Limits for the therapeutic application of the analytical anisotropic algorithm in the context of ablative lung radiotherapy near the minima of lung density and tumor size

PURPOSE: 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. METHODS: 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(3)), tumor density (0.30–1.00 g/cm(3)), 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. RESULTS: The strongest predictors of a statistically significant reduction in tumor coverage were lung density ≤0.15 g/cm(3), tumor diameter ≤10 mm, tumor density equal to 0.30 g/cm(3), 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. CONCLUSIONS: 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.