ESTRO 2021 Abstract Book

S615

ESTRO 2021

The model was applied to 189 C3 CT slices. Skeletal muscle area (SMA) and skeletal muscle density (SMD) (mean intensity in HU) were extracted from the segmentations after reviewing model predictions. The impact of these measurements on patient survival was analysed using a multivariate Cox proportional hazards model, with backwards variable selection considering tumour stage, RT total dose, number of fractions, age, sex, surgical intervention and current smoker status. Results The interobserver Dice score was 0.88, and the network achieved a Dice score of 0.89 indicating it is equivalent to a human observer. Only SMD was found to be prognostic (continuous variable, p = 0.001) in a multivariate model, with a hazard ratio of 0.96 per HU, indicating a decrease in SMD results in a worse patient outcome. The Kaplan-Meier curve for SMD, split by median values for men and women (33 HU and 26 HU), is shown in Figure 2, alongside the Cox regression hazard ratios shown in Table 1. Patients with SMD > median showed a higher survival time than patients with SMD < median, (93.9 months vs 32.5 months) for a survival probability of 0.75, suggesting that skeletal muscle is protective.

Conclusion An automatic model for determining skeletal muscle characteristics at C3 was developed using a pretrained CNN. The model was used to extract the SMD of 189 H&N cancer patients (median: 26 HU in women, 33 HU in men) and this was shown to be prognostic. The lack of significance in clinical variables indicates the need to explore a larger dataset. Our novel model at C3 allows sarcopenia assessment in H&N cancer patients, who often do not have scans that extend to L3. Further work will develop a suite of models at other vertebral levels to allow sarcopenia assessment of all radiotherapy patients. PD-0784 Predicting toxicity after RT for head and neck cancer: combining dosimetry with a biomarker T. Rancati 1 , S. Deneuve 2 , T. Bastogne 3 , M. Duclos 4 , P. Bois 2 , P. Bachmann 2 , L. Nokovitch 2 , P. Roux 2 , D. Girodet 2 , M. Puopart 2 , P. Zrounba 2 , L. Claude 2 , L. Ferella 5 , E. Orlandi 6 , N. Foray 7 , S. Perreira 4 1 Fondazione IRCCS Istituto Nazionale dei Tumori, Prostate Cancer Program, Milan, Italy; 2 Centre Regional de Lutte Contre le Cancer Léon-Bérard, Oncological Surgery, Lyon, France; 3 Institut De Cancérologie de Lorraine – Alexis VAutrin, Radiation Oncology, Vandoeuvre-lès-Nancy, France; 4 Neolys, Neolys, Lyon, France; 5 Fondazione IRCCS Istituto Nazionale dei Tumori, Radiation Oncology 2, Milan, France; 6 CNAO and Fondazione IRCCS Istituto Nazionale dei Tumori, Radiation Oncology, Pavia, Italy; 7 INSERM, Centre Léon Bérard, UA8 Unit, Lyon, France

Purpose or Objective