Evaluation of Skin Dose In Tomohelical TBI Using Virtual Bolus across Two Treatment Planning Systems
Abstract
Purpose
This study evaluates the effect of virtual bolus (VB) thickness on skin dose in TomoHelical total body irradiation (TBI) using two treatment planning systems (TPSs): Accuray Precision and RaySearch Laboratories RayStation (RS).
Methods
Bolus materials of tissue-equivalent density are used to increase surface dose, a critical consideration in TBI. Treatment plans were generated in both TPSs using VB configurations: no VB, 0.5 cm, 1.0 cm, and 1.5 cm. A 5-mm skin contour was defined for quantitative skin dose assessment. Due to differences in optimization algorithms between the TPSs, plans were optimized to achieve comparable dose distributions and target coverage metrics. In RS, beam spoilers lining the treatment bore were modeled and evaluated as an alternative to VB. Dosimetric indices for the skin and planning target volume (PTV) were recorded and compared.
Results
Increasing VB thickness resulted in higher skin dose across all plans, with the greatest skin coverage observed for the 1.5 cm VB (V95% = 84.8% in Precision and 82.4% in RS). The mean skin dose differed between TPSs by an average of 6.25 ± 2.1cGy, with Precision consistently producing higher skin doses than RS. Despite these differences, both systems achieved comparable PTV coverage, with similar V105%, V100%, D95%, and D50% values. For skin dose metrics, Precision exceeded RS by approximately 3cGy at D98% and 5cGy at D95%. Beam spoiler modeling in RS demonstrated increased skin dose with spoiler thickness while maintaining target coverage and lower overall high-dose exposure compared to VB. In contrast, VB produced higher skin dose but also increased high-dose regions.
Conclusion
RayStation can generate TomoHelical TBI plans comparable to Precision in terms of target coverage and skin dose. Both VB thickness and beam spoilers significantly influence skin dose. Future work will include physical measurements and Monte Carlo simulations to validate TPS-based findings.