Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA.
Int J Radiat Oncol Biol Phys. 2012 Apr 1;82(5):1584-93. doi: 10.1016/j.ijrobp.2011.02.002. Epub 2011 Apr 7.
To develop a three-dimensional (3D) cone-beam computed tomography (CBCT) estimation method using a deformation field map, and to evaluate and optimize the efficiency and accuracy of the method for use in the clinical setting.
We propose a method to estimate patient CBCT images using prior information and a deformation model. Patients' previous CBCT data are used as the prior information, and the new CBCT volume to be estimated is considered as a deformation of the prior image volume. The deformation field map is solved by minimizing deformation energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. This method was implemented in 3D form using hardware acceleration and multi-resolution scheme, and it was evaluated for different scan angles, projection numbers, and scan directions using liver, lung, and prostate cancer patient data. The accuracy of the estimation was evaluated by comparing the organ volume difference and the similarity between estimated CBCT and the CBCT reconstructed from fully sampled projections.
Results showed that scan direction and number of projections do not have significant effects on the CBCT estimation accuracy. The total scan angle is the dominant factor affecting the accuracy of the CBCT estimation algorithm. Larger scan angles yield better estimation accuracy than smaller scan angles. Lung cancer patient data showed that the estimation error of the 3D lung tumor volume was reduced from 13.3% to 4.3% when the scan angle was increased from 60° to 360° using 57 projections.
The proposed estimation method is applicable for 3D DTS, 3D CBCT, four-dimensional CBCT, and four-dimensional DTS image estimation. This method has the potential for significantly reducing the imaging dose and improving the image quality by removing the organ distortion artifacts and streak artifacts shown in images reconstructed by the conventional Feldkamp-Davis-Kress (FDK) algorithm.
开发一种基于变形场图的三维（3D）锥形束计算机断层摄影术（CBCT）估计方法，并评估和优化该方法在临床环境中的效率和准确性。
我们提出了一种使用先验信息和变形模型来估计患者 CBCT 图像的方法。患者的先前 CBCT 数据用作先验信息，而要估计的新 CBCT 体积被视为先验图像体积的变形。通过最小化变形能并使用非线性共轭梯度法保持新投影数据的保真度来求解变形场图。该方法以 3D 形式实现，使用硬件加速和多分辨率方案，并使用肝、肺和前列腺癌患者数据评估不同扫描角度、投影数量和扫描方向的性能。通过比较器官体积差异和估计的 CBCT 与完全采样投影重建的 CBCT 之间的相似性来评估估计的准确性。
结果表明，扫描方向和投影数量对 CBCT 估计准确性没有显著影响。总扫描角度是影响 CBCT 估计算法准确性的主要因素。较大的扫描角度比较小的扫描角度产生更好的估计准确性。肺癌患者数据表明，当使用 57 个投影将扫描角度从 60°增加到 360°时，3D 肺肿瘤体积的估计误差从 13.3%降低到 4.3%。
所提出的估计方法适用于 3D DTS、3D CBCT、四维 CBCT 和四维 DTS 图像估计。该方法通过去除传统 Feldkamp-Davis-Kress（FDK）算法重建图像中显示的器官变形伪影和条纹伪影，有可能显著降低成像剂量并提高图像质量。
