ESTRO 36 Abstract Book

S305 ESTRO 36 _______________________________________________________________________________________________

Material and Methods Work focused on bladder and prostate cancers and soft tissue sarcoma. Published hypoxia signatures were tested by analysing transcriptomic data from public databases. Tumour samples were available from the BCON phase III trial that randomised bladder cancer patients to radiotherapy alone or with carbogen and nicotinamide (CON). Gene expression was analysed in 152 BCON tumours using Affymetrix Human 1.0 Exon arrays and used for independent validation. Results Published signatures performed inconsistently and tended to do worse in bladder than prostate and sarcoma. A bladder-specific signature was derived, which was prognostic in an independent surgical cohort (n=408, p=0.00274) and in BCON patients receiving radiotherapy alone (n=75, hazard ratio [HR] for overall survival 2.80, 95% CI 1.48-5.32, p=0.0016). The signature also predicted benefit from CON (n=76, HR 0.47, 95% CI 0.26-0.84, p=0.011). Prognostic and predictive significance remained after adjusting for clinicopathological variables. A sarcoma signature was derived that was prognostic in independent Affymetrix Plus2 (n=127; HR=3.44, 95% CI 1.73-6.84; p<0.001) and The Cancer Genome Atlas (TCGA) RNAseq (n=246; HR=2.63, 95% CI 1.67-4.14; p<0.001) validation cohorts. A prostate signature was prognostic in TCGA (n=491; p<0.001) and an FFPE RNAseq (n=102; p=0.014) validation cohorts. The prostate signature was prognostic in the BCON radiotherapy arm (n=75; p=0.049) and predicted benefit from addition of CON to radiotherapy (p=0.019). Conclusion Tumour-type specific signatures outperform those derived in other tumour types. Biomarker driven trials are now required to test these signatures in a prospective setting. SP-0574 MLC tracking: from bench to bedside M. Fast 1 1 The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Joint Department of Physics, London, United Kingdom Dynamic multi-leaf collimator tracking is an emerging form of real-time adaptive radiotherapy in which the treatment beam is continuously reshaped according to the target motion in beam’s-eye-view. By following the regular or erratic motion of the treatment target, MLC tracking ensures its dosimetric coverage. Prominent examples for intra-fractional anatomy variations are respiration and gastrointestinal motion. Through better beam-target alignment and subsequent margin reductions, MLC tracking is utilized to reduced the size of the target volume. The reduction of dose to adjacent healthy tissue in combination with complete target coverage is especially relevant for highly conformal, hypo- fractionated treatment protocols. MLC tracking was first suggested in 2001 [1]. Since then, MLC tracking has been demonstrated on linac platforms of all major radiotherapy vendors: Elekta, Siemens and Varian. Initially, the feasibility of MLC tracking was established in phantom experiments and treatment planning studies. Recently, first clinical implementation trials have started in Sydney, Australia, designed to demonstrate the safety and efficacy of tracked treatment deliveries for prostate and lung cancer patients [2]. This presentation will give a brief summary of past research activities and derive conclusions with regards to clinical implementation. One crucial consideration when translating MLC tracking from the laboratory `bench’ to the clinical `bedside’ is quality assurance. Traditional delivery QA approximates Symposium: 4D imaging and tracked delivery

the patient as a static object and relies on the planned sequence of delivery control points. For MLC tracking, these approximations are too simplistic. Crucially, the interplay of patient and MLC motion is not known a-priori. A task group (TG 264) assembled by the American Association of Physicists in Medicine (AAPM) is currently developing guidelines on the “Safe clinical implementation of MLC tracking in radiotherapy”. At the same time, novel online QA tools are being developed in order to accumulate dose in real-time during each treatment fraction with the same dosimetric precision achieved in clinical treatment planning systems [3]. This presentation will summarise tracking QA requirements and give preliminary recommendations for clinical implementation. The efficacy of MLC tracking is limited by the spatial and temporal resolution of the target localisation modality, system lag times, and the mechanical performance of the MLC. Current target localisation strategies rely on x-ray imaging, often in combination with implanted radiopaque markers, or implanted resonant circuits and their detection with an electromagnetic antenna array. Less invasive and non-ionizing target localisation relying on soft tissue contrast, namely ultrasound imaging and MRI, are increasingly being investigated as drivers for MLC tracking deliveries. For tracked deliveries in the presence of a strong magnetic field, the electron-return effect could potentially introduce an additional challenge for the safe delivery of treatment. A recent treatment planning study, however, has confirmed the efficacy of MLC tracking on the Elekta MR-linac prototype [4]. The suitability of the treatment plan for MLC tracking is another important area of investigation. As an example, this presentation will provide a simple template for creating a treatment plan suitable for a tracked lung SBRT delivery. References [1] Keall et al. Motion adaptive x-ray therapy: a feasibility study. Phys Med Biol 2001;46:1-10. [2] Keall et al. The first clinical implementation of electromagnetic transponder-guided MLC tracking. Med Phys 2014;41: 020702. [3] Fast et al. Assessment of MLC tracking performance during hypofractionated prostate radiotherapy using real- time dose reconstruction. Phys Med Biol 2016; 61: 1546– 1562. [4] Menten et al. Lung stereotactic body radiotherapy with an MR-linac–Quantifying the impact of the magnetic field and real-time tumor tracking. Radiother Oncol 2016;119:461-466. SP-0575 Motions models and tracking using MR R. Tijssen 1 1 UMC Utrecht, Department of Radiation Oncology, Utrecht, The Netherlands Image guidance plays an important role in modern radiotherapy. Current x-ray based onboard imaging, however, has poor soft-tissue contrast, which challenges image guidance of mobile tumors. Particularly in abdominal regions, tumor visualization is virtually impossible on clinical CBCT images. By utilizing Magnetic Resonance Imaging (MRI) for radiation guidance, tumor and organs-at-risks (OAR) can be directly visualized and targeting can be improved. This has been the philosophy behind the development of the MRI-Linac (MRL). An MRI based workflow has the potential to shape the radiotherapy paradigm of the future: an online adaptive treatment in which positional uncertainties are mitigated and the deposited dose can be tracked in real-time making dose escalation possible while sparing healthy tissue. In order to facilitate this new paradigm, fast MRI acquisition and processing methods are needed that accurately map the motion within the entire irradiated volume with sufficient temporal and spatial resolution.