ESTRO 36 Abstract Book

S919 ESTRO 36 _______________________________________________________________________________________________

EP-1684 Optimal window for assessing treatment responsiveness on repeated FDG-PET scans in NSCLC patients M. Lazzeroni 1 , J. Uhrdin 2 , S. Carvalho 3 , W. Van Elmpt 3 , P. Lambin 3 , A. Dasu 4 , I. Toma-Dasu 5 1 Karolinska Institutet, Medical Radiation Physics- Department of Oncology-Pathology, Stockholm, Swede 2 RaySearch Laboratories AB, RaySearch Laboratories AB, Stockholm, Sweden 3 GROW-School for Oncology and Developmental Biology- Maastricht University Medical Center, Department of Radiation Oncology, Maastricht, The Netherlands 4 The Skandion Clinic, The Skandion Clinic, Uppsala, Sweden 5 Stockholm University, Medical Radiation Physics- Department of Physics, Stockholm, Sweden Purpose or Objective A previous study has shown that the early response to treatment in NSCLC can be evaluated by stratifying the patients in good and poor responders based on calculations of the effective radiosensitivity, αeff, derived from two FDG-PET scans taken before the treatment and during the second week of radiotherapy [1]. However, the optimal window during the treatment for assessing αeff was not investigated. This study aims at assessing αeff of NSCLC tumours on a new cohort of patients for which the second scan was taken during the third week of treatment. The optimal window for response assessment could be determined by investigating the ability of the method to predict treatment outcome through a comparison of the results of a ROC analysis for the new cohort of patients, imaged at three weeks, with the results of the previous study in which patients were imaged at two weeks. Material and Methods Twenty-eight NSCLC patients were imaged with FDG-PET before the treatment and during the third week of radiotherapy. The patients received 45 Gy in 1.5 Gy fractions twice-daily followed by a dose-escalation up to maximum 69 Gy in daily fractions of 2 Gy. The outcome of the treatment was reported as overall survival (OS) at two years. αeff was determined at the voxel level taking into account the voxel SUV in the two images and the dose delivered until the second scan. Correlations were sought between the average (a_αeff) or negative fraction (nf_αeff) of αeff values and the OS. The AUC and the p- value resulting from the ROC analysis were compared to the corresponding values reported for the case when the second scan was taken during the second week of treatment. Results The ROC curves in Figure 1 show the correlation between a_αeff and OS and also the correlation between nf_αeff and OS in the present and the earlier analysis. The results expressed as AUC and p-value show the lack of correlation between either a_αeff (AUC=0.5, p=0.7) or nf_αeff (AUC=0.5, p=0.8) and the OS for the scan at 3 weeks. This contrasts with the case when the second image was taken during the second week of treatment (AUC=0.9, p<0.0001). From the comparison of the ROC curves it results that the values of αeff can be used for predicting the OS if the second scan is taken during the second week, but not during the third week.

Conclusion The optimal window for assessing the responsiveness to treatment based on αeff calculations derived from repeated FDG PET scans in NSCLC patients appears to be the second week of the treatment but validation on a larger cohort of patients is warranted. [1] Toma-Dasu I, Uhrdin J, Lazzeroni M, Carvalho S, van Elmpt W, Lambin P, Dasu A. Evaluating tumor response of non-small cell lung cancer patients with 18F- fludeoxyglucose positron emission tomography: potential for treatment individualization. Int J Radiat Oncol Biol Phys. 2015 1;91(2):376-84. EP-1685 CT-Radiomics outperforms FMISO-PET/CT for the prediction of local control in head-and-neck cancer J.A. Socarras Fernandez 1 , D. Mönnich 1 , F. Lippert 1 , D. Welz 2 , C. Pfannenberg 3 , C. La Fougere 4 , G. Reischl 5 , D. Zips 2 , D. Thorwarth 1 1 University Hospital Tübingen, Radiation Oncology - Section for Biomedical Physics, Tübingen, Germany 2 University Hospital Tübingen, Radiation Oncology, Tübingen, Germany 3 University Hospital Tübingen, Diagnostic and Interventional Radiology, Tübingen, Germany 4 University Hospital Tübingen, Radiology - Section of Nuclear Medicine, Tübingen, Germany 5 University Hospital Tübingen, Radiology - Section of Radiopharmacy, Tübingen, Germany Purpose or Objective FMISO-PET has proven to capture probabilities of hypoxia in tumors, which may predict risks of local recurrence across patients. On the other hand, Radiomics hypothesizes that heterogeneity of tumors can be extracted from medical images. In this study, we investigate the performance of CT-radiomics features and FMISO PET/CT for prediction of local recurrence in head and neck cancer (HNC) patients. Material and Methods A cohort of 22 HNC patients who underwent FMISO PET/CT before primary Radiotherapy (RT) treatment was used. Planning CT scans as well as FMISO PET/CT were acquired prior to RT, FMISO PET data was analysed using maximum tumour-to-muscle ratios (TMR max ) 4h post injection. 92 Robust radiomics features including intensity-based as well as texture features were extracted from the planning CT images in the gross tumour volume (GTV). Six highly significant radiomics features were selected from a simple filter method based on cumulative distribution function (CDF) in a univariate fashion in addition to a logistic regression classification model (LoG) to build a predictive model. Area under the curve of the receiver operating characteristic curve (AUC-ROC) was computed for TMR max and the model including the six selected radiomics Features. Finally, a combined model using FMISO TMR max and two radiomics features (one from texture and one from intesity) were constructed.