ESTRO 2022 - Abstract Book

S1258

Abstract book

ESTRO 2022

Figure 2. Median and interquartile range (IQR) of V%, DSC, and MAX_DA for all considered OARs (2a). Graphical representation of V% (2b - top) and relative formula (2b- bottom).

Conclusion In conclusion, as expected bony structures resulted less prone to motion than the other OARs; GTV is found to be the structure with the greatest V%, meaning a great displacement with respect to its location in the sCT; thus in order to achieve safety and accuracy during stereotactic treatments also GTV motion has to be considered, and further highlights the importance of CBCT imaging. In the era of personalized medicine and tailored treatment, dealing with inter-fraction errors due to motion is still an open question and would lead to safer and more effective treatment approaches.

PO-1483 A predictive model to quantify the dosimetric impact of inter-fraction variability in breast cancer

M. Iezzi 1 , D. Cusumano 2 , D. Piccari 3 , S. Menna 2 , F. Catucci 3 , A. D'Aviero 4 , A. Re 4 , C. Di Dio 4 , F. Quaranta 4 , A. Boschetti 4 , M. Marras 3 , D. Piro 3 , C. Votta 3 , E. Sanna 3 , C. Flore 3 , G.C. Mattiucci 2 , V. Valentini 5 1 Institute of Radiology, Università Cattolica del Sacro Cuore, Department of Radiological and Hematological Sciences, Rome, Italy; 2 Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Departemet of Radiation Oncology, Rome, Italy; 3 Mater Olbia Hospital, Departemet of Radiation Oncology, Olbia, Italy; 4 Mater Olbia Hospital, Department of Radiation Oncology, Olbia, Italy; 5 Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Department of Radiation Oncology, Rome, Italy Purpose or Objective Breast cancer is one of the anatomical sites where standard radiotherapy (RT) has today a very established role, so the benefits brought by the introduction of any new variation has to be carefully assessed. As a discipline in its infancy, online adaptive RT (ART) needs new ontologies and ad hoc criteria to evaluate the appropriateness of its use in clinical practice. In this experience we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to early identify the treatment fractions where patients might benefit of an online ART approach. Materials and Methods The study was focused on right breast patients treated using standard adjuvant RT on an Artificial Intelligence (AI)-based linear accelerator (Ethos, Varian Medical System). Patients were treated with daily CBCT images and without online adaptation, prescribing 40.05 Gy in 15 fractions, with a IMRT technique consisting in four tangential beams. ESTRO guidelines were followed for the delineation on planning CT (pCT) of organs at risk (OARs) and target volumes: CTV was defined as entire mammary gland, PTV as CTV+5 mm in LR and 7 mm in AP and CC direction, with 5 mm crop margin from the body. For each patient, all the CBCT images were rigidly aligned to pCT, excluding rotational shifts according to Ethos workflow. CTV and PTV were manually re-contoured on daily CBCT images, and the original treatment plan was recalculated. Various radiological parameters were measured on CBCT images, with the aim of quantifying inter-fraction variability present in each RT fraction after couch shifts compensation. The absolute difference in terms of body between daily CBCT and pCT was calculated along each beam axes, considering the isocentre plan as reference plan. The variation of these parameters was correlated with the variation of V95% of PTV ( Δ V95%) using the Wilcoxon Mann Whitney test. Fractions where Δ V95>2% were considered as adverse events. A linear regression model was calculated considering the most significant parameter and its performance were quantified in terms of Receiver Operating Characteristic (ROC) curve

Results