Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
IEEE Trans Med Imaging. 2012 Mar;31(3):805-15. doi: 10.1109/TMI.2011.2181997. Epub 2012 Jan 18.
Magnetic resonance imaging (MRI) has been commonly used for guiding and planning image guided interventions since it provides excellent soft tissue visualization of anatomy and allows motion modeling to predict the position of target tissues during the procedure. However, MRI-based motion modeling remains challenging due to the difficulty of acquiring multiple motion-free 3-D respiratory phases with adequate contrast and spatial resolution. Here, we propose a novel retrospective respiratory gating scheme from a 3-D undersampled high-resolution MRI acquisition combined with fast and robust image registrations to model the nonrigid deformation of the liver. The acquisition takes advantage of the recently introduced golden-radial phase encoding (G-RPE) trajectory. G-RPE is self-gated, i.e., the respiratory signal can be derived from the acquired data itself, and allows retrospective reconstructions of multiple respiratory phases at any arbitrary respiratory position. Nonrigid motion modeling is applied to predict the liver deformation of an average breathing cycle. The proposed approach was validated on 10 healthy volunteers. Motion model accuracy was assessed using similarity-, surface-, and landmark-based validation methods, demonstrating precise model predictions with an overall target registration error of TRE = 1.70 ± 0.94 mm which is within the range of the acquired resolution.
磁共振成像（MRI）已广泛用于指导和规划图像引导介入，因为它可以提供出色的解剖结构软组织可视化效果，并允许进行运动建模，以预测手术过程中目标组织的位置。然而，由于难以采集具有足够对比度和空间分辨率的多个无运动的三维呼吸相位，基于 MRI 的运动建模仍然具有挑战性。在这里，我们提出了一种新的基于三维欠采样高分辨率 MRI 采集和快速、稳健的图像配准的回顾性呼吸门控方案，以模拟肝脏的非刚性变形。该采集利用了最近引入的黄金径向相位编码（G-RPE）轨迹。G-RPE 是自门控的，即可以从采集的数据本身中得出呼吸信号，并且可以在任意呼吸位置回顾性重建多个呼吸相位。非刚性运动建模用于预测平均呼吸周期的肝脏变形。该方法在 10 名健康志愿者上进行了验证。使用相似性、表面和标志点验证方法评估运动模型的准确性，结果表明模型预测非常精确，整体目标配准误差 TRE = 1.70 ± 0.94mm，在采集分辨率范围内。
