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采用具有匹配和基于激励回波图像导航的相控循环的自由呼吸 cine DENSE MRI。

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

机构信息

Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.

Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia.

出版信息

Magn Reson Med. 2018 Nov;80(5):1907-1921. doi: 10.1002/mrm.27199. Epub 2018 Apr 1.

Abstract

PURPOSE

This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T -relaxation echo and blurring.

METHODS

The method identifies phase-cycled spiral interleaves at matched respiratory phases by minimizing the residual signal due to T relaxation after phase-cycling subtraction. Next, the method reconstructs image-based navigators from matched phase-cycled interleaves that are comprised of the stimulated echo (ste-iNAVs). Ste-iNAVs are used for motion estimation and compensation of k-space data. The method was demonstrated in phantoms and compared to diaphragm-based navigator (dNAV) and conventional iNAV (c-iNAV) methods for the reconstruction of free-breathing volunteer data sets (N = 10).

RESULTS

Phantom experiments demonstrated that the proposed method removes striping artifacts and blurring due to motion. Volunteer results showed that respiratory motion measured by ste-iNAVs was better correlated than c-iNAVs to dNAV data (R  = 0.82 ± 0.03 vs. 0.70 ± 0.05, P < 0.05). Match-making reconstructions of free-breathing data sets achieved lower residual T -relaxation echo energy (1.04 ± 0.01 vs. 1.18 ± 0.04 for dNAV and 1.18 ± 0.03 for c-iNAV, P < 0.05), higher apparent SNR (11.93 ± 1.05 vs. 10.68 ± 1.06 for dNAV and 10.66 ± 0.99 for c-iNAV, P < 0.05), and better phase quality (0.147 ± 0.012 vs. 0.166 ± 0.017 for dNAV, P = 0.06, and 0.168 ± 0.015 for c-iNAV, P < 0.05) than dNAV and c-iNAV methods.

CONCLUSION

For free-breathing cine DENSE, the proposed method addresses both types of breathing-induced artifacts and provides better quality images than conventional dNAV and iNAV methods.

摘要

目的

本研究旨在开发一种自由呼吸螺旋电影位移编码的自导航方法,该方法使用相位循环进行伪影抑制,是一种心肌应变成像技术。该方法需要解决 DENSE 运动的 2 个后果:不完全抑制 T 弛豫回波的条纹伪影和模糊。

方法

该方法通过最小化相位循环后 T 弛豫引起的残余信号,识别出相位循环螺旋交织在匹配的呼吸相位。接下来,该方法从由激发回波组成的匹配相位循环交织中重建图像导航器(ste-iNAVs)。Ste-iNAVs 用于运动估计和 k 空间数据的补偿。该方法在体模中进行了验证,并与基于膈肌的导航器(dNAV)和传统的 iNAV(c-iNAV)方法进行了比较,用于重建自由呼吸志愿者数据集(N=10)。

结果

体模实验表明,所提出的方法可以消除由于运动引起的条纹伪影和模糊。志愿者结果表明,与 c-iNAVs 相比,ste-iNAVs 测量的呼吸运动与 dNAV 数据相关性更好(R=0.82±0.03 与 0.70±0.05,P<0.05)。自由呼吸数据集的匹配重建实现了更低的残余 T 弛豫回波能量(1.04±0.01 与 dNAV 的 1.18±0.04 和 c-iNAV 的 1.18±0.03,P<0.05),更高的表观 SNR(11.93±1.05 与 dNAV 的 10.68±1.06 和 c-iNAV 的 10.66±0.99,P<0.05)和更好的相位质量(0.147±0.012 与 dNAV 的 0.166±0.017,P=0.06,和 c-iNAV 的 0.168±0.015,P<0.05),优于 dNAV 和 c-iNAV 方法。

结论

对于自由呼吸电影 DENSE,所提出的方法解决了两种类型的呼吸引起的伪影,并提供了比传统的 dNAV 和 iNAV 方法更好的图像质量。

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