Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria; Research center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom.
Z Med Phys. 2024 Nov;34(4):565-579. doi: 10.1016/j.zemedi.2023.02.001. Epub 2023 Mar 25.
Precise instrument placement plays a critical role in all interventional procedures, especially percutaneous procedures such as needle biopsies, to achieve successful tumor targeting and increased diagnostic accuracy. C-arm cone beam computed tomography (CBCT) has the potential to precisely visualize the anatomy in direct vicinity of the needle and evaluate the adequacy of needle placement during the intervention, allowing for instantaneous adjustment in case of misplacement. However, even with the most advanced C-arm CBCT devices, it can be difficult to identify the exact needle position on CBCT images due to the strong metal artifacts around the needle. In this study, we proposed a framework for customized trajectory design in CBCT imaging based on Prior Image Constrained Compressed Sensing (PICCS) reconstruction with the goal of reducing metal artifacts in needle-based procedures. We proposed to optimize out-of-plane rotations in three-dimensional (3D) space and minimize projection views while reducing metal artifacts at specific volume of interests (VOIs). An anthropomorphic thorax phantom with a needle inserted inside and two tumor models as the imaging targets were used to validate the proposed approach. The performance of the proposed approach was also evaluated for CBCT imaging under kinematic constraints by simulating some collision areas on the geometry of the C-arm. We compared the result of optimized 3D trajectories using the PICCS algorithm and 20 projections with the result of a circular trajectory with sparse view using PICCS and Feldkamp, Davis, and Kress (FDK), both using 20 projections, and the circular FDK method with 313 projections. For imaging targets 1 and 2, the highest values of structural similarity index measure (SSIM) and universal quality index (UQI) between the reconstructed image from the optimized trajectories and the initial CBCT image at the VOI was calculated 0.7521, 0.7308 and 0.7308, 0.7248 respectively. These results significantly outperformed the FDK method (with 20 and 313 projections) and the PICCS method (20 projections) both using the circular trajectory. Our results showed that the proposed optimized trajectories not only significantly reduce metal artifacts but also suggest a dose reduction for needle-based CBCT interventions, considering the small number of projections used. Furthermore, our results showed that the optimized trajectories are compatible with spatially constrained situations and enable CBCT imaging under kinematic constraints when the standard circular trajectory is not feasible.
精确的器械定位在所有介入性操作中起着至关重要的作用，特别是在经皮操作中，如针活检，以实现成功的肿瘤靶向和提高诊断准确性。C 臂锥形束 CT（CBCT）具有精确显示针附近解剖结构的潜力，并在介入过程中评估针放置的充分性，以便在放置错误时立即进行调整。然而，即使使用最先进的 C 臂 CBCT 设备，由于针周围的强烈金属伪影，也很难在 CBCT 图像上准确识别针的位置。在这项研究中，我们提出了一种基于先验图像约束压缩感知（PICCS）重建的 CBCT 成像中定制轨迹设计的框架，旨在减少针基手术中的金属伪影。我们建议优化三维（3D）空间中的面外旋转，并在特定感兴趣体积（VOI）处最小化投影视图，同时减少金属伪影。使用一个内置针的模拟人体胸部体模和两个成像目标的肿瘤模型来验证所提出的方法。还通过模拟 C 臂几何形状上的一些碰撞区域，评估了该方法在运动学约束下的 CBCT 成像性能。我们比较了使用 PICCS 算法和 20 个投影的优化 3D 轨迹的结果与使用 PICCS 和 Feldkamp、Davis 和 Kress（FDK）的稀疏视图圆形轨迹的结果，这两种方法都使用 20 个投影，以及具有 313 个投影的圆形 FDK 方法。对于成像目标 1 和 2，在 VOI 处从优化轨迹重建的图像与初始 CBCT 图像之间计算的结构相似性指数测量（SSIM）和通用质量指数（UQI）的最高值分别为 0.7521、0.7308 和 0.7308、0.7248。这些结果明显优于 FDK 方法（使用 20 个和 313 个投影）和 PICCS 方法（使用 20 个投影）的圆形轨迹。我们的结果表明，所提出的优化轨迹不仅可以显著减少金属伪影，而且还可以考虑到使用的投影数量较少，从而为针基 CBCT 干预减少剂量。此外，我们的结果表明，当标准的圆形轨迹不可行时，优化轨迹与空间约束情况兼容，并能够在运动学约束下进行 CBCT 成像。
