188. Optimization of the Pinnacle 9.10 Physics parameters for the volumetric modulated arc treatments with Autoplanning module. (December 2018)

• Record Type: Journal Article
• Authors: Bernardi, L.; Benelli, M.; Betti, M.; Fedele, D.; Mazzoni, L.; Vaiano, A.
• Is Part Of: Physica medica. Volume 56(2018)Supplement 2
• Page Start: 177
• Publication Date: 2018-12
• Subjects: Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2018.04.199
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Purpose: In order to optimize the agreement between the planned and the delivered dose distribution for VMAT treatments and thus obtain better pretreatment dosimetric evaluation, a set of Linac Elekta Synergy Agility specific machine parameters has been tuned in the TPS Pinnacle 9.10 with autoplanning module. Methods: The introduction of the autoplanning module in the TPS resulted in a higher complexity of the treatment plans, worst affecting, as a consequence, the outcome of pretreatment dosimetric evaluation. This situation has been confirmed by a retrospective analysis of VMAT treatments of the Head&Neck district delivered in our center since 2015. The set of machine parameters considered in this study included dose rate, leaf motion, gantry speed and dynamic leaf gap. The association between these parameters and the outcome of pretreatment dosimetric evaluation by OCTAVIUS 4D (PTW) with 729 matrix has been performed. Results: Our analysis suggests to use more stringent constraints for dose rate (by setting effective rather than nominal value as the maximum dose rate), leaf motion and gantry speed. As for the dynamic leaf gap, a commissioning of two machines was performed including a machine with the minimum achievable value to carry out stereotactic treatments in proximity of risk organs or multiple targets and a machine with a greater value for the remaining treatments. As a result, for the non SRT/SBRT VMAT treatment, these two machines enabled to obtain clinically equivalent plans in terms of PTV and OAR, but with less modulation. Conclusions: The dynamic leaf gap resulted as the parameter impacting the most on the complexity of the plans[1], also affecting the outcome of pretreatment dosimetric evaluation. To have a greater flexibility in the planning phase, it could be helpful to have the possibility of setting the value of this parameter outside the physics of the machine.