Purpose

This study aimed to evaluate the accuracy of deformable image registration (DIR) algorithms using data sets with different levels of ground-truth deformation vector fields (DVFs) and to investigate the correlation between DVF errors and contour-based metrics.

Methods and Materials

Nine pairs of digital data sets were generated through contour-controlled deformations based on 3 anonymized patients’ CTs (head and neck, thorax/abdomen, and pelvis) with low, medium, and high deformation intensity for each site using the ImSimQA software. Image pairs and their associated contours were imported to MIM-Maestro, Raystation, and Velocity systems, followed by DIR and contour propagation. The system-generated DVF and propagated contours were compared with the ground-truth data. The correlation between DVF errors and contour-based metrics was evaluated using the Pearson correlation coefficient (r), while their correlation with volumes were calculated using Spearman correlation coefficient (rho).

Results

The DVF errors increased with increasing deformation intensity. All DIR algorithms performed well for esophagus, trachea, left femoral, right femoral, and urethral (mean and maximum DVF errors <2.50 mm and <4.27 mm, respectively; Dice similarity coefficient: 0.93-0.99). Brain, liver, left lung, and bladder showed large DVF errors for all 3 systems (d_max: 2.8-91.90 mm). The minimum and maximum DVF errors, conformity index, and Dice similarity coefficient were correlated with volumes (|rho|: 0.41-0.64), especially for very large or small structures (|rho|: 0.64-0.80). Only mean distance to agreement of Raystation and Velocity correlated with some indices of DVF errors (r: 0.70-0.78).

Conclusions

Most contour-based metrics had no correlation with DVF errors. For adaptive radiation therapy, well-performed contour propagation does not directly indicate accurate dose deformation and summation/accumulation within each contour (determined by DVF accuracy). Tolerance values for DVF errors should vary as the acceptable accuracy for overall adaptive radiation therapy depends on anatomic site, deformation intensity, organ size, and so forth. This study provides benchmark tables for evaluating DIR accuracy in various clinical scenarios.

中文翻译：

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使用具有真实变形矢量场的数字数据集对多个解剖部位的可变形图像配准进行基准测试

目的

本研究旨在使用具有不同水平真实变形矢量场 (DVF) 的数据集评估可变形图像配准 (DIR) 算法的准确性，并研究 DVF 误差与基于轮廓的指标之间的相关性。

方法和材料

使用 ImSimQA 软件，根据 3 个匿名患者的 CT（头颈部、胸部/腹部和骨盆），每个部位的低、中和高变形强度，通过轮廓控制变形生成 9 对数字数据集。图像对及其相关轮廓被导入 MIM-Maestro、Raystation 和 Velocity 系统，然后是 DIR 和轮廓传播。系统生成的 DVF 和传播的轮廓与地面实况数据进行了比较。DVF 误差与基于轮廓的指标之间的相关性使用 Pearson 相关系数 ( r )进行评估，而它们与体积的相关性使用 Spearman 相关系数 ( rho ) 计算。

结果

DVF 误差随着变形强度的增加而增加。所有 DIR 算法对食道、气管、左股骨、右股骨和尿道均表现良好（平均和最大 DVF 误差分别<2.50 mm 和 <4.27 mm；Dice 相似系数：0.93-0.99）。大脑、肝脏、左肺和膀胱在所有 3 个系统中都显示出较大的 DVF 误差（d _max：2.8-91.90 mm）。最小和最大 DVF 误差、一致性指数和 Dice 相似系数与体积相关 ( |rho|: 0.41-0.64)，特别是对于非常大或非常小的结构 ( |rho|: 0.64-0.80)。只有与 Raystation 和 Velocity 一致的平均距离与某些 DVF 误差指数相关（r： 0.70-0.78）。

结论

大多数基于轮廓的指标与 DVF 错误无关。对于自适应放射治疗，执行良好的轮廓传播并不直接表明每个轮廓内的准确剂量变形和总和/累积（由 DVF 精度确定）。DVF 误差的容差值应有所不同，因为整体自适应放射治疗的可接受精度取决于解剖部位、变形强度、器官大小等。本研究提供了用于在各种临床情况下评估 DIR 准确性的基准表。