ESTRO 2022 - Abstract Book

S608

Abstract book

ESTRO 2022

Conclusion According to our results, pre-existing heart comorbidities and the onset of cardiac toxicity predict a higher risk of mortality in NSCLC patients treated with RT. Therefore, the risk of developing cardiac toxicity must be carefully considered in all patients. Preliminary dosimetric data suggest a possible correlation between heart dosimetry and the development of RT related cardiac toxicity, but longer follow up periods are required to confirm these findings.

PD-0673 Validation of the interaction between peritumour density and dose for local relapse in lung SABR

A. Davey 1 , M. Thor 2 , M. van Herk 1 , C. Faivre-Finn 1 , J.O. Deasy 2 , A. Rimner 3 , A. McWilliam 1

1 The University of Manchester, Division of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester, United Kingdom; 2 Memorial Sloan Kettering Cancer Center, Medical Physics, New York, USA; 3 Memorial Sloan Kettering Cancer Center, Radiation Oncology, New York, USA Purpose or Objective Local relapse (LR) can occur after lung SABR due to inadequate coverage of microscopic disease (MDE). A Cox-per-radius method has been applied to study the interaction between CT biomarkers that predict MDE and incidental dose, with preliminary data reported at ESTRO 2021. The resulting model proposed high peritumour density combined with high dose standard deviation (SD) outside the GTV as a predictor of LR. We update and explore the model in internal training and external validation cohorts. Materials and Methods 275 early-stage NSCLC patients treated to 60Gy (199, internal training data) or 50Gy (76, external validation data) in 5 fractions were collated from two institutions. In both, dose distributions were accumulated for respiratory motion and converted to EQD2. A pre-analysis plan was registered. Cox-per-radius was implemented to build a map of the interaction between 90th percentile density and dose SD in independent 1mm annuli outside the GTV, with a multiple-testing correction on region size implemented. Density and dose were averaged in annuli defined by the map and included in a Cox model. Bootstrapping was performed with 500 resamples to test stability and improvement in c-index compared to clinical variables after adjusting for optimism. For external validation, the overall models (clinical, including dose and density, and including the interaction) were explored with and without re-fitting in the external data. Results Cox-per-radius detected one region (at the GTV edge for density and 1 cm outside the GTV for dose) involved in LR (Fig. 1A). Only the model including the interaction improved the clinical model after bootstrapping on the internal dataset (Fig. 1B). The models did not directly translate when validating on the external dataset due to difference in demographics (Fig. 1C), prescription, and contouring (judged qualitatively). Model coefficients were, therefore, re-fitted, establishing the importance of the interaction in both datasets.