School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
Med Phys. 2019 Aug;46(8):3627-3639. doi: 10.1002/mp.13595. Epub 2019 Jun 17.
To develop and evaluate a method of reconstructing a patient- and treatment day- specific volumetric image and motion model from free-breathing cone-beam projections and respiratory surrogate measurements. This Motion-Compensated Simultaneous Algebraic Reconstruction Technique (MC-SART) generates and uses a motion model derived directly from the cone-beam projections, without requiring prior motion measurements from 4DCT, and can compensate for both inter- and intrabin deformations. The motion model can be used to generate images at arbitrary breathing points, which can be used for estimating volumetric images during treatment delivery.
The MC-SART was formulated using simultaneous image reconstruction and motion model estimation. For image reconstruction, projections were first binned according to external surrogate measurements. Projections in each bin were used to reconstruct a set of volumetric images using MC-SART. The motion model was estimated based on deformable image registration between the reconstructed bins, and least squares fitting to model parameters. The model was used to compensate for motion in both projection and backprojection operations in the subsequent image reconstruction iterations. These updated images were then used to update the motion model, and the two steps were alternated between. The final output is a volumetric reference image and a motion model that can be used to generate images at any other time point from surrogate measurements.
A retrospective patient dataset consisting of eight lung cancer patients was used to evaluate the method. The absolute intensity differences in the lung regions compared to ground truth were 50.8 ± 43.9 HU in peak exhale phases (reference) and 80.8 ± 74.0 in peak inhale phases (generated). The 50th percentile of voxel registration error of all voxels in the lung regions with >5 mm amplitude was 1.3 mm. The MC-SART was also applied to measured patient cone-beam projections acquired with a linac-mounted CBCT system. Results from this patient data demonstrate the feasibility of MC-SART and showed qualitative image quality improvements compared to other state-of-the-art algorithms.
We have developed a simultaneous image reconstruction and motion model estimation method that uses Cone-beam computed tomography (CBCT) projections and respiratory surrogate measurements to reconstruct a high-quality reference image and motion model of a patient in treatment position. The method provided superior performance in both HU accuracy and positional accuracy compared to other existing methods. The resultant reference image and motion model can be combined with respiratory surrogate measurements to generate volumetric images representing patient anatomy at arbitrary time points.
开发并评估一种从自由呼吸锥形束投影和呼吸替代测量中重建患者和治疗日特定容积图像和运动模型的方法。这种运动补偿同时代数重建技术（MC-SART）直接从锥形束投影中生成和使用运动模型，而无需从 4DCT 获得先前的运动测量，并且可以补偿内外束变形。运动模型可用于在任意呼吸点生成图像，可用于在治疗过程中估计容积图像。
MC-SART 通过同时进行图像重建和运动模型估计来构建。对于图像重建，首先根据外部替代测量对投影进行分组。在每个 bin 中，使用投影重建一组容积图像。基于重建 bin 之间的可变形图像配准，根据最小二乘法拟合模型参数来估计运动模型。该模型用于在后续图像重建迭代的投影和反向投影操作中补偿运动。然后使用这些更新的图像来更新运动模型，并在这两个步骤之间交替。最终的输出是一个容积参考图像和一个运动模型，该模型可用于从替代测量中生成任何其他时间点的图像。
使用包含 8 名肺癌患者的回顾性患者数据集来评估该方法。与真实参考相比，在呼气峰值阶段（参考）肺区的绝对强度差异为 50.8±43.9 HU，在吸气峰值阶段（生成）为 80.8±74.0 HU。在肺区具有 >5 mm 幅度的所有体素中，体素配准误差的第 50 百分位数为 1.3 mm。MC-SART 还应用于带有 LINAC 安装的 CBCT 系统采集的测量患者锥形束投影。该患者数据的结果证明了 MC-SART 的可行性，并与其他最先进的算法相比，显示出定性图像质量的改善。
我们开发了一种同时进行图像重建和运动模型估计的方法，该方法使用锥形束计算机断层扫描（CBCT）投影和呼吸替代测量来重建治疗位置患者的高质量参考图像和运动模型。该方法在 HU 精度和位置精度方面均优于其他现有方法。生成的参考图像和运动模型可与呼吸替代测量相结合，生成代表任意时间点患者解剖结构的容积图像。
