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  • Oral presentation
  • Open Access

Evaluation of accelerated real-time CMR using sparse sampling with iterative SENSE reconstruction in patients and volunteers

  • 1,
  • 1,
  • 2,
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Journal of Cardiovascular Magnetic Resonance201416 (Suppl 1) :O12

https://doi.org/10.1186/1532-429X-16-S1-O12

  • Published:

Keywords

  • Left Ventricle
  • Short Axis Slice
  • Sparse Sampling
  • Left Ventricle Ejection Fraction
  • Entire Left Ventricle

Background

The use of gated CMR can be limited by motion artifacts secondary to cardiac and respiratory motion. Imaging is especially challenging in patients with arrhythmias or those who cannot perform adequate breath-holds. Real-time CMR is a non-gated technique that has been successfully applied in scenarios where standard segmented acquisitions break down. In this study, we sought to accelerate real-time acquisition by using sparse sampling with an iterative SENSE reconstruction.

Methods

Seven consecutively recruited patients undergoing non-emergent CMR (58 ± 18 years, M:F = 3:4) and 6 volunteers (38 ± 11 years, M:F = 4:2) were included in this IRB-approved study. CMR was performed at 1.5T (MAGNETOM Aera, Siemens Healthcare, Erlangen, Germany). The examination included acquisitions of standard segmented SSFP (iPAT2) (GRAPPA accel factor 2, TR 40 msec, 2.1 × 2.1 × 10 mm3) cine, standard real time (TPAT3) (TPAT accel factor 3, TR 62 msec, 2.9 × 2.9 × 7 mm3), and the investigational prototype sparsely sampled SSFP with iterative SENSE reconstruction with L1 regularization along one spatial and temporal dimension (SPARSEi9.9) (accel factor 9.9, TR 43 msec, 2.0 × 2.0 × 7 mm3) (1). Each technique was used to acquire a three-, four-chamber, and short axis series in identical slice positions (Figure 1), with coverage of the entire left ventricle (LV) and 10 mm interslice gaps. Individual slice scan times were recorded. Quantitative LV functional analysis was performed. A reviewer blinded to acquisition type scored images for overall image quality, noise, and artifacts using a 5-point Likert scale. Continuous variables were compared between groups using a paired t-test, and ordinal variables were compared using a Wilcoxon signed-rank test.
Figure 1
Figure 1

Visual comparison of the standard segmented (iPAT2), accelerated real-time iterative SENSE reconstruction (SENSE i 9.9), and accelerated real-time (TPAT3) CMR in a 73 year-old patient undergoing imaging for post-operative aortic valve replacement. 4-chamber (A), 3-chamber (B), and mid-short axis slices (C) are shown.

Results

In a combined analysis of patients and volunteers, there was no significant difference between LV ejection fraction between iPAT2 and SPARSEi9.9 (p = 0.18) or TPAT3 (p = 0.31), and there was no difference between either real time acquisition (p = 0.83). The iPAT2 technique measured higher myocardial mass than SPARSEi9.9 (105 ± 25 g vs. 95 ± 30 g, p = 0.004) and TPAT3 (86 ± 26 g, p < 0.001). The iPAT2 technique was superior to both SPARSEi9.9 (p < 0.001) and TPAT3 (p < 0.001) in overall image quality. The SPARSEi9.9 group had higher image quality compared to TPAT3 (p < 0.001), but TPAT3 had marginally reduced noise (p = 0.01) and reduced artifact (p < 0.001). (Figure 2) Short axis slice acquisition times were shorter for SPARSEi9.9 (3.8 ± 0.6 sec) than iPAT2 (8.9 ± 1.5 sec, p < 0.001) and TPAT3 (5.7 ± 1.0 sec, p < 0.001).
Figure 2
Figure 2

Qualitative analysis in patients and volunteers.

Conclusions

Highly accelerated real-time CMR using sparse sampling with iterative SENSE reconstruction can be successfully applied in patients and volunteers with accurate calculation of LV functional parameters. Image quality is reduced relative to gold-standard segmented acquisitions, but is superior to standard real-time acquisitions. 1. Liu J, et al. ISMRM 20th Annual Meeting. Melbourne, Australia, 2012:4249.

Funding

NIH NCI 5R25CA132822-04.

Authors’ Affiliations

(1)
Radiology, Northwestern University, Chicago, Illinois, USA
(2)
Siemens AG Healthcare Sector, Erlangen, Germany
(3)
Siemens Corporate Technology, Princeton, New Jersey, USA
(4)
Siemens Healthcare USA, Inc., Chicago, Illinois, USA

Copyright

© Allen et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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