High spatial and temporal resolution retrospective cine cardiovascular magnetic resonance from shortened free breathing real-time acquisitions

Abstract

Background: Cine cardiovascular magnetic resonance (CMR) is challenging in patients who cannot perform repeated breath holds. Real-time, free-breathing acquisition is an alternative, but image quality is typically inferior. There is a clinical need for techniques that achieve similar image quality to the segmented cine using a free breathing acquisition. Previously, high quality retrospectively gated cine images have been reconstructed from real-time acquisitions using parallel imaging and motion correction. These methods had limited clinical applicability due to lengthy acquisitions and volumetric measurements obtained with such methods have not previously been evaluated systematically.

Methods: This study introduces a new retrospective reconstruction scheme for real-time cine imaging which aims to shorten the required acquisition. A real-time acquisition of 16-20s per acquired slice was inputted into a retrospective cine reconstruction algorithm, which employed non-rigid registration to remove respiratory motion and SPIRiT non-linear reconstruction with temporal regularization to fill in missing data. The algorithm was used to reconstruct cine loops with high spatial (1.3-1.8 × 1.8-2.1 mm²) and temporal resolution (retrospectively gated, 30 cardiac phases, temporal resolution 34.3 ± 9.1 ms). Validation was performed in 15 healthy volunteers using two different acquisition resolutions (256 × 144/192 × 128 matrix sizes). For each subject, 9 to 12 short axis and 3 long axis slices were imaged with both segmented and real-time acquisitions. The retrospectively reconstructed real-time cine images were compared to a traditional segmented breath-held acquisition in terms of image quality scores. Image quality scoring was performed by two experts using a scale between 1 and 5 (poor to good). For every subject, LAX and three SAX slices were selected and reviewed in the random order. The reviewers were blinded to the reconstruction approach and acquisition protocols and scores were given to segmented and retrospective cine series. Volumetric measurements of cardiac function were also compared by manually tracing the myocardium for segmented and retrospective cines.

Results: Mean image quality scores were similar for short axis and long axis views for both tested resolutions. Short axis scores were 4.52/4.31 (high/low matrix sizes) for breath-hold vs. 4.54/4.56 for real-time (paired t-test, P = 0.756/0.011). Long axis scores were 4.09/4.37 vs. 3.99/4.29 (P = 0.475/0.463). Mean ejection fraction was 60.8/61.4 for breath-held acquisitions vs. 60.3/60.3 for real-time acquisitions (P = 0.439/0.093). No significant differences were seen in end-diastolic volume (P = 0.460/0.268) but there was a trend towards a small overestimation of end-systolic volume of 2.0/2.5 ml, which did not reach statistical significance (P = 0.052/0.083).

Conclusions: Real-time free breathing CMR can be used to obtain high quality retrospectively gated cine images in 16-20s per slice. Volumetric measurements and image quality scores were similar in images from breath-held segmented and free breathing, real-time acquisitions. Further speedup of image reconstruction is still needed.

Figure 1

Schematic diagram of proposed reconstruction scheme.

Figure 2

An illustration of the Gadgetron based inline reconstruction of retrospective real-time cine imaging. The reconstruction for a slice starts whenever all readout signal for this slice have been sent to the Gadgetron computer on the right. Once the reconstruction is complete, the images are sent back to the scanner host. In this setup, user has the flexibility to configure the external computer for more powerful hardware and software. The functionality of emitting data and receiving images were implemented on the vendor provided reconstruction computer attached to the magnet.

Figure 3

Retrospective real-time cine images with shortened acquisition covering the ventricles. The acquisition for this case is 256 × 144 matrix and 20 s per slice. A total of 10 SAX slices were acquired within 3.5 mins. FFT reconstruction (a) is not robust for the shortened acquisition, leading to degraded image quality, while proposed approach gives good image quality. The 4th image on the top of the left hand panel is an illustration of what happens when the central k-space lines are missing after binning.

Figure 4

Example of k-space of cine series with ‘holes’ after binning. Missing lines in the binned k-space (a) degrades the image quality. After the reconstruction, missing data is filled and image quality is restored (b). The right column shows the log magnitude of k-space. The 20% asymmetric echo portion can be seen on the right end of k-space.

Figure 5

Retrospective real-time cine for different long-axis views. (a) the vertical long-axis or two-chamber view, (b) the four-chamber view, (c) the LV inflow/outflow or three-chamber view. The image quality of retrospective real-time cine on the left is comparable to the segmented breath-hold acquisition on the right. Both the real-time and segmented cine were acquired with 192 × 128 matrix. For the real-time cine, data from 16s of acquisition was used for reconstruction.

Figure 6

Retrospective real-time cine with improved temporal resolution can enhance the visualization of valve. In this 3CH slice, the mitral valve is well captured in both real-time reconstruction (b) and segmented cine (c). The image quality of raw real-time cine (a) is much worse than the retrospective reconstruction. (d) shows the intensity profiles across time for the retrospective real-time and segmented cine. The intensity profile of raw real-time cine is generated by interpolating all images acquired in one cardiac cycle. The trigger time of raw real-time cine is 342 ms and for retro-gated reconstruction (b and c), it is the 7th cardiac phase out of 30 with the approximated trigger time of 395 ms.

Figure 7

An example of segmented cine degraded with imperfect breath-holding (right column), while the retrospective real-time cine (left column) gives good results. Besides being tedious and time-consuming, the repeated breath-holding in the segmented cine also complicates the scanning procedure and reduces the robustness. Both ES (upper row) and ED phases (lower row) are shown.

Figure 8

Bland-Altman plots of end-systolic volume and end-diastolic volume measures for segmented and retrospective real-time cine for two acquisition matrix sizes.

Figure 9

An example of multiple average segmented cine. (a) The breath-held segmented cine; (b) Segmented cine acquired under normal breathing with three times averaging. (c) The retrospective real-time cine reconstructed from 20s acquisition; (d) The raw real-time cine with lower temporal resolution and SNR. The acquired matrix size for this case is 192 × 128. The breath-held cine acquisition took 11s and the three times averaged segmented cine took 31 s to acquire.

Figure 10

Comparison of linear reconstruction and non-linear reconstruction for retrospective cine. (a) Segmented breath-held cine; (b) Retrospective cine using the non-linear SPIRiT; (c) Retrospective cine using the linear SPIRiT (equation 3). (d) Retrospective cine with only zero-filling. No parallel imaging is applied on the binned k-space. The insufficient performance of linear SPIRiT is improved by the non-linear regularization.