A 3D printed modular phantom for quality assurance of image-guided small animal irradiators: Design, imaging experiments, and Monte Carlo simulations.

PURPOSE: The goal of this work was to develop and test a cylindrical tissue-equivalent quality assurance (QA) phantom for micro computed tomography (microCT) image-guided small animal irradiators that overcomes deficiencies of existing phantoms due to its mouse-like dimensions and composition. METHODS: The 8.6-cm-long and 2.4-cm-diameter phantom was three-dimensionally (3D) printed out of Somos NeXt plastic on a stereolithography (SLA) printer. The modular phantom consisted of four sections: (a) CT number evaluation section, (b) spatial resolution with slanted edge (for the assessment of longitudinal resolution) and targeting section, (c) spatial resolution with hole pattern (for the assessment of radial direction) section, and (d) uniformity and geometry section. A Python-based graphical user interface (GUI) was developed for automated analysis of microCT images and evaluated CT number consistency, longitudinal and radial modulation transfer function (MTF), image uniformity, noise, and geometric accuracy. The phantom was placed at the imaging isocenter and scanned with the small animal radiation research platform (SARRP) in the pancake geometry (long axis of the phantom perpendicular to the axis of rotation) with a variety of imaging protocols. Tube voltage was set to 60 and 70 kV, tube current was set to 0.5 and 1.2 mA, voxel size was set to 200 and 275 µm, imaging times of 1, 2, and 4 min were used, and frame rates of 6 and 12 frames per second (fps) were used. The phantom was also scanned in the standard (long axis of the phantom parallel to the axis of rotation) orientation. The quality of microCT images was analyzed and compared to recommendations presented in our previous work that was derived from a multi-institutional study. Additionally, a targeting accuracy test with a film placed in the phantom was performed. MicroCT imaging of the phantom was also simulated in a modified version of the EGSnrc/DOSXYZnrc code. Images of the resolution section with the hole pattern were acquired experimentally as well as simulated in both the pancake and the standard imaging geometries. The radial spatial resolution of the experimental and simulated images was evaluated and compared to experimental data. RESULTS: For the centered phantom images acquired in the pancake geometry, all imaging protocols passed the spatial resolution criterion in the radial direction (>1.5 lp/mm @ 0.2 MTF), the geometric accuracy criterion (<200 µm), and the noise criterion (<55 HU). Only the imaging protocol with 200-µm voxel size passed the criterion for spatial resolution in the longitudinal direction (>1.5 lp/mm @ 0.2 MTF). The 70-kV tube voltage dataset failed the bone CT number consistency test (<55 HU). Due to cupping artifacts, none of the imaging protocols passed the uniformity test of <55 HU. When the phantom was scanned in the standard imaging geometry, image uniformity and longitudinal MTF were satisfactory; however, the CT number consistency failed the recommended limit. A targeting accuracy of 282 and 251 µm along the x- and z-direction was observed. Monte Carlo simulations confirmed that the radial spatial resolution for images acquired in the pancake geometry was higher than the one acquired in the standard geometry. CONCLUSIONS: The new 3D-printed phantom presents a useful tool for microCT image analysis as it closely mimics a mouse. In order to image mouse-sized animals with acceptable image quality, the standard protocol with a 200-µm voxel size should be chosen and cupping artifacts need to be resolved.

Multi-institutional MicroCT image comparison of image-guided small animal irradiators.

To recommend imaging protocols and establish tolerance levels for microCT image quality assurance (QA) performed on conformal image-guided small animal irradiators. A fully automated QA software SAPA (small animal phantom analyzer) for image analysis of the commercial Shelley micro-CT MCTP 610 phantom was developed, in which quantitative analyses of CT number linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, spatial resolution by means of modulation transfer function (MTF), and CT contrast were performed. Phantom microCT scans from eleven institutions acquired with four image-guided small animal irradiator units (including the commercial PXi X-RAD SmART and Xstrahl SARRP systems) with varying parameters used for routine small animal imaging were analyzed. Multi-institutional data sets were compared using SAPA, based on which tolerance levels for each QA test were established and imaging protocols for QA were recommended. By analyzing microCT data from 11 institutions, we established image QA tolerance levels for all image quality tests. CT number linearity set to R 2 > 0.990 was acceptable in microCT data acquired at all but three institutions. Acceptable SNR > 36 and noise levels <55 HU were obtained at five of the eleven institutions, where failing scans were acquired with current-exposure time of less than 120 mAs. Acceptable spatial resolution (>1.5 lp mm-1 for MTF = 0.2) was obtained at all but four institutions due to their large image voxel size used (>0.275 mm). Ten of the eleven institutions passed the set QA tolerance for geometric accuracy (<1.5%) and nine of the eleven institutions passed the QA tolerance for contrast (>2000 HU for 30 mgI ml-1). We recommend performing imaging QA with 70 kVp, 1.5 mA, 120 s imaging time, 0.20 mm voxel size, and a frame rate of 5 fps for the PXi X-RAD SmART. For the Xstrahl SARRP, we recommend using 60 kVp, 1.0 mA, 240 s imaging time, 0.20 mm voxel size, and 6 fps. These imaging protocols should result in high quality images that pass the set tolerance levels on all systems. Average SAPA computation time for complete QA analysis for a 0.20 mm voxel, 400 slice Shelley phantom microCT data set was less than 20 s. We present image quality assurance recommendations for image-guided small animal radiotherapy systems that can aid researchers in maintaining high image quality, allowing for spatially precise conformal dose delivery to small animals.

Assessment and management of radiotherapy beam intersections with the treatment couch.

The impact of the treatment couch on a radiotherapy plan is rarely fully assessed during the treatment planning process. Incorporating a couch model into the treatment planning system (TPS) enables the planner to avoid or dosimetrically evaluate beam-couch intersections. In this work, we demonstrate how existing TPS tools can be used to establish this capability and assess the accuracy and effectiveness of the system through dose measurements and planning studies. Such capabilities may be particularly relevant for the planning of arc therapies.Treatment couch top models were introduced into a TPS by fusing their CT image sets with the patient CT dataset. Regions of interest characterizing couch elements were then imported and assigned appropriate densities in the TPS. Measurements in phantom agreed with TPS calculations to within 2% dose and 1 degrees gantry rotation. To clinically validate the model, a retrospective study was performed on patient plans that posed difficulties in beam-couch intersection during setup. Beam-couch intersection caused up to a 3% reduction in PTV coverage, defined by the 95% of the prescribed dose, and up to a 1% reduction in mean CTV coverage. Dose compensation strategies for IMRT treatments with beams passing through couch elements were investigated using a four-field IMRT plan with three beams passing through couch elements. In this study, ignoring couch effects resulted in point dose reductions of 8 +/- 3%.A methodology for incorporating detailed couch characteristics into a TPS has been established and explored. The method can be used to predict beam-couch intersections during planning, potentially eliminating the need for pretreatment appointments. Alternatively, if a beam-couch intersection problem arises, the impact of the couch can be assessed on a case-by-case basis and a clinical decision made based on full dosimetric information.