Department of Radiation Oncology, Yunnan Tumor Hospital, The Third Affiliated Hospital of Kunming Medical University, No.519 Kunzhou, Road, Xishan District, Kunming, Yunnan, China.
Radiat Oncol. 2020 Jul 6;15(1):161. doi: 10.1186/s13014-020-01603-6.
To explore the efficacy and sensitivity of 3D gamma analysis and bio-mathematical model for cervical cancer in detecting dose changes caused by dose-calculation-grid-size (DCGS).
17 patients' plans for cervical cancer were enrolled (Pinnacle TPS, VMAT), and the DCGS was changed from 2.0 mm to 5.0 mm to calculate the planned dose respectively. The dose distribution calculated by DCGS = 2.0 mm as the "reference" data set (RDS), the dose distribution calculated by the rest DCGS as the"measurement"data set (MDS), the 3D gamma passing rates and the (N) TCPs of the all structures under different DCGS were obtained, and then analyze the ability of 3D gamma analysis and (N) TCP model in detecting dose changes and what factors affect this ability.
The effect of DCGS on planned dose was obvious. When the gamma standard was 1.0 mm, 1.0 and 10.0%, the difference of the results of the DCGS on dose-effect could be detected by 3D gamma analysis (all p value < 0.05). With the decline of the standard, 3D gamma analysis' ability to detect this difference shows weaker. When the standard was 1.0 mm, 3.0 and 10.0%, the p value of > 0.05 accounted for the majority. With DCGS = 2.0 mm being RDS, ∆gamma-passing-rate presented the same trend with ∆(N) TCPs of all structures except for the femurs only when the 1.0 mm, 1.0 and 10.0% standards were adopted for the 3D gamma analysis.
The 3D gamma analysis and bio-mathematical model can be used to analyze the effect of DCGS on the planned dose. For comparison, the former's detection ability has a lot to do with the designed standard, and the latter's capability is related to the parameters and calculated accuracy instrinsically.
探讨 3D 伽马分析和生物数学模型在宫颈癌中的功效和灵敏度，以检测剂量计算网格尺寸（DCGS）引起的剂量变化。
纳入 17 例宫颈癌患者计划（Pinnacle TPS，VMAT），分别改变 DCGS 从 2.0mm 至 5.0mm 计算计划剂量。将 DCGS=2.0mm 计算的剂量分布作为“参考”数据集（RDS），其余 DCGS 计算的剂量分布作为“测量”数据集（MDS），获得不同 DCGS 下所有结构的 3D 伽马通过率和（N）TCPs，并分析 3D 伽马分析和（N）TCP 模型检测剂量变化的能力以及哪些因素影响这种能力。
DCGS 对计划剂量的影响明显。当伽马标准为 1.0mm、1.0%和 10.0%时，3D 伽马分析可以检测到 DCGS 对剂量效应的结果差异（均 p 值<0.05）。随着标准的降低，3D 伽马分析检测这种差异的能力显示出较弱的趋势。当标准为 1.0mm、3.0%和 10.0%时，>0.05 的 p 值占大多数。当以 DCGS=2.0mm 为 RDS 时，除股骨外，所有结构的∆gamma 通过率与∆（N）TCPs 呈相同趋势，仅当 3D 伽马分析采用 1.0mm、1.0%和 10.0%标准时。
3D 伽马分析和生物数学模型可用于分析 DCGS 对计划剂量的影响。相比之下，前者的检测能力与设计标准有很大关系，后者的能力与内在参数和计算精度有关。
