Analysis of a free-running synchronization artifact correction for MV-imaging with aSi:H flat panels

Deep learning-augmented radiotherapy visualization with a cylindrical radioluminescence system

This study aims to demonstrate a low-cost camera-based radioluminescence imaging system (CRIS) for high-quality beam visualization that encourages accurate pre-treatment verifications on radiation delivery in external beam radiotherapy. To ameliorate the optical image that suffers from mirror glare and edge blurring caused by photon scattering, a deep learning model is proposed and trained to learn from an on-board electronic portal imaging device (EPID). Beyond the typical purposes of an on-board EPID, the developed system maintains independent measurement with co-planar detection ability by involving a cylindrical receptor. Three task-aware modules are integrated into the network design to enhance its robustness against the artifacts that exist in an EPID running at the cine mode for efficient image acquisition. The training data consists of various designed beam fields that were modulated via the multi-leaf collimator (MLC). Validation experiments are performed for five regular fields ranging from 2 × 2 cm² to 10 × 10 cm² and three clinical IMRT cases. The captured CRIS images are compared to the high-quality images collected from an EPID running at the integration-mode, in terms of gamma index and other typical similarity metrics. The mean 2%/2 mm gamma pass rate is 99.14% (range between 98.6% and 100%) and 97.1% (ranging between 96.3% and 97.9%), for the regular fields and IMRT cases, respectively. The CRIS is further applied as a tool for MLC leaf-end position verification. A rectangular field with introduced leaf displacement is designed, and the measurements using CRIS and EPID agree within 0.100 mm ± 0.072 mm with maximum of 0.292 mm. Coupled with its simple system design and low-cost nature, the technique promises to provide viable choice for routine quality assurance in radiation oncology practice.

Use of electronic portal imaging devices for electron treatment verification

This study aims to help broaden the use of electronic portal imaging devices (EPIDs) for pre-treatment patient positioning verification, from photon-beam radiotherapy to photon- and electron-beam radiotherapy, by proposing and testing a method for acquiring clinically-useful EPID images of patient anatomy using electron beams, with a view to enabling and encouraging further research in this area. EPID images used in this study were acquired using all available beams from a linac configured to deliver electron beams with nominal energies of 6, 9, 12, 16 and 20 MeV, as well as photon beams with nominal energies of 6 and 10 MV. A widely-available heterogeneous, approximately-humanoid, thorax phantom was used, to provide an indication of the contrast and noise produced when imaging different types of tissue with comparatively realistic thicknesses. The acquired images were automatically calibrated, corrected for the effects of variations in the sensitivity of individual photodiodes, using a flood field image. For electron beam imaging, flood field EPID calibration images were acquired with and without the placement of blocks of water-equivalent plastic (with thicknesses approximately equal to the practical range of electrons in the plastic) placed upstream of the EPID, to filter out the primary electron beam, leaving only the bremsstrahlung photon signal. While the electron beam images acquired using a standard (unfiltered) flood field calibration were observed to be noisy and difficult to interpret, the electron beam images acquired using the filtered flood field calibration showed tissues and bony anatomy with levels of contrast and noise that were similar to the contrast and noise levels seen in the clinically acceptable photon beam EPID images. The best electron beam imaging results (highest contrast, signal-to-noise and contrast-to-noise ratios) were achieved when the images were acquired using the higher energy electron beams (16 and 20 MeV) when the EPID was calibrated using an intermediate (12 MeV) electron beam energy. These results demonstrate the feasibility of acquiring clinically-useful EPID images of patient anatomy using electron beams and suggest important avenues for future investigation, thus enabling and encouraging further research in this area. There is manifest potential for the EPID imaging method proposed in this work to lead to the clinical use of electron beam imaging for geometric verification of electron treatments in the future.

An independent system for real-time dynamic multileaf collimation trajectory verification using EPID

A new tool has been developed to verify the trajectory of dynamic multileaf collimators (MLCs) used in advanced radiotherapy techniques using only the information provided by the electronic portal imaging devices (EPID) measured image frames. The prescribed leaf positions are resampled to a higher resolution in a pre-processing stage to improve the verification precision. Measured MLC positions are extracted from the EPID frames using a template matching method. A cosine similarity metric is then applied to synchronise measured and planned leaf positions for comparison. Three additional comparison functions were incorporated to ensure robust synchronisation. The MLC leaf trajectory error detection was simulated for both intensity modulated radiation therapy (IMRT) (prostate) and volumetric modulated arc therapy (VMAT) (head-and-neck) deliveries with anthropomorphic phantoms in the beam. The overall accuracy for MLC positions automatically extracted from EPID image frames was approximately 0.5 mm. The MLC leaf trajectory verification system can detect leaf position errors during IMRT and VMAT with a tolerance of 3.5 mm within 1 s.

Image quality improvements of electronic portal imaging devices by multi-level gain calibration and temperature correction

Amorphous silicon (aSi:H) flat panel detectors are prevalent in radiotherapy for megavoltage imaging tasks. Any clinical and dosimetrical application requires a well-defined dose response of the system to achieve meaningful results. Due to radiation damages, panels deteriorate and the linearity of pixel response to dose as well as the stability with regard to changing operating temperatures get worse with time. Using a single level gain correction can lead to an error of about 23% when irradiating a flood field image with 100 MU min(-1) on an old detector. A multi-level gain (MLG) correction is introduced, emending the nonlinearities and subpanel-related artifacts caused by insufficient radiation hardness of amplifiers in the read-out electronics. With rising temperature, offset values typically increase (up to 300 gray values) while the response at higher dose values per frame remain constant for a majority of pixels. To account for temperature-related image artifacts, two additional temperature correction methods have been developed. MLG in combination with temperature corrections can re-establish the aSi:H image quality to the performance required by reliable medical verification tools. Furthermore, the life span and recalibration intervals of these costly devices can be prolonged decisively.