Wellington Blood and Cancer Centre, Department of Radiation Oncology, Wellington, New Zealand; University of Canterbury, School of Physical and Chemical Sciences, Christchurch, New Zealand.
University of Canterbury, School of Physical and Chemical Sciences, Christchurch, New Zealand.
Radiother Oncol. 2020 Feb;143:117-125. doi: 10.1016/j.radonc.2019.12.009. Epub 2020 Feb 14.
Deformable image registration (DIR) facilitated dose reconstruction and accumulation can be applied to assess delivered dose and verify the validity of the treatment plan during treatment. This retrospective study used in silico deformations based on clinically observed anatomical changes as ground truth to investigate the uncertainty of reconstructed and accumulated dose in head-and-neck radiotherapy (HNRT).
A planning CT (pCT), cone beam CT (CBCT) from week one of treatment and three later CBCTs were selected for 12 HNRT patients. These images were used to generate in silico reference CBCTs and deformation vector fields (DVFs) as ground truth with B-spline DIR. Inverse consistency (IC) of voxels was assessed by determining their net displacement after successive application of the forward and backward DVF. The reconstructed dose based on demons DIR was compared to the ground truth to assess the structure-specific uncertainties of this DIR algorithm for inverse consistent and inverse inconsistent voxels.
Overall, 98.5% of voxels were inverse consistent with the 95% level of confidence range for dose reconstruction of a single fraction equal to [-2.3%; +2.1%], [-10.2%; +15.2%] and [-9.5%; +12.5%] relative to their planned dose for target structures, critical organs at risk (OARs) and non-critical OARs, respectively. Inverse inconsistent voxels generally showed a higher level of uncertainty.
The uncertainty in accumulated dose using DIR can be accurately quantified and incorporated in dose-volume histograms (DVHs). This method can be used to prospectively assess the adequacy of target coverage during treatment in an objective manner.
可变形图像配准（DIR）有助于剂量重建和积累，可用于评估已施剂量并在治疗过程中验证治疗计划的有效性。本回顾性研究使用基于临床观察到的解剖学变化的仿真变形作为金标准，以研究头颈部放疗（HNRT）中重建和积累剂量的不确定性。
为 12 名 HNRT 患者选择了计划 CT（pCT）、治疗第一周的锥形束 CT（CBCT）和之后的三个 CBCT。这些图像用于生成基于 B 样条 DIR 的仿真参考 CBCT 和变形矢量场（DVF）作为金标准。通过确定正向和反向 DVF 连续应用后的净位移来评估体素的反向一致性（IC）。根据 demons DIR 重建的剂量与金标准进行比较，以评估该 DIR 算法对反向一致和反向不一致体素的结构特异性不确定性。
总体而言，98.5%的体素在剂量重建的单个分数中具有反向一致性，置信区间范围为 95%，对于靶结构、关键危及器官（OAR）和非关键 OAR，其分别为[-2.3%；+2.1%]、[-10.2%；+15.2%]和[-9.5%；+12.5%]。反向不一致的体素通常显示出更高水平的不确定性。
使用 DIR 累积剂量的不确定性可以准确量化并纳入剂量体积直方图（DVHs）中。该方法可用于前瞻性地以客观的方式评估治疗期间靶区覆盖的充分性。
