Abstract Book

S1079

ESTRO 37

The aim of our study was to determine how changes in brain metastases over time can impact on radiosurgical treatment planning. Material and Methods Retrospective and unicentric study of patients with brain metastases who were evaluated for radiosurgical treatment (SRS) between March 2016 and September 2017. All patients underwent a planning MRI. We analysed time between diagnostic MRI (dMRI) and planning MRI (pMRI), changes in dimension and/or number of lesions and time between pMRI and treatment delivery. Results Forty-one patients were identified. Median time between dMRI and pMRI was 28 days. Forty-six percent (n=19) of patients had stable disease on pMRI and 54% (n=22) had significant changes in dimension and/number of lesions. Median time between dMRI and pMRI for these two groups was 23 and 31,5 days, respectively. In 37% (n=17) there was a change in dimension which would lead to suboptimal tumour coverage or overtreatment of normal brain tissue. In 17% of patients (n=7) SRS was not performed: in 1 patient due to the disappearance of the suspicious lesion and in 6 patients due to a substantial increase in the number of lesions. These 6 patients were referred to WBRT. Median time between pMRI and SRS was 2 days. Thirty-four patients with 50 lesions were treated. Conclusion Important tumour changes can occur in a short time leading to suboptimal tumour coverage, overtreatment or geographical miss. Our study emphasizes the need to treat patients based on a planning MRI and to minimize the time between planning and delivery of SRS. EP-1983 Robust DIBH 3D conformal irradiation technique of left sided whole breast + supraclavicular region S. Russo 1 , F. Rossi 2 , M. Esposito 1 , S. Pini 1 , R. Barca 2 , S. Fondelli 2 , L. Paoletti 2 , P. Bastiani 2 1 Azienda USL Toscana Centro, SC Fisica Sanitaria - Firenze, Bagno a Ripoli - Firenze, Italy 2 Azienda USL Toscana Centro, SC Radioterapia- Firenze, Bagno a Ripoli - Firenze, Italy Purpose or Objective The aim of the study was to compare the deep inspiration breath-hold (DIBH) 3D conformal irradiation technique with Free-breathing (FB) 3D conformal and volumetric modulated arc therapy (VMAT) for left sided whole breast + lymph node radiation therapy and to verify the robustness of DIBH delivery Material and Methods An Elekta Synergy linac is used to simulate the treatment of five patients. Three plans were generated in Monaco 5.0 for each patient with FB and DIBH 3D conformal and FB VMAT technique with a dose prescription of 50 Gy in 25 fractions. Plan quality was assessed considering target coverage, sparing of the controlateral breast, the lungs, the heart and the normal tissue. The Wilcoxon test was used for statistical analysis with a significance level of 0.05. Optical surface tracking technologies were used to support the DIBH gated treatments. Prospective gating CT imaging was performed by Sentinel™ (C-RAD Positioning AB, Sweden) laser scanner system and a GE BrightSpeed CT scanner. Base line level and gating window amplitude of the respiratory signal was established during CT simulation procedure. DIBH treatments delivery was gated by the Catalyst™ system (C-RAD Positioning AB, Sweden) connected with an Elekta Synergy linear accelerator (Elekta AB, Sweden) via the Elekta Response™ Interface. Visual coaching through video goggles were provided to help the patient following the optimal breathing pattern.

The robustness of DIBH delivery was assessed by set-up verification with electronic portal images (EPID) and intra-fraction monitoring via the optical system. EPID were acquired during the first three treatment fractions and one time week for and compared with the digitally reconstructed radiographs with a maximal acceptable tolerance of 5 mm. Intra-fraction and intra-beam set-up variability were quantified over all the treatment fractions. Results DIBH 3D technique provided a significant dose reduction in Heart Mean Dose (0.8 Gy DIBH 3D 2.6Gy 3D FB vs 4.5 VMAT FB), and LAD mean dose (3.8 Gy DIBH 3D 14.2Gy 3D FB vs 9.0 VMAT FB) . Better PTV coverage was found in DIBH 3D plans and no difference in Homolateral Lung parameters (V10, V20 and Dmedia) were achieved . Controlateral breast and lung and the normal tissue were significantly spared in DIBH 3D irradiation. Set-up verification with EPID and intra-fraction monitoring via the optical system provided an Intra-fraction variability <3.1 mm in translations and <3° in rotations. Conclusion Balancing target coverage and OAR sparing, DIBH 3D conformal can be considered the preferable of the investigated treatment options in left sided whole breast + lymph node supraclavicular region boost irradiation EP-1984 A radiobiological Markov simulation tool for aiding decision making in proton therapy referral A. Austin 1 , S. Penfold 2 , M. Douglass 2 , G. Nguyen 3 1 University of Adelaide, Physical Sciences, Adelaide, Australia 2 Royal Adelaide Hospital, Medical Physics, Adelaide, Australia 3 University of Adelaide, Mathematical Sciences, Adelaide, Australia Purpose or Objective The use of intensity modulated proton therapy (IMPT) for the treatment of cancer has become increasingly common in recent years. The main attraction of IMPT lies in the fact that a reduced integral dose can be deposited in the patient compared with intensity modulated radiation therapy with X-rays (IMRT) while maintaining an equivalent tumour dose. However, compared with IMRT it is more expensive with limited availability. This suggests that patients most in need should be given priority. Such clinical decisions are traditionally based on the results of clinical trials. The rapidly evolving nature of radiation oncology treatment technology, however, can make it difficult to base clinical decisions on data from clinical trials as the long follow-up times required can lead to results being outdated shortly after they are gathered. Alternatively, modelling studies can provide a prediction of the clinical outcome of a planned treatment, and hence can assist a clinician when deciding whether to refer a patient for proton therapy. Material and Methods A Monte Carlo-based Markov model has been developed to estimate the radiobiological effect of a given treatment plan and hence the clinical outcome of an individual patient. The Markov model approximates the time remaining of the patient’s life after treatment as a series of transitions between several discrete states that describe the health status of the patient. The radiobiological effect is quantified in terms of the tumour control probability (TCP), normal tissue complication probability (NTCP) and second primary cancer induction probability (SPCIP). These metrics are used as transition Electronic Poster: Physics track: (Radio)biological modelling