ESTRO 36 Abstract Book

S852 ESTRO 36 2017 _______________________________________________________________________________________________

Purpose or Objective Radiomics aims to extract features from medical images that are prognostic for outcome and may help optimize treatment. As far as the tumour is concerned, most work has focused on pixel values inside the gross tumour volume (GTV). The aim of this work is to develop a generic methodology to also sample pixels outside a tumour volume, assuming that these may carry information about microscopic tumour spread and therefore might predict outcome. Material and Methods We analysed data from a cohort of 1101 non-small cell lung cancer patients treated with IMRT to 55 Gy in 20 fractions. To evaluate the CT pixel values at various distances inside and outside the GTV, we calculated a signed distance transform of the GTV, which was subsequently used to efficiently collect cross-histograms of the CT density versus distance from the GTV edge. Based on these cross- histograms various pixel statistics were determined as function of the GTV distance, here we report only on the mean pixel value, giving a curve of mean CT value versus distance. The mean of these curves was calculated for patients that were alive (652) and dead (449) at 12 months after start of therapy, censored for follow-up. Significance of the difference was tested by permuting the dead/alive labels 1000 times to create mock differences and counting how often the true difference exceeded the mock difference. Significant regions were defined and the mean pixel value from those regions used as variable in a cox proportional hazard model, splitting the patients on the median of the mean region density, while correcting for age and tumour size. As the outside of the tumour can also include chest wall and mediastinum, we repeated the analysis only analysing pixels inside the lungs. Results There was a significant different average pixel value in the region 0-1 cm outside the GTV for dead and alive patients (fig. 1) that translated to a hazard ratio (HR) of 1.4, p<10 - 5 (corrected for tumour size and age), survival curves split at median density value (fig. 2A). However when only pixels inside the lungs were analysed, the HR reduced to 1.1, p=0.15; i.e. no longer significant (fig. 2B). This finding indicates that the mean pixel values represent mediastinal attachment rather than microscopic disease. Not correcting for tumour size, both signals incorrectly predict outcome significantly (e.g. fig. 2C for lung pixels only).

Conclusion Proper analysis of pixel-based data mining showed that lung pixel density outside the GTV did not predict for survival. The method we proposed allows pixel-based data mining based on distance to an organ. For such analysis, one should be well aware of confounding variables such as tumour size and mediastinal attachment. EP-1602 Treatment planning individualisation based on 18F-HX4 PET hypoxic subvolumes in NSCLC patients E. Lindblom 1 , A. Dasu 2 , J. Uhrdin 3 , A. Even 4 , W. Van Elmpt 4 , P. Lambin 4 , I. Toma-Dasu 5 1 Stockholm University, Medical Radiation Physics- Department of Physics, Stockholm, Sweden 2 The Skandion Clinic, The Skandion Clinic, Uppsala, Sweden 3 RaySearch Laboratories AB, RaySearch Laboratories AB, Stockholm, Sweden 4 Maastricht University Medical Center, Department of Radiation Oncology- GROW-School for Oncology and Developmental Biology, Maastricht, The Netherlands 5 Stockholm University and Karolinska Institutet, Medical Radiation Physics- Department of Physics and Department of Oncology and Pathology, Stockholm, Sweden Purpose or Objective Pre-treatment functional imaging of tumour hypoxia enables the identification of patients at greater risk of treatment failure, and, potentially, allows individualisation of treatment to overcome the increased radioresistance of hypoxic tumours. Treatment individualisation based on tumour hypoxia aims at identifying and prescribing higher doses to radioresistant hypoxic subvolumes based on the relative uptake of hypoxia-specific tracers. This study aimed to perform hypoxic target volume delineation and dose-prescription calculation for non-small cell lung cancer (NSCLC) patients using a novel hypoxic PET tracer, 18 F-HX4. Material and Methods Six non-small cell lung cancer (NSCLC) patients imaged with 18 F-HX4 PET/CT were included in the study. The hypoxic target volumes (HTV) were determined based on a non-linear conversion between tracer uptake and pO2,