Vickress Jason, Battista Jerry, Barnett Rob, Yartsev Slav
Department of Medical Biophysics, University of Western Ontario, London, ON, Canada.
Phys Med Biol. 2017 Aug 11;62(17):N391-N403. doi: 10.1088/1361-6560/aa8133.
Deformable image registration (DIR) is emerging as a tool in radiation therapy for calculating the cumulative dose distribution across multiple fractions of treatment. Unfortunately, due to the variable nature of DIR algorithms and dependence of performance on image quality, registration errors can result in dose accumulation errors. In this study, landmarked images were used to characterize the DIR error throughout an image space and determine its impact on dosimetric analysis. Ten thoracic 4DCT images with 300 landmarks per image study matching the end-inspiration and end-expiration phases were obtained from 'dir-labs'. DIR was performed using commercial software MIM Maestro. The range of dose uncertainty (RDU) was calculated at each landmark pair as the maximum and minimum of the doses within a sphere around the landmark in the end-expiration phase. The radius of the sphere was defined by a measure of DIR error which included either the actual DIR error, mean DIR error per study, constant errors of 2 or 5 mm, inverse consistency error, transitivity error or the distance discordance metric (DDM). The RDUs were evaluated using the magnitude of dose uncertainty (MDU) and inclusion rate (IR) of actual error lying within the predicted RDU. The RDU was calculated for 300 landmark pairs on each 4DCT study for all measures of DIR error. The most representative RDU was determined using the actual DIR error with a MDU of 2.5 Gy and IR of 97%. Across all other measures of DIR error, the DDM was most predictive with a MDU of 2.5 Gy and IR of 86%, closest to the actual DIR error. The proposed method represents the range of dosimetric uncertainty of DIR error using either landmarks at specific voxels or measures of registration accuracy throughout the volume.
可变形图像配准（DIR）正在成为放射治疗中的一种工具，用于计算多疗程治疗的累积剂量分布。不幸的是，由于DIR算法的可变性质以及性能对图像质量的依赖性，配准误差可能导致剂量累积误差。在本研究中，使用地标图像来表征整个图像空间中的DIR误差，并确定其对剂量分析的影响。从“dir-labs”获得了10幅胸部4DCT图像，每幅图像研究有300个地标，匹配吸气末和呼气末阶段。使用商业软件MIM Maestro进行DIR。在每个地标对处计算剂量不确定性范围（RDU），作为呼气末阶段地标周围球体范围内剂量的最大值和最小值。球体半径由DIR误差的度量定义，该度量包括实际DIR误差、每项研究的平均DIR误差、2或5毫米的恒定误差、逆一致性误差、传递性误差或距离不一致度量（DDM）。使用预测RDU内实际误差的剂量不确定性大小（MDU）和包含率（IR）来评估RDU。针对所有DIR误差度量，在每项四维CT研究的300个地标对上计算RDU。使用实际DIR误差确定最具代表性的RDU，MDU为2.5 Gy，IR为97%。在所有其他DIR误差度量中，DDM的预测性最强，MDU为2.5 Gy，IR为86%，最接近实际DIR误差。所提出的方法使用特定体素处的地标或整个体积的配准精度度量来表示DIR误差的剂量不确定性范围。
