Page 36 - FiM_03_2016

An adaptive min-max robust optimization strategy for the management of the geometrical uncertainties of the radiotherapy treatment in prostate cancer patients.
Candidato: Maria Oronzio
Relatore: Marco Brambilla
Azienda Ospedaliero-Universitaria Maggiore della Carità, Novara
Scuola di Specializzazione in Fisica Medica (A.A. 2014-2015) Direttore: Roberto Cirio
Purpose: To implement a new offline adaptive radiotherapy technique in prostate cancer patients based on the modeling of the organ motion by means of deformable image registration (DIR) contour propagation and the inclusion of setup uncertainties directly in the optimization process by means min-max robust optimization.
Methods: Five patients with low-intermediate stage prostate cancer were retrospectively evaluated in this study. The patients underwent exclusive radiotherapy with prescribed doses of 78-60 Gy (2 Gy /fr) respectively on CTV1 (prostate) and CTV2 (prostate + seminal vesicles). For each patient 5 consecutive CBCT (in the first 5 fractions ) plus 7 CBCT (once a week for the remaining fractions) were acquired during the treatment course. All the CBCT were co-registered with the planning CT importing in the treatment planning system (TPS) the on-line match rigid transformation provided by the OBI system on the treatment unit, a Varian Trilogy TX linear accelerator. Subsequently the DIR algorithm ANACONDA [1] implemented in the TPS Raystation has been applied for the deformable image registration of all the CBCTs with the reference planning CT. The first 5 CBCT were used in order to model the prostate deformations due to organ motion of rectum and bladder as a consequence of their different filling conditions over the time. CTV1 and CTV2 were propagated by means of DIR on the CBCTs , the reliability of contour propagation was assessed by a radiation oncologist correcting any inconsistence, the envelope of the resulting CTVs was used to derive a patient specific ITV for each target volume (fig.1). The customized ITVs were used to adapt the plan for the remaining treatment fractions, the original plan, consisting of a dual arc VMAT, was re- optimized (fig.2) by means of a min-max robust algorithm based on the worst scenario optimization originally developed by Fredriksson [2,3] with an isotropic 5 mm maximum setup error. CTV coverage and OAR sparing of robust optimization planning (RP) was previously validated respect the standard PTV based plans (SP) simulating in silico isocenter perturbations occurring along the antero-posterior direction in the range [-5 mm, 5mm] with a step of 1 mm. Then CTV coverage and OAR sparing were analyzed and compared calculating the dose distributions on the residual CBCTs acquired during the remaining treatment course generated by adapted RP and PTV based original SP.
Results: Robustness simulation showed that RP successfully achieve optimal coverage of CTV also in the worst case scenario (geometric error up to 5 mm) with D99>95% of prescribed dose with significant less dose to rectum and bladder. The analysis on all the residual CBCT acquired during the treatment showed that CTV coverage was optimal and not significant different among SP and RP, but statistically and clinically significant dose reduction was noted in rectum (p<0.001, Wilcoxon test) and in the case of empty bladder (p<0.01, Wilcoxon test) . RP appear to give a better sparing and to be less sensitive to risk organ filling like happens in rectum and bladder (fig.3), moreover also the integral dose resulted inferior in RP.
Conclusions: Robust optimization is a feasible and safe approach in prostate treatment. It can be successfully used to adapt the treatment with better target coverage and OAR sparing then standard PTV based planning during the treatment course.
Bibliography
Tesi di Specialità
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