Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298, USA.
Med Phys. 2010 Dec;37(12):6212-20. doi: 10.1118/1.3515460.
To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set.
A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set. A parametrized deformation model is applied to the source FBCT image, digitally reconstructed radiographs (DRRs) that emulate the CBCT projection image geometry are calculated and compared to the target CBCT projection data, and the deformation model parameters are adjusted iteratively until the DRRs optimally match the CBCT projection data set. The resulting deformed FBCT image is hypothesized to be an accurate representation of the patient's anatomy imaged by the CBCT system. The process is demonstrated via numerical simulation. A known deformation is applied to a prior FBCT image and used to create a synthetic set of CBCT target projections. The iterative projection matching process is then applied to reconstruct the deformation represented in the synthetic target projections; the reconstructed deformation is then compared to the known deformation. The sensitivity of the process to the number of projections and the DRR/CBCT projection mismatch is explored by systematically adding noise to and perturbing the contrast of the target projections relative to the iterated source DRRs and by reducing the number of projections.
When there is no noise or contrast mismatch in the CBCT projection images, a set of 64 projections allows the known deformed CT image to be reconstructed to within a nRMS error of 1% and the known deformation to within a nRMS error of 7%. A CT image nRMS error of less than 4% is maintained at noise levels up to 3% of the mean projection intensity, at which the deformation error is 13%. At 1% noise level, the number of projections can be reduced to 8 while maintaining CT image and deformation errors of less than 4% and 13%, respectively. The method is sensitive to contrast mismatch between the simulated projections and the target projections when the soft-tissue contrast in the projections is low.
By using prior knowledge available in a FBCT image, the authors show that a CBCT image can be iteratively reconstructed from a comparatively small number of projection images, thus saving acquisition time and reducing imaging dose. This will enable more frequent daily imaging during radiation therapy. Because the process preserves the CT numbers of the FBCT image, the resulting 3D image intensities will be more accurate than a CBCT image reconstructed via conventional backprojection methods. Reconstruction errors are insensitive to noise at levels beyond what would typically be found in CBCT projection data, but are sensitive to contrast mismatch errors between the CBCT projection data and the DRRs.
通过使先前的扇形束 CT(FBCT)图像变形,以匹配 CBCT 投影数据集所描绘的解剖结构,从而演示重建锥束 CT(CBCT)图像的可行性。
假设患者的先前 FBCT 图像可用作源图像。获取 CBCT 投影数据集,并将其用作目标图像集。将参数化变形模型应用于源 FBCT 图像,计算模拟 CBCT 投影图像几何形状的数字重建射线照片(DRR),并将其与目标 CBCT 投影数据进行比较,然后迭代调整变形模型参数,直到 DRR 最佳匹配 CBCT 投影数据集。假设所得变形 FBCT 图像是 CBCT 系统成像的患者解剖结构的准确表示。通过数值模拟演示该过程。将已知变形应用于先前的 FBCT 图像,并用于创建一组合成的 CBCT 目标投影。然后将迭代投影匹配过程应用于重建合成目标投影中表示的变形;将重建的变形与已知变形进行比较。通过系统地向目标投影添加噪声并相对于迭代源 DRR 扰动对比度,以及通过减少投影数量,探索该过程对投影数量和 DRR/CBCT 投影失配的敏感性。
当 CBCT 投影图像中没有噪声或对比度失配时,一组 64 个投影可以将已知变形的 CT 图像重建到 nRMS 误差小于 1%,将已知变形重建到 nRMS 误差小于 7%。在投影强度平均值的 3%噪声水平下,可以保持小于 4%的 CT 图像 nRMS 误差,在 1%噪声水平下,变形误差为 13%。当投影中的软组织对比度较低时,该方法对模拟投影与目标投影之间的对比度失配敏感。
通过使用 FBCT 图像中的先验知识,作者表明可以从相对较少数量的投影图像中迭代重建 CBCT 图像,从而节省采集时间并减少成像剂量。这将使在放射治疗期间能够更频繁地进行日常成像。由于该过程保留了 FBCT 图像的 CT 值,因此生成的 3D 图像强度将比通过传统反向投影方法重建的 CBCT 图像更准确。重建误差对噪声水平不敏感,噪声水平超过 CBCT 投影数据中通常发现的噪声水平,但对 CBCT 投影数据与 DRR 之间的对比度失配误差敏感。