Image-based deformable motion compensation in cone-beam CT: translation to clinical studies in interventional body radiology

S. Capostagno, A. Sisniega, J. W. Stayman, T. Ehtiati, C. R. Weiss, J. Siewerdsen
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引用次数: 1

Abstract

Purpose: Complex, involuntary, non-periodic, deformable motion presents a confounding factor to cone-beam CT (CBCT) image quality due to long (>10 s) scan times. We report and demonstrate an image-based deformable motion compensation method for CBCT, including phantom, cadaver, and animal studies as precursors to clinical studies. Methods: The method corrects deformable motion in CBCT scan data by solving for a motion vector field (MVF) that optimizes a sharpness criterion in the 3D image (viz., gradient entropy). MVFs are estimated by interpolating M locally rigid motion trajectories across N temporal nodes and are incorporated in a modified 3D filtered backprojection approach. The method was evaluated in a cervical spine phantom under flexion, and a cadaver undergoing variable magnitude of complex motion while imaged on a mobile C-arm (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Further assessment was performed on a preclinical animal study using a clinical fixed-room C-arm (Artis Zee, Siemens Healthineers, Forchheim, Germany). Results: In phantom studies, the algorithm resolved visibility of cervical vertebrae under situations of strong flexion, reducing the root-mean-square error by 60% when compared to a motion-free reference. Reduced motion artifacts (blurring, streaks, and loss of soft-tissue edges) were evident in abdominal CBCT of a cadaver imaged during small, medium, and large motion-induced deformation. The animal study demonstrated reduction of streaks from complex motion of bowel gas during the scan. Conclusion: Overall, the studies demonstrate the robustness of the algorithm to a broad range of motion amplitudes, frequencies, data sources (i.e., mobile or fixed-room C-arms) and other confounding factors in real (not simulated) experimental data (e.g., truncation and scatter). These preclinical studies successfully demonstrate reduction of motion artifacts in CBCT and support translation of the method to clinical studies in interventional body radiology.
锥形束CT基于图像的可变形运动补偿:在介入性人体放射学中的临床研究转化
目的:复杂的、非自愿的、非周期性的、可变形的运动是锥形束CT (CBCT)图像质量的一个干扰因素,因为扫描时间长(>10秒)。我们报告并展示了一种基于图像的CBCT变形运动补偿方法,包括幻影,尸体和动物研究作为临床研究的先驱。方法:该方法通过求解运动矢量场(MVF)来修正CBCT扫描数据中的可变形运动,该运动矢量场优化了3D图像中的清晰度标准(即梯度熵)。通过在N个时间节点上插值M个局部刚性运动轨迹来估计MVFs,并将其纳入改进的3D滤波反向投影方法中。该方法在屈曲下的颈椎幻像和在移动c型臂上成像时经历不同幅度复杂运动的尸体中进行了评估(Cios Spin 3D, Siemens Healthineers, Forchheim, Germany)。在使用临床固定室c型臂的临床前动物研究中进行了进一步评估(Artis Zee, Siemens Healthineers, Forchheim, Germany)。结果:在幻体研究中,该算法解决了强屈曲情况下颈椎的可见性,与无运动参考相比,将均方根误差降低了60%。在小、中、大的运动引起的变形中,在尸体的腹部CBCT成像中,明显减少了运动伪影(模糊、条纹和软组织边缘的丢失)。动物研究表明,扫描过程中肠道气体的复杂运动减少了条纹。结论:总体而言,这些研究证明了该算法对大范围的运动幅度、频率、数据源(即移动或固定房间的c型臂)以及真实(非模拟)实验数据(例如截断和分散)中的其他混杂因素的鲁棒性。这些临床前研究成功地证明了CBCT中运动伪影的减少,并支持将该方法转化为介入性身体放射学的临床研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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