Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America.
Phys Med Biol. 2020 Aug 19;65(16):165012. doi: 10.1088/1361-6560/ab9454.
Metal artifacts present a challenge to cone-beam CT (CBCT) image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy-often in the very region of interest pertinent to the imaging/surgical tasks. We present a method to reduce the influence of metal artifacts by prospectively defining an image acquisition protocol-viz., the C-arm source-detector orbit-that mitigates metal-induced biases in the projection data. The metal artifact avoidance (MAA) method is compatible with simple mobile C-arms, does not require exact prior information on the patient or metal implants, and is consistent with 3D filtered backprojection (FBP), more advanced (e.g. polyenergetic) model-based image reconstruction (MBIR), and metal artifact reduction (MAR) post-processing methods. The MAA method consists of: (i) coarse localization of metal objects in the field-of-view (FOV) via two or more low-dose scout projection views and segmentation (e.g. a simple U-Net) in coarse backprojection; (ii) model-based prediction of metal-induced x-ray spectral shift for all source-detector vertices accessible by the imaging system (e.g. gantry rotation and tilt angles); and (iii) identification of a circular or non-circular orbit that reduces the variation in spectral shift. The method was developed, tested, and evaluated in a series of studies presenting increasing levels of complexity and realism, including digital simulations, phantom experiment, and cadaver experiment in the context of image-guided spine surgery (pedicle screw implants). The MAA method accurately predicted tilted circular and non-circular orbits that reduced the magnitude of metal artifacts in CBCT reconstructions. Realistic distributions of metal instrumentation were successfully localized (0.71 median Dice coefficient) from 2-6 low-dose scout views even in complex anatomical scenes. The MAA-predicted tilted circular orbits reduced root-mean-square error (RMSE) in 3D image reconstructions by 46%-70% and 'blooming' artifacts (apparent width of the screw shaft) by 20-45%. Non-circular orbits defined by MAA achieved a further ∼46% reduction in RMSE compared to the best (tilted) circular orbit. The MAA method presents a practical means to predict C-arm orbits that minimize spectral bias from metal instrumentation. Resulting orbits-either simple tilted circular orbits or more complex non-circular orbits that can be executed with a motorized multi-axis C-arm-exhibited substantial reduction of metal artifacts in raw CBCT reconstructions by virtue of higher fidelity projection data, which are in turn compatible with subsequent MAR post-processing and/or polyenergetic MBIR to further reduce artifacts.
金属伪影对锥形束 CT(CBCT)图像引导手术构成挑战,使金属器械和相邻解剖结构的可视化变得困难,而这些结构通常正是与成像/手术任务相关的关键区域。我们提出了一种通过前瞻性定义图像采集协议(即 C 臂源-探测器轨道)来减少金属伪影影响的方法,该协议可以减轻投影数据中金属引起的偏差。金属伪影回避(MAA)方法与简单的移动 C 臂兼容,不需要患者或金属植入物的精确先验信息,并且与 3D 滤波反投影(FBP)、更先进的(例如多能)基于模型的图像重建(MBIR)和金属伪影减少(MAR)后处理方法一致。MAA 方法包括:(i)通过两个或更多低剂量的扫描投影视图和粗反投影中的分割(例如简单的 U-Net)粗略定位视野(FOV)中的金属物体;(ii)针对成像系统可访问的所有源-探测器顶点,预测金属引起的 X 射线光谱偏移的基于模型的方法(例如,龙门旋转和倾斜角度);(iii)确定一个圆形或非圆形轨道,以减少光谱偏移的变化。该方法在一系列呈现出越来越复杂和现实的研究中得到了开发、测试和评估,包括数字模拟、体模实验和在脊柱手术图像引导(椎弓根螺钉植入物)背景下的尸体实验。MAA 方法准确地预测了倾斜的圆形和非圆形轨道,减少了 CBCT 重建中金属伪影的幅度。即使在复杂的解剖场景中,也可以从 2-6 个低剂量的扫描视图中成功定位(0.71 中位数 Dice 系数)金属器械的逼真分布。MAA 预测的倾斜圆形轨道将 3D 图像重建中的均方根误差(RMSE)降低了 46%-70%,并将“blooming”伪影(螺钉轴的表观宽度)降低了 20-45%。与最佳(倾斜)圆形轨道相比,MAA 定义的非圆形轨道进一步将 RMSE 降低了约 46%。MAA 方法提供了一种实用的方法来预测 C 臂轨道,以最大限度地减少金属器械引起的光谱偏差。由此产生的轨道——无论是简单的倾斜圆形轨道还是更复杂的非圆形轨道,都可以通过电动多轴 C 臂来执行——由于投影数据的保真度更高,从而在原始 CBCT 重建中大大减少了金属伪影,这反过来又与后续的 MAR 后处理和/或多能 MBIR 兼容,以进一步减少伪影。