ESTRO 37 Abstract book

S208

ESTRO 37

Material and Methods Calibration: A published stoichiometric parametrization ("The calibration of CT Hounsfield units for radiotherapy treatment planning", Schneider et al. 1996) using three fitting parameters was used for calibration. The CIRS Electron Density Phantom model 062M containing eight tissue substitutes and a large air cavity was scanned using thorax protocols on a CT scanner (Philips Brilliance Big Bore) and five linacs (Clinac On-Board Imaging system, VMS). Phantom study: The anthropomorphic Alderson Radiation Therapy Phantom (ARTP) was scanned on the same scanners and a dose plan was simulated on these images using the Eclipse treatment planning system (VMS). The dose on CBCT images was calculated using a mean curve obtained by taking the mean of the individual curves from the five linac CBCTs. Six structures were delineated on CT images of the ARTP, rigidly transferred to the CBCTs and mean doses to these structures were compared. Patient study: Fifty lung cancer patients had control CT scans (cCT) taken at treatment fraction (F) 10 and 20. Twelve patients were selected for the analysis based on the criterion that the anatomy and patient positioning on cCT and CBCT acquired at F10 and F20 was unchanged. Target and organs at risk were transferred rigidly from cCT to CBCT. The planned dose was calculated on the cCTs and the CBCTs at F10 and F20 and compared. Results Phantom study: The median difference in mean dose to the structures delineated on the ARTP was -0.37% (max.: 3.12%, min.: -6.52%) and the 25th to 75th percentiles lie within ±1%. Patient study: Figure 1 shows 95% and 50% isodose levels for one dose plan on CT (left) and CBCT (right). Very similar anatomy and dose distributions are seen. Dose differences between CBCT and CT images for 24 patient image sets are shown in figure 2 (12 patients, two data points each). The median lies within ±2% and the 25th to 75th percentiles within ±3%. The largest deviation is - 7.9%.

Conclusion On an anthropomorphic phantom the error in dose calculated on CBCT is within 1%; this error is 2% larger going from phantom to patient images. Thus dose calculations on CBCT are feasible within ~3% accuracy when transferring structures rigidly between similar images.

Proffered Papers: PH 8: 4D imaging and motion management

OC-0411 Investigation of MRI-derived surrogate signals for modelling respiratory motion on an MRI-Linac E.H. Tran 1 , B. Eiben 1 , A. Wetscherek 2 , D.J. Collins 2 , U. Oelfke 2 , G. Meedt 3 , D.J. Hawkes 1 , J.R. McClelland 1 1 University College London, Medical Physics and Biomedical Engineering, London, United Kingdom 2 The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Joint Department of Physics, London, United Kingdom 3 Elekta, Medical Intelligence Medizintechnik GmbH, Schwabmünchen, Germany Purpose or Objective Elekta’s MRI-Linac combines a linear accelerator (linac) with a 1.5T MRI scanner enabling imaging of a patient’s internal anatomy during radiotherapy treatment. Surrogate-driven motion models relate the motion of internal anatomy to easily measurable surrogate signal(s). Surrogates may therefore play a viable role in the realisation of online tracking and gating techniques in the MRI-Linac workflow. In this work, we generated and compared several MRI-derived respiratory surrogate signals to determine the most suitable one(s) for driving 2D motion models. Material and Methods Sagittal cine-MR images of two patients with advanced lung cancer were acquired at two alternating fixed slice locations through the tumour volume (Fig. 1a-b), with images from one location forming the surrogate dataset, and images from the other location forming the model dataset. The surrogate dataset was processed to generate signals based on the motion of diaphragm and skin, mean image intensity, image entropy, and principal component analysis (PCA) of the image intensities (Fig. 1c-d). Group- wise deformable image registration was performed on the model dataset to obtain deformation vector fields (DVFs)