Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia.
Int J Radiat Oncol Biol Phys. 2015 Mar 15;91(4):849-56. doi: 10.1016/j.ijrobp.2014.12.027.
Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations.
The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR. Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases.
The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases.
Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.
计算机断层扫描（CT）伪影会严重降低质子治疗中的剂量计算精度。由于磁共振成像（MRI）在放射治疗临床中的应用日益普及，我们开发了一种基于 MRI 的 CT 伪影校正方法，以提高质子射程计算的准确性。
该方法通过将附近无伪影的切片的 CT 亨氏单位（HU 数）映射到受污染的 CT 数据，使用配准的 MRI 来替换损坏的 CT 数据。使用三维（3D）变形图像配准（DIR）对 MRI 和 CT 容积图像进行配准。通过使用 2D DIR 在切片基础上对配准进行微调。基于配对 MRI 像素值和无伪影切片的 HU 的强度，我们进行了全面分析，以预测受污染区域的正确 HU。为了进行概念验证，我们在参考数据集上模拟了金属伪影。使用参考、伪影和校正图像计算质子射程，以量化质子射程误差的减少。该校正方法应用于 4 个独特的临床病例。
校正方法在定量和定性方面都显著减少了伪影。在各自的模拟脑和头颈部 CT 图像上，校正后平均误差从 495HU 和 370HU 分别减少到 108HU 和 92HU。相应地，在两种情况下，2.4cm 和 1.7cm 的绝对平均质子射程误差都减少到小于 2mm。
我们基于 MRI 的 CT 伪影校正方法可以提高有严重 CT 伪影的患者的 CT 图像质量和质子射程计算准确性。
