ESTRO 37 Abstract book

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ESTRO 37

Purpose or Objective To date, no significant dose-volume effect relationship has been demonstrated to predict late bowel or sigmoid bowel toxicity in locally advanced cervical cancer (LACC) patients (pts) receiving chemoradiation plus image guided adaptive brachytherapy (IGABT). In fact, dose volume parameters, such as the D 2cm3, are highly uncertain due to mobility of the bowel. The total reference air kerma (TRAK) is the sum of the products of the Reference Air Kerma Rate and the irradiation time for each source. It is directly proportional to the integral dose to the pts. Recent data showed that the TRAK accurately predicted isodose surface volumes in cervix cancer IGABT. This study aims to examine correlation between and late bowel toxicities in pts receiving pulse dose rate (PDR) IGABT. Material and Methods Clinical data of 260 LACC pts treated with curative intent in our institution from 2004 to 2016 were examined. Pts received external beam radiotherapy (EBRT) +/- concomitant chemotherapy and a PDR-IGABT boost. Objective was to deliver at least 60Gy to 90% of the CTV IR and 85Gy to the D90 of the CTV HR . For the sigmoid bowel, D 2cm3 was kept <70-75 Gy EQD2 . For small bowel, loops closed to CTV were delineated, but no dose constraint was applied. Bowel toxicity (including sigmoid toxicity) was examined as occurrence of late morbidity assessed using Common Terminology Criteria for Adverse event 4.03 considering following events: diarrhea, flatulence, abdominal pain, obstruction, stenosis, bowel fistula. The relationships between TRAK and toxicity were assessed using survival estimation model by Kaplan-Meier, log-rank tests and Cox proportional-hazards model on event-free periods with the exclusion of recurrences. Results With median follow-up of 5 years (Interquartile [IQ] 4.5- 5.4), late bowel toxicity Grade (Gr) ≥2 occurred in 56 pts (21.5%). Probability of survival without late bowel toxicity Gr≥2 rate for pts without recurrence (n=174) at 5 years was 82.4 (76.1–88.7). The mean TRAK was 1.7cGy at 1m (IQ: 1.51–1.88). The following variables were associated with higher probability of late bowel toxicity Gr≥ 2: smoking (p=0.029), larger CTV HR (p=0.007), higher D 2cm3 sigmoid (trend, p=0.073) and TRAK>1.8 cGy at 1m (p=0.014). Larger CTV HR volumes were correlated with higher TRAK (p<0.001). In multivariate analysis, including smoking status, a TRAK>1.8 cGy at 1m was significantly associated with more frequent bowel toxicity, with HR=6.45 (95%confidence interval: 1.22–34.19). Conclusion In this single center cohort of PDR-IGABT, TRAK was predictive of late bowel/sigmoid bowel toxicities Gr≥2. These data suggest that the integral dose (and therefore the reference isodose volume) should be considered, even in the era of IGABT, and that dose volume constraints applied to organs at risk D 2cm3 might not fully reflect the expected toxicity of treatments. OC-0075 A MRI radiomic signature for predicting brachytherapy outcomes in locally advanced cervical cancer S. Reuzé 1,2,3 , A. Alexis 1,2 , C. Chargari 2,3,4,5,6 , S. Bockel 4 , K. Berthelot 4 , A. Escande 4 , I. Dumas 1 , F. Orlhac 7 , C. Haie- Meder 4 , E. Deutsch 2,3,4 , C. Robert 1,2,3 1 Gustave Roussy, Radiotherapy Department- Medical Physics Unit, Villejuif, France 2 Paris-Saclay University, Faculty of Medicine, Le Kremlin- Bicêtre, France 3 INSERM U1030, Molecular Radiotherapy, Villejuif, France 4 Gustave Roussy, Radiotherapy Department, Villejuif, France 5 Institut de Recherche Biomédicale des Armées, Paris, France 6 French Military Health Services Academy, Ecole du Val-

de-Grâce, Paris, France 7 CEA-SHFJ, IMIV, Orsay, France

Purpose or Objective The standard treatment of locally advanced cervical cancer (LACC) consists of concomitant chemoradiation followed by brachytherapy (BT). The recent implementation of image-guided adaptive brachytherapy (IGABT) has shown a significant improvement in local control rates while limiting toxicity. Conventional prognostic factors for local control have been identified such as the volume of the high-risk clinical target volume (HR-CTV) at time of BT or the overall treatment time. However, with the advent of IGABT, tumor texture analysis could be a powerful tool providing additional quantitative information to refine the prediction of outcome. The aim of this study was to identify a radiomic signature of LACC relapse based on per-BT fast-spin echo T2 (FSE T2) MRI realized with vaginal mold, after a 45 Gy radiotherapy. A methodological study was first carried out to identify the most robust and informative textural features. Material and Methods Two groups of patients with LACC treated with pulsed- dose-rate IGABT after initial concomitant chemoradiation were retrospectively included (TS: N=60, training; VS: N=40, validation). FSE T2 MRI were used for BT planning and were acquired on the same device with similar acquisition parameters. Using LIFEx freeware, we extracted 30 textural features from the HR-CTV delineated on per-BT MRI. To this end, voxel intensities were first resampled (absolute method: fixed bin size in [0-6000]). The relationships between features, their correlation to tumor volume and their robustness with respect to the intensity discretization step were studied. The ability of features to predict relapse was afterwards assessed through univariate and multivariate statistical analysis. Results Discretization affects the feature values and resampling using at least 30 gray levels (bins) should be used for texture feature calculation for FSE T2 MRI. LGZE and LZLGE were highly sensitive to variation of discretization step. Using 40 bins, 11 groups of highly correlated features were identified (Spearman correlation coefficient |ρ|>0.75) and 4 features were shown to be highly correlated to the volume of HR-CTV (Fig.1). Therefore, only 9 groups including 24 robust features were considered for the clinical analysis. In univariate analysis, five features were statistically significant discriminators of relapsing patients from non-relapsing patients (TS: Wilcoxon test, p<0.05). A 5-features signature predicting relapse was identified and validated (TS: AUC=0.88, p<0.00001, VS: AUC=0.78, p<0.01, Fig.2) and performed better than the five features determined from univariate analysis and the volume of HR-CTV (TS, Delong’s test, p<0.05).