Dosimetric Comparison of AAA and Acuros Xb Algorithm In VMAT Total Body Irradiation
Abstract
Purpose
To evaluate dosimetric differences and dose calculation efficiency between the Anisotropic Analytical Algorithm (AAA) and Acuros XB for volumetric modulated arc therapy (VMAT)-based total body irradiation (TBI) planning.
Methods
Four previously treated patients undergoing VMAT TBI were retrospectively analyzed. Each patient received a three-isocenter VMAT plan consisting of eight upper-body VMAT fields and two conventional 3D parallel-opposed fields for the lower extremities. All plans were calculated using AAA with 6 MV photon beams, prescribing a total dose of 1200 cGy delivered in 8 fractions. For direct dosimetric comparison, each plan was recomputed using Acuros XB while preserving identical beam geometry and monitor units. Dose calculation time was manually recorded. Plan evaluation included target coverage and dose to organs at risk (OARs).
Results
The average dose computation time across all patients was 313 s and 187 s for AAA and Acuros XB, respectively. Higher V100% target coverage was observed in AAA plans compared with Acuros XB for all four patients, with differences ranging from 4.8% -10.4%. Meanwhile reduced maximum target was observed in Acuros XB where the largest difference was 3.2%. For organs at risk, Acuros XB demonstrated lower doses to the bilateral lungs (mean dose differences: 2.8% to 3.5%), oral cavity (D0.03cc differences: 2.4% to 3.3%), and lenses (D0.03cc differences: 1.2%–3.1%) compared with AAA. Dose differences for the kidneys and bowel were within 2%. Noticeable heterogeneity in the isodose distribution was observed in Acuros XB plans, with pronounced cold spots near bony anatomy.
Conclusion
Dosimetric differences were observed between VMAT TBI plans calculated using AAA and Acuros XB. Acuros XB resulted in reduced target coverage but improved OAR sparing compared with AAA, while also demonstrating shorter dose computation time. These findings highlight the impact of tissue heterogeneity modeling and the importance of algorithm selection in VMAT TBI planning.