After reconstruction of the time series, additional artifact suppression is obtained through low-pass temporal filtering, which removes any artifacts that “flickers” in time at the Nyquist (18
The undersampling before rFOV processing was roughly 5 (192 Nr χ 36 Np). The trajectory was centered so that each projection crossed the center of k-space at the echo time, using a recently described method (19
). Reconstruction of the 3D PR data was performed offline using gridding (20
) followed by fast Fourier transform (FFT; www.fftw.org
), and rFOV processing.
Scan parameters for the 2D FT technique were: 192 × 160 encoding matrix, FOV = 32 × 24 cm, flip = 45°, TR/TE = 3.4/1.5 msec, receiver bandwidth = ±125 kHz, 8-mm slices, 3-mm slice gaps, ECG-gating, 12 views-per-segment, 40-msec temporal resolution, full R-R coverage, with arrhythmia rejection and retrospective ECG-gating, and a cine view-sharing technique to reconstruct 30 phases. The slices were acquired using 12 heartbeat breath holds, acquired in 10–12 separate breath holds.
On all datasets (2D FT slices and the corresponding 3D PR slices for each volunteer), the signal-to-noise ratio (SNR) of blood and myocardium, and the contrast to noise ratio (CNR) between blood and myocardium, and between myocardium and lung, were measured. Noise measures on undersampled PR images do not represent thermal noise only; the artifacts present in the image will contribute to the root-mean-square-deviation (RMSD) of the background, providing an effective noise measure that includes artifact. Care was taken to measure noise in the PR images in a background region without discrete streak artifacts.
For quantitative analysis, the end systolic frame was defined as the frame with the smallest LV cavity area. The end diastolic frame was defined as the first frame directly after the QRS complex. The most basal slice for both systole and diastole was chosen based on the presence of myocardium in that frame. An experienced cardiologist drew regions of interest (ROI) around the epicardial and endocardial surfaces (excluding trabeculae and papillary muscles) on each slice, using commercially provided software (Cine Tool; General Electric, Waukesha, WI). These tracings allowed automatic calculation of LVEF, LVEDV, LVESV, and LVEDM.
For all individual measurements (N
= 10) using both the 2D FT and the 3D PR technique, the means and standard deviations (SDs) were calculated. Statistical differences between the 2D and 3D methods were assessed by a Student's paired t-test. The cutoff for statistical significance was P
< 0.05. The limits of agreement between the two techniques were estimated as the mean difference between the techniques ±2 SD of the differences, using the Bland-Altman analysis (21
). A second experienced reader also traced the LV contours in the 10 volunteers to allow measurement of interob-server variability. For each technique (2D and 3D), the interobserver variability was assessed by calculating the correlation (R2
) between the two sets of measurements. The variability, defined as the SD of the differences between corresponding observations, divided by the average value (in percent), and the mean and SD of differences between corresponding observations, was also calculated.