158. Retrospective analysys of volumetric modulated arc therapy treatments: Correlation between plans complexity and dosimetric accuracy. (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: 161
• Page End: 162
• 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.2018.04.169
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Purpose: A retrospective analysis of VMAT treatments delivered in our center since 2015 has been performed by studying the correlation between the results of pretreatment dosimetric evaluation and different parameters related to the complexity of the treatment plans. Districts considered for this study included Head&Neck, Pelvis and Prostate. Methods: 3D pretreatment dose verification has been performed by OCTAVIUS 4D (PTW) with matrix 729 on a Linac Elekta Synergy Agility. Analysis of volumetric 3D gamma has been done by using thresholds of 3%, 3 mm and 10%. The treatment plans have been created with the TPS Pinnacle 9.10; since 2016, the autoplanning module was also considered. The complexity of each plan has been evaluated by a complexity index[1] and the number of MU. Within- and across- districts analysis has been performed by Receiver operating characteristic (ROC) curves. Results: For both complexity index and number of MU, our analysis identified a set of district-specific threshold values able to predict the success of pretreatment dosimetric evaluation (3D gamma >90%). Conclusions: Our analysis (for our configuration: Elekta Agility, Pinnacle 9.10 with autoplanning module, OCTAVIUS 4D with 729 matrix) suggests that, especially for Head&Neck and Pelvi, it's possible to predict the quality of a treatment plan on the basis of the corresponding complexity index and the number of MU. If validated prospectively, this analysis suggests the possibility to evaluate the quality of the plan before performing its 3D dose verification.