A priori patient-specific collision avoidance in radiotherapy using consumer grade depth cameras

A quantitative framework for patient-specific collision detection in proton therapy

BACKGROUND

Beam modifying accessories for proton therapy often need to be placed in close proximity of the patient for optimal dosimetry. However, proton treatment units are larger in size and as a result the planned treatment geometry may not be achievable due to collisions with the patient. A framework that can accurately simulate proton treatment geometry is desired.

PURPOSE

A quantitative framework was developed to model patient-specific proton treatment geometry, minimize air gap, and avoid collisions.

METHODS

The patient's external contour is converted into the International Electrotechnique Commission (IEC) gantry coordinates following the patient's orientation and each beam's gantry and table angles. All snout components are modeled by three-dimensional (3D) geometric shapes such as columns, cuboids, and frustums. Beam-specific parameters such as isocenter coordinates, snout type and extension are used to determine if any point on the external contour protrudes into the various snout components. A 3D graphical user interface is also provided to the planner to visualize the treatment geometry. In case of a collision, the framework's analytic algorithm quantifies the maximum protrusion of the external contour into the snout components. Without a collision, the framework quantifies the minimum distance of the external contour from the snout components and renders a warning if such distance is less than 5 cm.

RESULTS

Three different snout designs are modeled. Examples of potential collision and its aversion by snout retraction are demonstrated. Different patient orientations, including a sitting treatment position, as well as treatment plans with multiple isocenters, are successfully modeled in the framework. Finally, the dosimetric advantage of reduced air gap enabled by this framework is demonstrated by comparing plans with standard and reduced air gaps.

CONCLUSION

Implementation of this framework reduces incidence of collisions in the treatment room. In addition, it enables the planners to minimize the air gap and achieve better plan dosimetry.

Implementation of a Stereoscopic Camera System for Clinical Electron Simulation and Treatment Planning

PURPOSE

A 3-dimensinal (3D) stereoscopic camera system developed by .decimal was commissioned and implemented into the clinic to improve the efficiency of clinical electron simulations. Capabilities of the camera allowed simulations to be moved from the treatment vault into any room with a flat surface that could accommodate patient positioning devices, eliminating the need for clinical patient setup timeslots on the treatment machine. This work describes the process used for these simulations and compares the treatment parameters determined by the system to those used in delivery.

METHODS AND MATERIALS

The Decimal3D scanner workflow consisted of: scanning the patient surface; contouring the treatment area; determining gantry, couch, collimator, and source-to-surface distance (SSD) parameters for en face entry of the beam with sufficient clearance at the machine; and ordering custom electron cutouts when needed. Transparencies showing the projection of in-house library cutouts at various clinical SSDs were created to assist in choosing an appropriate library cutout. Data from 73 treatment sites were analyzed to evaluate the accuracy of the scanner-determined beam parameters for each treatment delivery.

RESULTS

Clinical electron simulations for 73 treatment sites, predominately keloids, were transitioned out of the linear accelerator (LINAC) vault using the new workflow. For all patients, gantry, collimator, and couch parameters, along with SSD and cone size, were determined using the Decimal3D scanner with 57% of simulations using library cutouts. Tolerance tables for patient setup were updated to allow differences of 10, 20, and 5° for gantry, collimator, and couch, respectively. Approximately 7% of fractions (N = 181 total fractions) were set up outside of the tolerance table based on physician direction during treatment. This reflects physician preference to adjust the LINAC rather than patient position during treatment setup. No scanner-derived plan was untreatable because of cutout shape inaccuracy or clearance issues.

CONCLUSIONS

Clinical electron simulations were successfully transitioned out of the LINAC vault using the Decimal3D scanner without loss of setup accuracy, as measured through machine parameter determination and electron cutout shape.

A novel, end-to-end framework for avoiding collisions between the patient's body and gantry in proton therapy

BACKGROUND

Administration of external radiation therapy via proton therapy systems carries a risk of occasional collisions between the patient's body and gantry, which is increased by the snout placed near the patient for better dose distribution. Although treatment planning software (TPS) can simulate controlled collisions, the computed tomography (CT) data used for treatment planning are insufficient given that collisions can occur outside the CT imaging region. Thus, imaging the three-dimensional (3D) surface outside the CT range and combining the data with those obtained by CT are essential for avoiding collisions.

PURPOSE

To construct a prototype for 3D surface imaging and an end-to-end framework for preventing collisions between the patient's body and the gantry.

METHODS

We obtained 3D surface data using a light sectioning method (LSM). By installing only cameras in front of the CT, we achieved LSM using the CT couch motion and preinstalled patient-positioning lasers. The camera image contained both sagittal and coronal lines, which are unnecessary for LSM and were removed by deep learning. We combined LSM 3D surface data and original CT data to create synthetic Digital Imaging and Communications in Medicine (DICOM) data. Subsequently, we compared the TPS snout auto-optimization using the original CT data with the synthetic DICOM data.

RESULTS

The mean positional error for LSM of the arms and head was 0.7 ± 0.8  and 0.8 ± 0.8 mm for axial and sagittal imaging, respectively. The TPS snout auto-optimization indicated that the original CT data would cause collisions; however, the synthetic DICOM data prevented these collisions.

CONCLUSIONS

The prototype system's acquisition accuracy for 3D surface data was approximately 1 mm, which was sufficient for the collision simulation. The use of a TPS with collision avoidance can help optimize the snout position using synthetic DICOM data. Our proposed method requires no external software for collision simulation and can be integrated into the clinical workflow to improve treatment planning efficiency.

Technical note: A collision prediction tool using Blender

Non-coplanar radiotherapy treatment techniques on C-arm linear accelerators have the potential to reduce dose to organs-at-risk in comparison with coplanar treatment techniques. Accurately predicting possible collisions between gantry, table and patient during treatment planning is needed to ensure patient safety. We offer a freely available collision prediction tool using Blender, a free and open-source 3D computer graphics software toolset. A geometric model of a C-arm linear accelerator including a library of patient models is created inside Blender. Based on the model, collision predictions can be used both to calculate collision-free zones and to check treatment plans for collisions. The tool is validated for two setups, once with and once without a full body phantom with the same table position. For this, each gantry-table angle combination with a 2° resolution is manually checked for collision interlocks at a TrueBeam system and compared to simulated collision predictions. For the collision check of a treatment plan, the tool outputs the minimal distance between the gantry, table and patient model and a video of the movement of the gantry and table, which is demonstrated for one use case. A graphical user interface allows user-friendly input of the table and patient specification for the collision prediction tool. The validation resulted in a true positive rate of 100%, which is the rate between the number of correctly predicted collision gantry-table combinations and the number of all measured collision gantry-table combinations, and a true negative rate of 89%, which is the ratio between the number of correctly predicted collision-free combinations and the number of all measured collision-free combinations. A collision prediction tool is successfully created and able to produce maps of collision-free zones and to test treatment plans for collisions including visualisation of the gantry and table movement.

AAPM task group report 302: Surface guided radiotherapy

The clinical use of surface imaging has increased dramatically with demonstrated utility for initial patient positioning, real-time motion monitoring, and beam gating in a variety of anatomical sites. The Therapy Physics Subcommittee and the Imaging for Treatment Verification Working Group of the American Association of Physicists in Medicine commissioned Task Group 302 to review the current clinical uses of surface imaging and emerging clinical applications. The specific charge of this task group was to provide technical guidelines for clinical indications of use for general positioning, breast deep-inspiration breath-hold (DIBH) treatment, and frameless stereotactic radiosurgery (SRS). Additionally, the task group was charged with providing commissioning and on-going quality assurance (QA) requirements for surface guided radiation therapy (SGRT) as part of a comprehensive QA program including risk assessment. Workflow considerations for other anatomic sites and for computed tomography (CT) simulation, including motion management are also discussed. Finally, developing clinical applications such as stereotactic body radiotherapy (SBRT) or proton radiotherapy are presented. The recommendations made in this report, which are summarized at the end of the report, are applicable to all video-based SGRT systems available at the time of writing. Review current use of non-ionizing surface imaging functionality and commercially available systems. Summarize commissioning and on-going quality assurance (QA) requirements of surface image-guided systems, including implementation of risk or hazard assessment of surface guided radiotherapy as a part of a total quality management program (e.g., TG-100). Provide clinically relevant technical guidelines that include recommendations for the use of SGRT for general patient positioning, breast DIBH, and frameless brain SRS, including potential pitfalls to avoid when implementing this technology. Discuss emerging clinical applications of SGRT and associated QA implications based on evaluation of technology and risk assessment. This article is protected by copyright. All rights reserved.

Patient-Specific Collision Zones for 4π Trajectory Optimized Radiation Therapy

PURPOSE

The 4π methodology determines optimized non-coplanar sub arcs for stereotactic radiation therapy which minimize dose to organs-at-risk. Every combination of treatment angle is examined, but some angles are not appropriate as a collision would occur between the gantry and the couch or the gantry and the patient. Those combinations of couch and gantry angles are referred to as collision zones. A major barrier to applying 4π to stereotactic body radiation therapy (SBRT) is the unknown shape of the collision zones, which are significant as patients take up a large volume within the 4π sphere. This study presents a system which determines patient-specific collision zones, without additional clinical steps, to enable safe and deliverable non-coplanar treatment trajectories for SBRT patients.

METHODS

To augment patient's computed tomography (CT) scan, full body scans of patients in treatment position were acquired using an optical scanner. A library of a priori scans (N = 25) was created. Based on the patients treatment position and their body dimensions, a library scan is selected and registered to the CT scan of the patient. Next, a model of the couch and immobilization equipment is added to the patient model. This results in a patient model that is then aligned with a model of the treatment linac in a "virtual treatment room", where both components can be rotated to test for collisions. To test the collision detection algorithm, an end-to-end test was performed using a cranial phantom. The registration algorithm was tested by comparing the registered patient collision zones to those generated by using the patient's matching scan.

RESULTS

The collision detection algorithm was found to have a 97.80% accuracy, a 99.99% sensitivity and a 99.99% negative predictive value (NPV). Analysis of the registration algorithm determined that a 6 cm buffer was required to achieve a 99.65% mean sensitivity, where a sensitivity of unity is considered to be a requirement for safe treatment delivery. With a 6 cm buffer the mean accuracy was 86.70% and the mean NPV was 99.33%.

CONCLUSIONS

Our method of determining patient-specific collision zones can be accomplished with minimal user intervention based on an a priori library of body surface scans, thus enabling the safe application of 4π SBRT.

Design of a 3D patient-specific collision avoidance virtual framework for half-gantry proton therapy system

Introduction

This study presents a comprehensive collision avoidance framework based on three‐dimension (3D) computer‐aided design (CAD) modeling, a graphical user interface (GUI) as peripheral to the radiation treatment planning (RTP) environment, and patient‐specific plan parameters for intensity‐modulated proton therapy (IMPT).

Methods

A stand‐alone software application was developed leveraging the Varian scripting application programming interface (API) for RTP database object accessibility. The Collision Avoider software models the Hitachi ProBeat‐V half gantry design and the Kuka robotic couch with triangle mesh structures. Patient‐specific plan parameters are displayed in the collision avoidance software for potential proximity evaluation. The external surfaces of the patients and the immobilization devices are contoured based on computed tomography (CT) images. A “table junction‐to‐CT‐origin” (JCT) measurement is made for every patient at the time of CT simulation to accurately provide reference location of the patient contours to the treatment couch. Collision evaluations were performed virtually with the program during treatment planning to prevent four major types of collisional events: collisions between the gantry head and the treatment couch, gantry head and the patient's body, gantry head and the robotic arm, and collisions between the gantry head and the immobilization devices.

Results

The Collision Avoider software was able to accurately model the proton treatment delivery system and the robotic couch position. Commonly employed clinical beam configuration and JCT values were investigated. Brain and head and neck patients require more complex gantry and patient positioning system configurations. Physical measurements were performed to validate 3D CAD model geometry. Twelve clinical proton treatment plans were used to validate the accuracy of the software. The software can predict all four types of collisional events in our clinic since its full implementation in 2020.

Conclusion

A highly efficient patient‐specific collision prevention program for scanning proton therapy has been successfully implemented. The graphical program has provided accurate collision detection since its inception at our institution.

The role of surface-guided radiation therapy for improving patient safety

Emerging data indicates SGRT could improve safety and quality by preventing errors in its capacity as an independent system in the treatment room. The aim of this work is to investigate the utility of SGRT in the context of safety and quality. Three incident learning systems (ILS) were reviewed to categorize and quantify errors that could have been prevented with SGRT: SAFRON (International Atomic Energy Agency), UW-ILS (University of Washington) and AvIC (Skåne University Hospital). A total of 849/9737 events occurred during the pre-treatment review/verification and treatment stages. Of these, 179 (21%) events were predicted to have been preventable with SGRT. The most common preventable events were wrong isocentre (43%) and incorrect accessories (34%), which appeared at comparable rates among SAFRON and UW-ILS. The proportion of events due to wrong accessories was much smaller in the AvIC ILS, which may be attributable to the mandatory use of SGRT in Sweden. Several case scenarios are presented to demonstrate that SGRT operates as a valuable complement to other quality-improvement tools routinely used in radiotherapy. Cases are noted in which SGRT itself caused incidents. These were mostly related to workflow issues and were of low severity. Severity data indicated that events with the potential to be mitigated by SGRT were of higher severity for all categories except wrong accessories. Improved vendor integration of SGRT systems within the overall workflow could further enhance its clinical utility. SGRT is a valuable tool with the potential to increase patient safety and treatment quality in radiotherapy.

CT-Based Collision Prediction Software for External-Beam Radiation Therapy

Purpose

Beam angle optimization is a critical issue for modern radiotherapy (RT) and is a challenging task, especially for large body sizes and noncoplanar designs. Noncoplanar RT techniques may have dosimetric advantages but increase the risk of mechanical collision. We propose a software solution to accurately predict colliding/noncolliding configurations for coplanar and noncoplanar beams.

Materials and Methods

Individualized software models for two different linear accelerators were built to simulate noncolliding gantry orientations for phantom/patient subjects. The sizes and shapes of the accelerators were delineated based on their manuals and on-site measurements. The external surfaces of the subjects were automatically contoured based on computed tomography (CT) simulations. An Alderson Radiation Therapy phantom was used to predict the accuracy of spatial collision prediction by the software. A gantry collision problem encountered by one patient during initial setup was also used to test the validity of the software. Results: In the comparison between the software estimates and on-site measurements, the noncoplanar collision angles were all predicted within a 5-degree difference in gantry position. The confusion matrix was calculated for each of the two empty accelerator models, and the accuracies were 98.7% and 97.3%. The true positive rates were 97.7% and 96.9%, while the true negative rates were 99.8% and 97.9%, respectively. For the phantom study, the collision angles were predicted within a 5-degree difference. The software successfully predicted the collision problem encountered by the breast cancer patient in the initial setup position and generated shifted coordinates that were validated to correspond to a noncolliding geometry.

Conclusion

The developed software effectively and accurately predicted collisions for accelerator-only, phantom, and patient setups. This software may help prevent collisions and expand the range of spatially applicable beam angles.

An open-source platform for interactive collision prevention in photon and particle beam therapy treatment planning

We present an open-source platform to aid medical dosimetrists in preventing collisions between gantry head and patient or couch during photon or particle beam therapy treatment planning. This generic framework uses the native scripting interface of the particular planning software to import STL files of the treatment machine elements. These are visualized in 3D together with the contoured or scanned patient surface. A graphical dialog with sliders allows the interactive rotation of the gantry and couch, with real-time feedback. To prevent a future replanning, treatment planners can assess in advance and exclude beam angles resulting in a potential risk of collision. The software platform is publicly available on GitHub and has been validated for RayStation with actual patient plans. Furthermore, the incorporation of the complete patient geometry was tested with a 3D surface scan of a full-body phantom performed with a handheld smartphone. With this study, we aim at minimizing the risk of replanning due to collisions and thus of treatment delays and unscheduled consumption of manpower. The clinical workflow can be streamlined at no cost already at the treatment planning stage. By ensuring a real-time verification of the plan feasibility, the script might boost the use of optimal couch angles that a planner might shy away from otherwise.

Prediction of conical collimator collision for stereotactic radiosurgery

The purpose of this study is to predict the collision clearance distance of stereotactic cones with treatment setup devices in cone-based stereotactic radiosurgery (SRS). The BrainLAB radiosurgery system with a Frameless Radiosurgery Positioning Array and dedicated couch top was targeted in this study. The positioning array and couch top were scanned with CT simulators, and their outer contours of were detected. The minimum clearance distance was estimated by calculating the Euclidian distances between the surface of the SRS cones and the nearest surface of the outer contours. The coordinate transformation of the outer contour was performed by incorporating the Beam's Eye View at a planned arc range and couch angle. From the minimum clearance distance, the collision-free gantry ranges for each couch angle were sequentially determined. An in-house software was developed to calculate the clearance distance between the cone surface and the outer contours, and thus determine the occurrence of a collision. The software was extensively tested for various combinations of couch and arc angles at multiple isocenter locations for two combinations of cone-couch systems. A total of 50 arcs were used to validate the calculation accuracies of the software for each system. The calculated minimum distances and collision-free angles from the software were verified by physical measurements. The calculated minimum distances were found to agree with the measurements to within 0.3 ± 0.9 mm. The collision-free arc angles from the software also agreed with the measurements to within 1.1 ± 1.1° with a 5-mm safety margin for 20 arcs. In conclusion, the in-house software was able to calculate the minimum clearance distance with <1.0 mm accuracy and to determine the collision-free arc range for the cone-based BrainLab SRS system.

A collision prediction framework for noncoplanar radiotherapy planning and delivery

PURPOSE

Noncoplanar radiotherapy can provide significant dosimetric benefits. However, clinical implementation of such techniques is not fully realized, partially due to the absence of a collision prediction tool integrated into the clinical workflow. In this work, the feasibility of developing a collision prediction system (CPS) suitable for integration into clinical practice has been investigated.

METHODS

The CPS is based on a geometric model of the Linear Accelerator (Linac), and patient morphology acquired at the simulator using a combination of the planning CT scan and 3-D vision camera (Microsoft, Kinect) data. Physical dimensions of Linac components were taken to construct a geometric model. The Linac components include the treatment couch, gantry, and imaging devices. The treatment couch coordinates were determined based on a correspondence among the CT couch top, Linac couch, and the treatment isocenter location. A collision is predicted based on dot products between vectors denoting points in Linac components and patient morphology. Collision test cases were simulated with the CPS and experimentally verified using ArcCheck and Rando phantoms to simulate a patient.

RESULTS

For 111 collision test cases, the sensitivity and specificity of the CPS model were calculated to be 0.95 and 1.00, respectively. The CPS predicted collision states that left conservative margins, as designed, relative to actual collision locations. The average difference between the predicted and measured collision states was 2.3 cm for lateral couch movements. The predicted couch rotational position for a collision between the gantry and a patient analog differed from actual values on average by 3.8°. The magnitude of these differences is sufficient to account for interfractional patient positioning variations during treatment.

CONCLUSION

The feasibility of developing a CPS using geometric models and standard vector algebra has been investigated. This study outlines a framework for potential clinical implementation of a CPS for noncoplanar radiotherapy.

Collision prediction for intracranial stereotactic radiosurgery planning: An easy-to-implement analytical solution

PURPOSE

Gantry collision is a concern in linac-based stereotactic radiosurgery (SRS). Without collision screening, the planner may compromise optimal planning, unnecessary re-planning delays can occur, and incomplete treatments may be delivered. To address these concerns, we developed a software for collision prediction based on simple machine measurements.

MATERIALS AND METHODS

Three types of collision were identified; gantry-couch mount, gantry-couch and gantry-patient. Trigonometric formulas to calculate the distance from each potential point of collision to the gantry rotation axis were generated. For each point, collision occurs when that distance is greater than the gantry head to gantry rotational axis distance. The colliding arc for each point is calculated. A computer code incorporating these formulas was generated. The inputs required are the couch coordinates relative to the isocenter, the patient dimensions, and the presence or absence of a circular SRS collimator. The software outputs the collision-free gantry angles, and for each point, the shortest distance to the gantry or the colliding sector when collision is identified. The software was tested for accuracy on a TrueBEAM® machine equipped with BrainLab® accessories for 80 virtual isocenter-couch angle configurations with and without a circular collimator and a parallelepiped phantom.

RESULTS

The software predicted the absence of collision for 19 configurations. The mean absolute error between the measured and predicted gantry angle of collision for the remaining 61 cases was 0.86 (0.01-2.49).

CONCLUSION

This tool accurately predicted collisions for linac-based intracranial SRS and is easy to implement in any radiotherapy facility.

A practical method for predicting patient-specific collision in radiotherapy

Purpose

To develop a practical method for predicting patient‐specific collision during the treatment planning process.

Materials and method

Based on geometry information of the accelerator gantry and the location of plan isocenter, the collision‐free space region could be determined. In this study, collision‐free space region was simplified as a cylinder. Radius of cylinder was equal to the distance from isocenter to the collimator cover. The collision‐free space was converted and imported into treatment planning system (TPS) in the form of region of interest (ROI) which was named as ROISS. Collision was viewed and evaluated on the fusion images of patient's CT and ROIs in TPS. If any points of patient's body or couch fell beyond the safety space, collision would occur. This method was implemented in the Pinnacle TPS. The impact of safety margin on accuracy was also discussed. Sixty‐five plans of clinical patients were chosen for the clinical validation.

Results

When the angle of couch is zero, the ROISS displays as a series of circles on the cross section of the patient's CT. When the couch angle is not zero, ROISS is a series of ellipses in the transverse view of patient's CT. The ROISS can be generated quickly within five seconds after a single mouse click in TPS. Adding safety margin is an effective measure in preventing collisions from being undetected. Safety margin could increase negative predictive value (NPV) of test cases. Accuracy obtained was 96.3% with the 3 cm safety margin with 100% true positive collision detection.

Conclusion

This study provides a reliable, accurate, and fast collision prediction during the treatment planning process. Potential collisions can be discovered and prevented early before delivering. This method can integrate with the current clinical workflow without any additional required resources, and contribute to improvement in the safety and efficiency of the clinic.

Proton therapy delivery: what is needed in the next ten years?

Proton radiation therapy has been used clinically since 1952, and major advancements in the last 10 years have helped establish protons as a major clinical modality in the cancer-fighting arsenal. Technologies will always evolve, but enough major breakthroughs have been accomplished over the past 10 years to allow for a major revolution in proton therapy. This paper summarizes the major technology advancements with respect to beam delivery that are now ready for mass implementation in the proton therapy space and encourages vendors to bring these to market to benefit the cancer population worldwide. We state why these technologies are essential and ready for implementation, and we discuss how future systems should be designed to accommodate their required features.

Development and clinical implementation of eclipse scripting-based automated patient-specific collision avoidance software

PURPOSE

Increased use of Linac-based stereotactic radiosurgery (SRS), which requires highly noncoplanar gantry trajectories, necessitates the development of efficient and accurate methods of collision detection during the treatment planning process. This work outlines the development and clinical implementation of a patient-specific computed tomography (CT) contour-based solution that utilizes Eclipse Scripting to ensure maximum integration with clinical workflow.

METHODS

The collision detection application uses triangle mesh structures of the gantry and couch, in addition to the body contour of the patient taken during CT simulation, to virtually simulate patient treatments. Collision detection is performed using Binary Tree Hierarchy detection methods. Algorithm accuracy was first validated for simple cuboidal geometry using a calibration phantom and then extended to an anthropomorphic phantom simulation by comparing the measured minimum distance between structures to the predicted minimum distance for all allowable orientations. The collision space was tested at couch angles every 15° from 90 to 270 with the gantry incremented by 5° through the maximum trajectory. Receiver operating characteristic curve analysis was used to assess algorithm sensitivity and accuracy for predicting collision events. Following extensive validation, the application was implemented clinically for all SRS patients.

RESULTS

The application was able to predict minimum distances between structures to within 3 cm. A safety margin of 1.5 cm was sufficient to achieve 100% sensitivity for all test cases. Accuracy obtained was 94.2% with the 5 cm clinical safety margin with 100% true positive collision detection. A total of 88 noncoplanar SRS patients have been currently tested using the application with one collision detected and no undetected collisions occurring. The average time for collision testing per patient was 2 min 58 s.

CONCLUSIONS

A collision detection application utilizing patient CT contours was developed and successfully clinically implemented. This application allows collisions to be detected early during the planning process, avoiding patient delays and unnecessary resource utilization if detected during delivery.

Collision Risk Mitigation of Varian TrueBeam Linear Accelerator With Supplemental Live-View Cameras

BACKGROUND

Noncoplanar radiation therapy techniques such as 4π have potential dosimetric advantages but introduce complexities in treatment delivery that increase the risk for collision. Direct or remote visual confirmation of clearance is a safeguard against collisions of the gantry, couch, and patient. With our institution's Varian TrueBeam system, we identified configurations that cannot be visualized with the included closed-circuit television cameras. At our practice, electronic, portal imaging device (EPID) collision risk also exists because of the routine deployment to capture exit-dose images for treatment quality assurance. We propose a simple, cost-effective solution using network cameras to help eliminate blind spots that permits safe, noncoplanar arrangements with an EPID-acquired exit dose.

METHODS AND MATERIALS

Two Panasonic cameras were installed overhead while a third Panasonic camera was mounted onto the pedestal to monitor the couch undersurface. Live views from each camera were accessed with a web-based client. The EPID and gantry were visually assessed at 52 couch and gantry rotational angle configurations at 6 couch translational positions. Visibility was compared for the standard and supplemental camera setups at each configuration (χ² test).

RESULTS

Of the 294 assessable couch-gantry configurations, the standard camera setup had limited visibility of either gantry or EPID for 146 configurations compared with 72 configurations with additional cameras (51% blind-spot reduction; P < .01). An 87% blind-spot reduction was observed for our laterally centered, cranial-based, couch translational position (P < .01).

CONCLUSIONS

The supplemental cameras were simple, effective additions for collision detection, especially for noncoplanar radiation therapy with EPID-acquired, exit-dose imaging. Over half of the assessable noncoplanar configurations had blind spots using standard cameras, which was reduced to <25% with additional cameras. In practice, there were almost no blind spots for patients with brain tumors who were treated with our templated beam arrangements. Using live-view camera feeds, vault re-entry to visually confirm clearance was reduced approximately 10-fold, which increased the treatment efficiency. In the most recent 12 months, no collision or near-collision events have been reported.

Using a Somatosensory Controller to Assess Body Size for Size-Specific Dose Estimates in Computed Tomography

Computed tomography (CT) has been widely used in the healthcare environment. Presently, the radiation dose in CT is determined using the size-specific dose estimate (SSDE). Accurate assessment of individual's body size is essential for dose estimation. In this study, we integrated a somatosensory controller with a CT scanner to measure patient's anterior-posterior diameter (APD) and lateral diameter (LATD) and calculate the corresponding effective diameter (ED). A total of 108 individuals with an average age of 38.6 years were enrolled in this study. Microsoft Kinect was used to acquire the depth image of subjects. A grayscale-to-surface height conversion curve was created using acrylic sheets for APD estimation. The APD, LATD, and ED were measured and compared with the results obtained using F ruler and CT images. The mean absolute differences for APD, LATD, and ED between Kinect and F ruler measurements were 5.2%, 1.3%, and 2.5%, respectively, while those between Kinect and CT measurements were 8.8%, 2.6%, and 5.0%, respectively. Kinect can replace CT or F ruler for real-time body size measurements. The use of the somatosensory controller has the advantages of simple, low cost, no radiation, and automatic calculation. It can accurately estimate patient's APD, LATD, and ED for SSDE.