Lobb Eric, Plypoo Ahpa
Department of Radiation Oncology, Ascension NE Wisconsin - St. Elizabeth Hospital, Appleton, Wisconsin, USA.
J Appl Clin Med Phys. 2022 Jul;23(7):e13634. doi: 10.1002/acm2.13634. Epub 2022 May 9.
To systematically investigate the performance of the analytical anisotropic algorithm (AAA) within the extremes of small tumor volumes and near-minimum lung and tumor tissue densities in order to identify combinations of these parameters where the use of AAA could result in a therapeutically unacceptable loss of tumor coverage on an energy and fractionation-specific basis.
Clinically appropriate volumetric modulated arc therapy (VMAT) treatment plans were generated with AAA for 180 unique combinations of lung density (0.05-0.30 g/cm ), tumor density (0.30-1.00 g/cm ), tumor diameter (0.5-2.5 cm), and beam energy (6 and 10 MV) and recomputed using the AcurosXB algorithm. Regression analysis was used to identify the strongest predictors of a reduction in biologically effective dose at a clinically relevant level (100 Gy BED10) for commonly utilized 1-5 fraction treatment regimens. Measurements were performed within a phantom mimicking the lower extremes of lung and tumor densities to validate AcurosXB as the approximate ground truth within these scenarios.
The strongest predictors of a statistically significant reduction in tumor coverage were lung density ≤0.15 g/cm , tumor diameter ≤10 mm, tumor density equal to 0.30 g/cm , and a beam energy of 10 MV. Overestimation of clinical target volume (CTV) D95% and CTV V100Gy (BED10) by AAA can exceed 30%-40% in some scenarios. Measurements supported AcurosXB as highly accurate even for these challenging scenarios.
The accuracy of AAA rapidly diminishes near the minima of clinical lung density, particularly in combination with small tumors and when using a photon energy of 10 MV. The magnitude of the effect can be more dramatic than previously reported data suggests and could potentially compromise the ablative qualities of treatments performed within these environments, particularly with less aggressive fractionation approaches.
系统研究分析各向异性算法（AAA）在小肿瘤体积以及接近最小肺组织和肿瘤组织密度情况下的性能，以确定这些参数的组合，在此类组合下，基于能量和分次放疗的特定情况，使用AAA可能会导致肿瘤覆盖范围出现治疗上不可接受的损失。
采用AAA为180种独特的肺密度（0.05 - 0.30 g/cm³）、肿瘤密度（0.30 - 1.00 g/cm³）、肿瘤直径（0.5 - 2.5 cm）和射束能量（6和10 MV）组合生成临床适用的容积调强弧形放疗（VMAT）治疗计划，并使用AcurosXB算法重新计算。回归分析用于确定在临床相关水平（100 Gy BED10）下，对于常用的1 - 5分次治疗方案，生物有效剂量降低的最强预测因素。在模拟肺和肿瘤密度下限的模体中进行测量，以验证AcurosXB在这些情况下作为近似真实情况的准确性。
肿瘤覆盖范围出现统计学显著降低的最强预测因素为肺密度≤0.15 g/cm³、肿瘤直径≤10 mm、肿瘤密度等于0.30 g/cm³以及射束能量为10 MV。在某些情况下，AAA对临床靶体积（CTV）D95%和CTV V100Gy（BED10）的高估可超过30% - 40%。测量结果支持AcurosXB即使在这些具有挑战性的情况下也具有高度准确性。
AAA的准确性在临床肺密度接近最小值时迅速下降，特别是与小肿瘤组合以及使用10 MV光子能量时。这种影响的程度可能比先前报道的数据所显示的更为显著，并可能潜在地损害在这些环境中进行的治疗的消融质量，尤其是采用不太激进的分次放疗方法时。
