ESTRO 38 Abstract book

S185 ESTRO 38

features in our study were the most significant predictive values. To the best of our knowledge, this is the first work that shows predictive value of radiomics features in T2- weighted MRI for cervical cancer patients. These features need to be validated in subsequent more patients. Thus, the further investigation as comprehensive prediction model of LRR in cervical cancer patients would provide more statistical power and confirmation of these valuable features.

were extracted from GTV on pre-treatment T2-weighted MRI as a 3D contouring volume with MATLAB program. The association between radiomics features and loco-regional recurrence (LRR) were analyzed by T-Test and controlled by false discovery rate to reduce type I error from multiple testing. Then, the multivariable analysis was performed with significant radiomics features and known clinical prognostic factors using Cox-proportional hazard model. Results The median follow-up time was 29.2 months in this study. 12 of 90 patients (13.3%) had LRR. 80 radiomics features were collected. The statistically significant association between each radiomics features with LRR showed as table below.

Joint Symposium: ESTRO-ASTRO: Translating discovery to cure

SP-0370 Integrating Immunotherapy with Radiation J. Schoenfeld 1 1 Dana Faber Cancer Institute, Radiation Oncology, Boston, USA Abstract text Immunotherapy has revolutionized the field of oncology. However, only a minority of patients with solid tumors respond to current immunotherapy treatments. Here, we will review the mechanism of action of immune checkpoint blockade and outcomes in recent seminal immunotherapy trials. Preclinical and an increasing amount of clinical data suggest that radiation can augment the clinical effectiveness of immune checkpoint blockade – we will review these data and discuss ongoing clinical trials. SP-0371 A retrospective overview and future perspectives of developments in MRgRT J. Lagendijk 1 1 UMC Utrecht, Department of Radiation Oncology, Utrecht, The Netherlands Abstract text Currently, MR linacs systems are entering the clinic. Those systems move radiotherapy in the direction of real-time MRI guided treatment optimization, greatly reducing the targeting uncertainty in radiotherapy. This development puts great importance on all forms of high quality imaging needed for tumour localization and characterization; the step from relative large PTV volumes to stereotactic body irradiation requires better target definition. The reduction of the PTV both facilitates dose optimization and the further development of hypofractionation for the majority of tumours. This process transforms radiotherapy towards interventional radiology, re-inventing radiotherapy and finally allowing dose painting as pointed out by every TCP model. The Impact on the organization of radiotherapy will also be discussed. The new focus on complex, large imaging departments with interventional treatments will steer away from the old model with small radiotherapy satellites with a focus on closeness to the patient. SP-0372 Real Time Adaptive Radiation, Lessons from Clinical Practice Teams M. Bassetti 1 1 University of Wisconsin School of Medicine and Public Health, Human Oncology, Madison, USA Abstract text Radiation treatment plans are traditionally created pre- treatment and are unchanged during the course of delivery. Recent advances in radiation treatment delivery systems, including integration of MRI and rapid treatment planning software, enable oncologists to adapt radiation treatment plans in real time. This capability to adjust treatment to account for daily anatomical position changes allows the potential to increase dose to tumors and minimize dose to normal organs. While opening

The maximum intensity feature (p = 0.00023) and correlation135 GLCM feature (p = 0.0015) were the lowest p values.

Cox-regression analysis of radiomics features controlled for known clinical prognostic factors also confirmed significant hazard ratio for maximum intensity (p = 0.038) and correlation135 GLCM (p = 0.013) features. For overall survival outcome, there was no statistically significant association in any radiomics features Conclusion The pre-treatment T2-weighted MR images in cervical cancer patients could provide additional information in predictive value of radiomics features with radiotherapy outcomes. Maximum intensity and correlation135 GLCM