Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA.
Med Phys. 2011 Oct;38(10):5530-8. doi: 10.1118/1.3637501.
As a counterpart of 4DCT in the treatment planning stage of radiotherapy treatment, 4D cone beam computed tomography (4DCBCT) method has been proposed to verify tumor motion trajectories before radiation therapy treatment delivery. Besides 4DCBCT acquisition using slower gantry rotation speed or multiple rotations, a new method using the prior image constrained compressed sensing (PICCS) image reconstruction method and the standard 1-min data acquisition were proposed. In this paper, the PICCS-4DCBCT method was combined with deformable registration to validate its capability in motion trajectory extraction using physical phantom data, simulated human subject data from 4DCT and in vivo human subject data.
Two methods were used to validate PICCS-4DCBCT for the purpose of respiratory motion delineation. The standard 1-min gantry rotation Cone Beam CT acquisition was used for both methods. In the first method, 4DCBCT projection data of a physical motion phantom were acquired using an on-board CBCT acquisition system (Varian Medical Systems, Palo Alto, CA). Using a deformable registration method, the object motion trajectories were extracted from both FBP and PICCS reconstructed 4DCBCT images, and compared against the programmed motion trajectories. In the second method, using a clinical 4DCT dataset, Cone Beam CT projections were simulated by forward projection. Using a deformable registration method, the tumor motion trajectories were extracted from the reconstructed 4DCT and PICCS-4DCBCT images. The performance of PICCS-4DCBCT is assessed against the 4DCT ground truth. The breathing period was varied in the simulation to study its effect on motion extraction. For both validation methods, the root mean square error (RMSE) and the maximum of the errors (MaxE) were used to quantify the accuracy of the extracted motion trajectories. After the validation, a clinical dataset was used to demonstrate the motion delineation capability of PICCS-4DCBCT for human subjects.
In both validation studies, the RMSEs of the extracted motion trajectories from PICCS-4DCBCT images are less than 0.7 mm, and their MaxEs are less than 1 mm, for all three directions. In comparison, FBP-4DCBCT shows considerably larger RMSEs in the physical phantom based validation. PICCS-4DCBCT also shows insensitivity to the breathing period in the 4DCT based validation. For the in vivo human subject study, high quality 3D motion trajectory of the tumor was obtained from PICCS-4DCBCT images and showed consistency with visual observation.
These results demonstrate accurate delineation of tumor motion trajectory can be achieved using PICCS-4DCBCT and the standard 1-min data acquisition.
作为放射治疗计划阶段 4DCT 的对应物，4D 锥形束计算机断层扫描（4DCBCT）方法已被提出用于在放射治疗治疗前验证肿瘤运动轨迹。除了使用较慢的机架旋转速度或多次旋转进行 4DCBCT 采集之外，还提出了一种使用先前图像约束压缩感知（PICCS）图像重建方法和标准 1 分钟数据采集的新方法。在本文中，将 PICCS-4DCBCT 方法与可变形配准相结合，以验证其使用物理体模数据、来自 4DCT 的模拟人体数据和体内人体数据提取运动轨迹的能力。
使用两种方法验证 PICCS-4DCBCT 用于呼吸运动描绘的目的。这两种方法都使用标准的 1 分钟机架旋转锥形束 CT 采集。在第一种方法中，使用机载 CBCT 采集系统（加利福尼亚州帕洛阿尔托的瓦里安医疗系统）获取物理运动体模的 4DCBCT 投影数据。使用可变形配准方法，从 FBP 和 PICCS 重建的 4DCBCT 图像中提取物体运动轨迹，并与编程运动轨迹进行比较。在第二种方法中，通过正向投影模拟临床 4DCT 数据集的锥形束 CT 投影。使用可变形配准方法，从重建的 4DCT 和 PICCS-4DCBCT 图像中提取肿瘤运动轨迹。根据 4DCT 地面实况评估 PICCS-4DCBCT 的性能。在模拟中改变呼吸周期以研究其对运动提取的影响。对于这两种验证方法，使用均方根误差（RMSE）和误差最大值（MaxE）来量化提取运动轨迹的准确性。验证后，使用临床数据集演示 PICCS-4DCBCT 对人体的运动描绘能力。
在这两种验证研究中，从 PICCS-4DCBCT 图像中提取的运动轨迹的 RMSE 均小于 0.7mm，其 MaxE 均小于 1mm，所有三个方向均如此。相比之下，基于物理体模的验证中，FBP-4DCBCT 的 RMSE 要大得多。PICCS-4DCBCT 在基于 4DCT 的验证中也对呼吸周期不敏感。对于体内人体研究，从 PICCS-4DCBCT 图像中获得了高质量的肿瘤 3D 运动轨迹，并与视觉观察一致。
这些结果表明，使用 PICCS-4DCBCT 和标准的 1 分钟数据采集可以实现肿瘤运动轨迹的准确描绘。
