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从欠采样的黄金 RPE 采集中获得高效的 3D 运动补偿腹部 MRI。

Highly efficient 3D motion-compensated abdomen MRI from undersampled golden-RPE acquisitions.

机构信息

Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, King's College London, St Thomas' Hospital, 4th Floor, Lambeth Wing, London, SE1 7EH, UK,

出版信息

MAGMA. 2013 Oct;26(5):419-29. doi: 10.1007/s10334-013-0370-y. Epub 2013 Feb 13.

Abstract

OBJECT

A common approach to compensate for respiratory motion in free-breathing 3D magnetic resonance imaging (MRI) is navigator gating where MRI data is only acquired when the respiratory signal coincides within a small predefined acceptance window. However, this leads to poor scan efficiency and prolonged scan times. Here, we propose a method to reconstruct motion-compensated 3D MRI of the abdomen acquired during free-breathing with nearly 100% scan efficiency without increasing scan time.

MATERIALS AND METHODS

The approach is based on a self-gated golden-radial phase encoding sampling scheme that allows for the reconstruction of multiple undersampled 3D images at different respiratory positions. Non-rigid image registrations and time-wise motion field interpolations are employed to form 3D motion models that combine all low-quality images into one high-quality motion-compensated image.

RESULTS

Our highly efficient technique allows reconstruction of 3D liver MRI with a high isotropic resolution of 1.75 mm from a short acquisition of 1.1 min. The approach is validated in 10 healthy volunteers by comparing image quality to data sets acquired with a self-gating approach.

CONCLUSION

Our method reduces scan time by 56% compared to the gating technique while similar image quality is preserved.

摘要

目的

在自由呼吸 3D 磁共振成像(MRI)中,补偿呼吸运动的常用方法是导航门控,仅在呼吸信号在小预设接受窗口内匹配时才采集 MRI 数据。然而,这导致扫描效率差且扫描时间延长。在这里,我们提出了一种在不增加扫描时间的情况下,以近 100%的扫描效率重建自由呼吸期间腹部运动补偿 3D MRI 的方法。

材料和方法

该方法基于自门控金放射状相位编码采样方案,允许在不同呼吸位置重建多个欠采样 3D 图像。采用非刚性图像配准和时间运动场插值,形成 3D 运动模型,将所有低质量图像组合成一个高质量的运动补偿图像。

结果

我们的高效技术允许从 1.1 分钟的短采集重建具有 1.75 毫米高各向同性分辨率的 3D 肝脏 MRI。该方法在 10 名健康志愿者中得到验证,通过与自门控方法采集的数据进行比较,评估图像质量。

结论

与门控技术相比,我们的方法将扫描时间减少了 56%,同时保持了相似的图像质量。

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