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压缩感知运动补偿(CosMo):一种用于冠状动脉 MRI 的前瞻性-回顾性联合呼吸导航器。

Compressed-sensing motion compensation (CosMo): a joint prospective-retrospective respiratory navigator for coronary MRI.

机构信息

Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

出版信息

Magn Reson Med. 2011 Dec;66(6):1674-81. doi: 10.1002/mrm.22950. Epub 2011 Jun 10.

Abstract

Prospective right hemidiaphragm navigator (NAV) is commonly used in free-breathing coronary MRI. The NAV results in an increase in acquisition time to allow for resampling of the motion-corrupted k-space data. In this study, we are presenting a joint prospective-retrospective NAV motion compensation algorithm called compressed-sensing motion compensation (CosMo). The inner k-space region is acquired using a prospective NAV; for the outer k-space, a NAV is only used to reject the motion-corrupted data without reacquiring them. Subsequently, those unfilled k-space lines are retrospectively estimated using compressed sensing reconstruction. We imaged right coronary artery in nine healthy adult subjects. An undersampling probability map and sidelobe-to-peak ratio were calculated to study the pattern of undersampling, generated by NAV. Right coronary artery images were then retrospectively reconstructed using compressed-sensing motion compensation for gating windows between 3 and 10 mm and compared with the ones fully acquired within the gating windows. Qualitative imaging score and quantitative vessel sharpness were calculated for each reconstruction. The probability map and sidelobe-to-peak ratio show that the NAV generates a random undersampling k-space pattern. There were no statistically significant differences between the vessel sharpness and subjective score of the two reconstructions. Compressed-sensing motion compensation could be an alternative motion compensation technique for free-breathing coronary MRI that can be used to reduce scan time.

摘要

前瞻性右侧膈肌导航(NAV)常用于自由呼吸冠状动脉 MRI。NAV 会增加采集时间,以便对运动伪影的 K 空间数据进行重采样。在这项研究中,我们提出了一种联合的前瞻性-回顾性 NAV 运动补偿算法,称为压缩感知运动补偿(CosMo)。使用前瞻性 NAV 采集内 K 空间区域;对于外 K 空间,仅使用 NAV 拒绝运动伪影数据,而无需重新采集。随后,使用压缩感知重建来回顾性估计那些未填充的 K 空间线。我们对 9 名健康成年受试者的右冠状动脉进行成像。计算欠采样概率图和旁瓣峰值比,以研究 NAV 生成的欠采样模式。然后,使用压缩感知运动补偿对门控窗为 3 至 10 毫米的右冠状动脉图像进行回顾性重建,并与在门控窗内完全采集的图像进行比较。对每种重建计算定性成像评分和血管锐度的定量值。概率图和旁瓣峰值比表明 NAV 生成了随机的欠采样 K 空间模式。两种重建的血管锐度和主观评分之间没有统计学上的显著差异。压缩感知运动补偿可能是一种用于自由呼吸冠状动脉 MRI 的替代运动补偿技术,可用于减少扫描时间。

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