Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California.
Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California.
Int J Radiat Oncol Biol Phys. 2015 Jun 1;92(2):415-22. doi: 10.1016/j.ijrobp.2015.01.033. Epub 2015 Apr 3.
The purpose of this study was to systematically monitor anatomic variations and their dosimetric consequences during intensity modulated radiation therapy (IMRT) for head and neck (H&N) cancer by using a graphics processing unit (GPU)-based deformable image registration (DIR) framework.
Eleven IMRT H&N patients undergoing IMRT with daily megavoltage computed tomography (CT) and weekly kilovoltage CT (kVCT) scans were included in this analysis. Pretreatment kVCTs were automatically registered with their corresponding planning CTs through a GPU-based DIR framework. The deformation of each contoured structure in the H&N region was computed to account for nonrigid change in the patient setup. The Jacobian determinant of the planning target volumes and the surrounding critical structures were used to quantify anatomical volume changes. The actual delivered dose was calculated accounting for the organ deformation. The dose distribution uncertainties due to registration errors were estimated using a landmark-based gamma evaluation.
Dramatic interfractional anatomic changes were observed. During the treatment course of 6 to 7 weeks, the parotid gland volumes changed up to 34.7%, and the center-of-mass displacement of the 2 parotid glands varied in the range of 0.9 to 8.8 mm. For the primary treatment volume, the cumulative minimum and mean and equivalent uniform doses assessed by the weekly kVCTs were lower than the planned doses by up to 14.9% (P=.14), 2% (P=.39), and 7.3% (P=.05), respectively. The cumulative mean doses were significantly higher than the planned dose for the left parotid (P=.03) and right parotid glands (P=.006). The computation including DIR and dose accumulation was ultrafast (∼45 seconds) with registration accuracy at the subvoxel level.
A systematic analysis of anatomic variations in the H&N region and their dosimetric consequences is critical in improving treatment efficacy. Nearly real-time assessment of anatomic and dosimetric variations is feasible using the GPU-based DIR framework. Clinical implementation of this technology may enable timely plan adaptation and improved outcome.
本研究旨在通过基于图形处理单元（GPU）的形变图像配准（DIR）框架，对行调强放疗（IMRT）的头颈部（H&N）癌症患者进行解剖结构变化及其剂量学影响的系统监测。
本研究纳入了 11 例接受 IMRT 治疗的 H&N 癌症患者，这些患者在治疗过程中每日行兆伏级 CT（MVCT）扫描，每周行千伏级 CT（kVCT）扫描。通过基于 GPU 的 DIR 框架，自动将预处理 kVCT 与相应的计划 CT 进行配准。计算 H&N 区域中每个勾画结构的变形，以考虑患者摆位的非刚性变化。通过计算计划靶区和周围危及器官的雅可比行列式来量化解剖体积的变化。考虑器官变形，计算实际的剂量分布。使用基于标记点的伽玛评估来估计因配准误差引起的剂量分布不确定性。
观察到明显的分次间解剖结构变化。在 6-7 周的治疗过程中，腮腺体积变化高达 34.7%，双侧腮腺的质心位移范围为 0.9-8.8mm。对于原发肿瘤体积，每周 kVCT 评估的累积最小剂量、平均剂量和等效均匀剂量分别比计划剂量低 14.9%（P=.14）、2%（P=.39）和 7.3%（P=.05）。左侧腮腺（P=.03）和右侧腮腺（P=.006）的累积平均剂量明显高于计划剂量。包括 DIR 和剂量累积的计算速度非常快（约 45 秒），配准精度达到亚像素水平。
对头颈部区域解剖结构变化及其剂量学影响进行系统分析对于提高治疗效果至关重要。使用基于 GPU 的 DIR 框架，几乎可以实时评估解剖结构和剂量变化。该技术的临床应用可能实现及时的计划调整和改善治疗效果。
