UCLA, Department of Radiation Oncology, Los Angeles, CA, United States of America.
Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Department of Radiation Oncology, Boston, MA, United States of America.
Phys Med Biol. 2024 Mar 26;69(7). doi: 10.1088/1361-6560/ad311b.
. To combat the motion artifacts present in traditional 4D-CBCT reconstruction, an iterative technique known as the motion-compensated simultaneous algebraic reconstruction technique (MC-SART) was previously developed. MC-SART employs a 4D-CBCT reconstruction to obtain an initial model, which suffers from a lack of sufficient projections in each bin. The purpose of this study is to demonstrate the feasibility of introducing a motion model acquired during CT simulation to MC-SART, coined model-based CBCT (MB-CBCT).. For each of 5 patients, we acquired 5DCTs during simulation and pre-treatment CBCTs with a simultaneous breathing surrogate. We cross-calibrated the 5DCT and CBCT breathing waveforms by matching the diaphragms and employed the 5DCT motion model parameters for MC-SART. We introduced the Amplitude Reassignment Motion Modeling technique, which measures the ability of the model to control diaphragm sharpness by reassigning projection amplitudes with varying resolution. We evaluated the sharpness of tumors and compared them between MB-CBCT and 4D-CBCT. We quantified sharpness by fitting an error function across anatomical boundaries. Furthermore, we compared our MB-CBCT approach to the traditional MC-SART approach. We evaluated MB-CBCT's robustness over time by reconstructing multiple fractions for each patient and measuring consistency in tumor centroid locations between 4D-CBCT and MB-CBCT.. We found that the diaphragm sharpness rose consistently with increasing amplitude resolution for 4/5 patients. We observed consistently high image quality across multiple fractions, and observed stable tumor centroids with an average 0.74 ± 0.31 mm difference between the 4D-CBCT and MB-CBCT. Overall, vast improvements over 3D-CBCT and 4D-CBCT were demonstrated by our MB-CBCT technique in terms of both diaphragm sharpness and overall image quality.. This work is an important extension of the MC-SART technique. We demonstrated the ability of5DCT models to provide motion compensation for CBCT reconstruction. We showed improvements in image quality over both 4D-CBCT and the traditional MC-SART approach.
为了克服传统 4D-CBCT 重建中存在的运动伪影，先前开发了一种称为运动补偿同时代数重建技术（MC-SART）的迭代技术。MC-SART 使用 4D-CBCT 重建来获得初始模型，但该模型在每个 bin 中缺乏足够的投影。本研究的目的是证明将在 CT 模拟期间获得的运动模型引入 MC-SART 的可行性，该模型称为基于模型的 CBCT（MB-CBCT）。对于 5 名患者中的每一名，我们在模拟期间和治疗前采集了 5DCT 和带同步呼吸替代物的 CBCT。我们通过匹配横膈膜来对 5DCT 和 CBCT 呼吸波进行交叉校准，并为 MC-SART 使用 5DCT 运动模型参数。我们引入了幅度重新分配运动建模技术，该技术通过以不同的分辨率重新分配投影幅度来测量模型控制横膈膜锐度的能力。我们评估了肿瘤的锐度，并将其与 MB-CBCT 和 4D-CBCT 进行了比较。我们通过在解剖边界上拟合误差函数来量化锐度。此外，我们将我们的 MB-CBCT 方法与传统的 MC-SART 方法进行了比较。我们通过为每位患者重建多个部分并测量 4D-CBCT 和 MB-CBCT 之间肿瘤质心位置的一致性，来评估 MB-CBCT 随时间的稳健性。我们发现对于 4/5 名患者，随着幅度分辨率的增加，横膈膜锐度持续上升。我们在多个部分中观察到一致的高质量图像，并观察到肿瘤质心稳定，4D-CBCT 和 MB-CBCT 之间的平均差异为 0.74±0.31mm。总的来说，我们的 MB-CBCT 技术在横膈膜锐度和整体图像质量方面都显著优于 3D-CBCT 和 4D-CBCT。
这项工作是 MC-SART 技术的重要扩展。我们证明了 5DCT 模型能够为 CBCT 重建提供运动补偿。我们显示了图像质量的改善，无论是与 4D-CBCT 还是传统的 MC-SART 方法相比都有所提高。
