Adaptation of dose-prescription for vestibular schwannoma radiosurgery taking body contouring method and heterogeneous material into account
DOI:
https://doi.org/10.2340/1651-226X.2025.41924Keywords:
Adaptation of dose-prescription, convolution algoritm, Gamma knife radiosurgery, vestibular schwannomaAbstract
Background: Majority of vestibular schwannoma (VS) patients have undergone gamma-knife radiosurgery (GKRS) with favorable results. Clinical evidence is derived from doses calculated with a type-a algorithm, which in this case assumes all material to be water. A type-b algorithm (Convolution algorithm [CA]) taking tissue heterogeneity into account is available. Historically, body contour is defined using a 16-point approximation, whereas modern softwares generate the body from Magnetic Resonance Imaging (MRI). The accuracy in dose-calculation algorithms (DCA) and contouring method (CM) will have a significant influence in the relation between clinical outcome and dosimetric data. The objective was to investigate the impact of DCA and CMs on dose distribution while preserving treatment conditions.
Methods: Treatment plans for 16 VS patients were recalculated in terms of DCA and CM. The difference in the dose covering 99% of the VS (DVS99%) depending on CM and DCA was estimated. The difference in DVS99% was used to adopt the prescription of new CA-based plans. CA-plans were recalculated to TMR10 to evaluate clinical treatability, as clinical evidence is derived from TMR10-doses.
Results: Both CM and DCA had a significant impact on the dose to VS and surrounding structures. CM altered the doses homogenously by 2.1–3.3%, whereas DCA heterogeneously by 5.0–10.7%. An increase of 9.1[8.1, 10.0]% was found for DVS99% and the CA-plans recalculated into TMR10 resulted in clinically treatable plans.
Interpretation: We conclude that transferring to more modern algorithms that take tissue heterogeneity into account heterogeneously alter dose distributions. This work establishes a safe pathway to adopt prescription dose for VS while preserving clinical treatability.
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Copyright (c) 2025 Marcus Fager, Michael Gubanski, Åsa Carlsson Tedgren, Hamza Benmakhlouf
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