Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka, Japan.
Department of Radiation Oncology, NTT West Osaka Hospital, Osaka, Japan.
Int J Radiat Oncol Biol Phys. 2015 Jul 15;92(4):779-86. doi: 10.1016/j.ijrobp.2015.02.041. Epub 2015 Apr 28.
To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP).
Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates.
The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03-.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important.
RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.
提出一种基于伽马指数的剂量评估指标,该指标整合了肿瘤控制(TCP)和正常组织并发症概率(NTCP)的放射生物学参数。
15 例前列腺和头颈部(H&N)癌症患者接受了调强放疗。在治疗前,通过逐束分析进行了患者特异性质量保证,并生成了束特异性剂量误差分布。通过对每束相对剂量误差分布进行反向投影,计算出预测的三维(3D)剂量分布。对不同器官(前列腺:临床[CTV]和计划靶区[PTV]、直肠、膀胱、股骨头;H&N:大体肿瘤体积[GTV]、CTV、脊髓、脑干、双侧腮腺)进行了 2%/2mm 容差和物理伽马通过率的预测和计划剂量分布的 3D 伽马分析。计算了物理伽马指数(PGI)>1 的体素的 TCP 和 NTCP 值。我们提出了一种新的放射生物学伽马指数(RGI)来量化 TCP 和 NTCP 的放射生物学效应,并计算放射生物学伽马通过率。
前列腺病例的平均 RGI 伽马通过率与 PGI 有显著差异(P<.03-.001)。H&N 病例(除 GTV 外)的平均 RGI 伽马通过率与 PGI 有显著差异(P<.001)。PGI 和 RGI 之间的伽马通过率差异是由于计划和预测剂量分布之间的剂量差异所致。放射生物学伽马分布可视化,以确定剂量具有放射生物学重要性的区域。
提出了 RGI 将放射生物学效应纳入 PGI。该指标不仅有助于医生和医学物理学家进行治疗交付准确性的物理评估,还有助于对预测剂量分布进行临床评估。