ESTRO 38 Abstract book

S914 ESTRO 38

background signal subtraction and Gaussian smoothing) and resulting images of the treatment beam is passed through a feature extraction process to locate leaf edges (SOBEL operator). An Elekta Agility linear accelerator (linac) was used to assess four key characteristics of TRAPS detector performance: attenuation, linearity of signal with doserate, positional accuracy and dynamic field response. Multi-leaf collimator defined field shapes for 6MV and 10MV photon beams were delivered whilst simultaneously acquiring TRAPS and EPID images (using the Elekta IViewTM amorphous silicon imaging panel). EPID images were passed through the same feature extraction process and the resultant EPID leaf positions were used as ‘standard’ and compared with time matched TRAPS leaf positions. Deliberately introduced positional errors (0.5, 1, 2 and 3mm) for individual collimator leafs within thin rectangular fields were used to visually assess error detection capability. A dynamic treatment plan (VMAT delivery) was devised to test the ability of TRAPS to track the linear leaf movement at varying speeds and under challenging beam scatter conditions. Results The 6MV attenuation factor of the sensor was 1.04% +/- 0.03% for a 5x5cm field size. Pixel values in TRAPS detector images responded linearly for dose rates up to 450 MU per minute for 6MV and 10MV photons (corresponding to a pulse repetition frequency (PRF) of 380 Hz). For a flattening filter free beam (6FFF) the response was linear to a dose rate of 600 MU per minute (PRF of 150 Hz) but the pixels saturated at higher beam intensities. Positional accuracy of leaf edges in TRAPS images were within 1mm + 0.26mm of the corresponding EPID images (figure 1).

FWHM estimate. Measurement repeatability was tested on the 20x20 mm beam by repeating by moving and positioning the CMOS for five times. Response linearity and noise variation against current were also measured. Results The agreement of the measured dose profiles and beam sizes is fairly good, with maximum difference being less than 2% for all the four beams tested (see figure 2) with a maximum deviation for FWHM of 0.3mm for the 20x20 mm beam and of 0.1mm for the circular 1mm beam between MC and RLI.

Figure 2 Normalized beams profiles from RLI and MC. The image correction procedure was confirmed to be able to reduce the perspective distortion at a negligible level and, at the same time, is also robust and reproducible. RLI dose measurements were performed in both lights off/on conditions, the signal can be detected even in the light on condition making the RLI measurements possible even when light can not be removed (e.g. no light-tight irradiators) without relevant impact on dose profiles measurements. Linearity was confirmed (R 2 =0.9996) and the noise was found to be almost negligible and following Poisson-like behavior against the number of incident photons. Conclusion A novel RLI approach for real time small animal dosimetry was developed. Results show a good agreement with MC dose calculations and linearity with respect to dose. We conclude that RLI can be an alternative approach to gafchromic films EP-1698 TRAPS upstream transmission detector for tracking mlc positions in VMAT and IMRT radiotherapy fields S. Fletcher 1 , J. Haynes 2 , L. Beck 3 , J. Velthuis 4 , D. Crawford 5 1 University Hospitals Bristol, Medical Physics Radiotherapy, Bristol, United Kingdom ; 2 University Hospitals Bristol, Medical Physics- radiotherapy, Brsitol, United Kingdom ; 3 University of Bristol, Physics, Brsitol, United Kingdom ; 4 University of Bristol, Physics, Bristol, United Kingdom ; 5 University Hospitals Bristol, Medical Physics, Bristol, United Kingdom Purpose or Objective Complex dynamic radiotherapy treatment techniques such as VMAT and IMRT present a challenge for beam delivery verification. The TRAPS detector is a prototype device designed for high precision detection of multi-leaf collimator position that could be suitable for real-time upstream monitoring of patients’ treatments. We have evaluated its performance within a radiotherapy treatment beam. Material and Methods The TRAPS detector comprises a Monolithic Active Pixel Sensor (MAPS), sensor readout electronics and DAQ, and can be mounted on a holder attached to the linac head. Raw pixel data is pre-processed (bad pixel removal,

Visual examination of TRAPS images (thin rectangular fields with known errors) identified leaf positioning errors as small as 0.5mm, which is within the accuracy of leaf position calibration (1mm). The dynamic leaf tests demonstrated that TRAPS is capable of tracking leaf movement at velocities up to 3.5cm/s Figure 2.

Conclusion The prototype TRAPS detector has a low attenuation, so is suitable for locating upstream in a treatment beam, and can accurately delineate leaf edges for a range of