Calvin R. Maurer

The CyberKnife Robotic Radiosurgery System in 2010.

This review provides a complete technical description of the CyberKnife® VSI™ System, the latest addition to the CyberKnife product family, which was released in September 2009. This review updates the previous technical reviews of the original system version published in the late 1990s. Technical developments over the last decade have impacted virtually every aspect of the CyberKnife System. These developments have increased the geometric accuracy of the system and have enhanced the dosimetric accuracy and quality of treatment, with advanced inverse treatment planning algorithms, rapid Monte Carlo dose calculation, and post-processing tools that allow trade-offs between treatment efficiency and dosimetric quality to be explored. This review provides a system overview with detailed descriptions of key subsystems. A detailed review of studies of geometric accuracy is also included, reporting a wide range of experiments involving phantom tests and patient data. Finally, the relationship between technical developments and the greatly increased range of clinical applications they have allowed is reviewed briefly.

Xsight Lung Tracking System: A Fiducial-Less Method for Respiratory Motion Tracking

The CyberKnife® Robotic Radiosurgery System (Accuray Incorporated, Sunnyvale, CA) can treat targets that move with respiration using the Synchrony® Respiratory Tracking System (Accuray Incorporated, Sunnyvale, CA). Alignment of each treatment beam with the moving target is maintained in real time by moving the beam dynamically with the target. The Synchrony system requires fiducials that are placed in or near the tumor to target the lesion and track it as it moves with respiration. The Xsightℳ (Accuray Incorporated, Sunnyvale, CA) Lung Tracking System, which recently became available for the CyberKnife system, is a direct soft tissue tracking method for respiratory motion tracking of lung lesions that eliminates invasive fiducial implantation procedures, thereby decreasing the time to treatment and eliminating the risk of pneumothorax and other fiducial placement complications. This chapter presents the concepts, methods, and some experimental results of the Xsight Lung Tracking System, which is fully integrated with the Synchrony Respiratory Tracking System. Observation and analysis of clinical image data for patients previously treated with the CyberKnife indicates that many reasonably large tumors (larger than 15 mm) located in the peripheral and apex lung regions are visible in orthogonal X-ray images acquired by the CyberKnife system. Direct tumor tracking can be performed for such visible tumors by registration of the tumor region in digitally reconstructed radiographs (DRRs), generated from the planning CT image, to the corresponding region in the treatment X-ray images. Image processing is used to enhance the visibility of the lung tumor in the DRRs and X-ray images. Experiments with an anthropomorphic motion phantom and retrospective analysis of clinical image data obtained from patients who underwent CyberKnife treatment for lung lesions using implanted fiducial markers show that the accuracy of Xsight Lung tracking is better than 1.5 mm.

Reconstruction of the treatment area by use of sinogram in helical tomotherapy

BackgroundTomoTherapy (Accuray, USA) has an image-guided radiotherapy system with a megavoltage (MV) X-ray source and an on-board imaging device. This system allows one to acquire the delivery sinogram during the actual treatment, which partly includes information from the irradiated object. In this study, we try to develop image reconstruction during treatment with helical tomotherapy.FindingsSinogram data were acquired during helical tomotherapy delivery using an arc-shaped detector array that consists of 576 xenon-gas filled detector cells. In preprocessing, these were normalized with full air-scan data. A software program was developed that reconstructs 3D images during treatment with corrections as; (1) the regions outside the field were masked not to be added in the backprojection (a masking correction), and (2) each voxel of the reconstructed image was divided by the number of the beamlets passing through its voxel (a ray-passing correction).The masking correction produced a reconstructed image, however, it contained streak artifacts. The ray-passing correction reduced this artifact. Although the SNR (the ratio of mean to standard deviation in a homogeneous region) and the contrast of the reconstructed image were slightly improved with the ray-passing correction, use of only the masking correction was sufficient for the visualization purpose.ConclusionsThe visualization of the treatment area was feasible by using the sinogram in helical tomotherapy. This proposed method would be useful in the treatment verification.

SU‐GG‐T‐544: Delivery Time Minimization for Robotic Radiosurgery and IMRT Treatments

Purpose:Roboticradiation delivery systems can accurately deliver conformal dose distributions for clinical applications throughout the body. Here we describe methods to reduce treatment times for step‐and‐shoot roboticradiation delivery while maintaining the dosimetric quality of the treatment plan. Method and Materials:Treatment delivery time, excluding patient setup, depends primarily on three parameters: beam‐on time, number of positions (called nodes) of the linear accelerator, and the number of beams delivered per node. New optimization techniques reduce treatment time by direct reduction of the number of nodes and beams. These techniques iteratively remove low‐utility nodes and beams from the solution space and optimize the beam weights of the remaining beams. Annealing schedules are developed based on a user‐specified treatment time and the number of nodes in the solution set. The algorithms were evaluated on plans for standard fractionated prostate roboticIMRT, hypo‐fractionated prostate radiosurgery, spine radiosurgery, and lungSBRT.Results: The algorithms reduced treatment delivery times (excluding patient setup time) per fraction by as much as 60% for prostate roboticIMRT, 35% for prostate radiosurgery, 25% for spine radiosurgery, and 50% for lungSBRT. The implementation of the new optimization features allows the user to explore trade‐offs in treatment plan quality and delivery time by generating a family of plans that correspond to varying treatment times. Substantial time reductions were obtained for most cases while maintaining plan quality and meeting established clinical criteria (e.g., RTOG‐0238 for prostate radiotherapy and RTOG‐0618 for lungradiosurgery). Although the number of nodes was reduced, the remaining nodes still encompassed a large non‐coplanar workspace. Conclusion: New optimization techniques are described that significantly reduce delivery times for roboticradiosurgery,SBRT, and IMRTtreatments. Reduced treatment times increase patient throughput and improve patient comfort. Conflict of Interest: The authors are employed by Accuray Incorporated, Sunnyvale, CA.

SU-GG-J-24: Retrospective Clinical Data Analysis of Fiducial-Free Lung Tracking

Purpose: To present the algorithmic approach used in the Xsight® LungTracking System (XLT; Accuray Incorporated, Sunnyvale, CA) of the CyberKnife® RoboticRadiosurgery System (Accuray Incorporated) and to quantify the expected proportion of lungradiosurgery candidates suitable for fiducial‐free motion‐compensated treatment using orthogonal kV imaging.Method and Materials: The XLT system was recently enhanced with the goal of increasing the proportion of lung lesions that can be tracked in orthogonal kV x‐ray image pairs without fiducials. These enhancements include digitally reconstructedradiographs generated from local tumor neighborhoods, an automatic preferred projection epipolar constraint, tumor template matching allowing for in‐plane rotations, and automatic x‐ray image enhancement. An extensive multi‐institutional (M=5) cohort of patients (N=103) was retrospectively analyzed to quantify fiducial‐free target localization performance for lungtumors spanning a broad range of anatomical locations and sizes (largest dimension ranged from 10 to 100 mm). This analysis evaluated 7,565 x‐ray image pairs to quantify the localization performance of the XLT system in comparison to fiducial localization as a gold standard. Clinical cases were categorized as “fiducial‐free candidates” when XLT localization satisfied preset accuracy, quality assurance and detection confidence metrics in over 75% of the tested image pairs. Results: A total of 57 out of 103 cases (55.3%) were found to be suitable candidates for fiducial‐free treatment. The site‐specific fiducial‐free candidate ratios ranged from 40% to 78% of all lungradiosurgery candidates, reflecting variability in patient population, tumor locations and sizes (algorithm works best for tumors larger than 15 mm in diameter), and x‐ray imaging technique. Conclusion: This study demonstrates that fiducial‐free localization and motion compensation can be achieved in over half of lungradiosurgery candidates using the recently enhanced XLT system, while maintaining tracking accuracy comparable to that obtained using implanted fiducial markers. Conflict of Interest: The authors are employed by Accuray Incorporated.

WE‐E‐AUD B‐02: Validation Tests for CyberKnife® Monte Carlo Dose Calculations Using Heterogeneous Phantoms

Purpose: To validate the Monte Carlo dose calculation algorithm for the CyberKnife® RoboticRadiosurgery System (Accuray Inc.) in the MultiPlan® Treatment Planning System. Method and Materials: Dose was measured in heterogeneous phantoms for clinically relevant dosimetry situations and compared with Monte Carlo dose calculations. The validation tests involve dose measurements in slab phantoms for single beams as well as multiple beams delivered on phantoms such as a modified Accuray ball cube and the RPC thorax‐lung phantom. Depth doses as well as dose distributions at the inhomogeneity boundaries were measured. Single beam tests were performed for four collimator sizes (5, 10, 30, and 60 mm). Measurements were performed primarily with EBT films and complemented with MOSFETs at inhomogeneity interfaces. Results: 1) EBT film and MOSFET measurements at the tissue inhomogeneities show excellent agreements in all phantoms and for all collimators in both orthogonal and oblique incidences. 2) The Monte Carlo depth dose calculations in heterogeneous phantoms show excellent agreements with measurements. For example, the depth doses in water‐lung‐water phantom show a drop in the lung region that was predicted very well by the Monte Carlo calculation. 3) The treatment plans delivered to the heterogeneous ball cube and RPC thorax‐lung phantom show excellent agreements between radiochromic film measurements and Monte Carlo calculations. Conclusion: The tests and phantoms collectively cover a wide range of tissue types (including air and lung, water, and bone‐equivalent materials), angles of incidence of beams to tissue interfaces, collimator sizes, and single and multiple beam situations. A total of 91 tests were performed and in 83 (91%) of these tests, 90% or more pixels pass γ(2% dose difference, 2 mm distance‐to‐agreement) condition.

SU‐GG‐T‐507: 4D Planning: Dose Calculation That Accounts for Moving Beams and Tissue Deformation

Purpose: To evaluate the ability of 4D Treatment Optimization and Planning, which is a recently available feature in the MultiPlan® Treatment Planning System for 4D treatment planning for motion tracking with the CyberKnife® RoboticRadiosurgery System, to calculate a dose distribution that takes into account both beam movement due to respiratory motion and soft tissue deformation. Method and Materials: A phantom was developed for 4D planning validation, containing a target that exhibits periodic motion driven by a motor, and a critical structure adjacent to the target. A 4D CT scan of the phantom in motion was obtained, and a treatment plan created on this 4D CT scan using MultiPlan with the 4D Planning module. The target has fiducials embedded in it, and Synchrony® Respiratory Motion Tracking System was used so that the treatment beams followed the target motion. Radiochromic film was placed in the critical structure and the treatment plan was delivered. The film dose after treatment was compared with that calculated by MultiPlan using both the static dose calculation (3D dose) and that calculated using the 4D Planning module. The 4D Planning module uses deformable registration and information about beam movement to calculate a dose distribution that takes into account both target movement and tissue deformation during treatment (4D dose). Results: For the 3D dose in the coronal film, 64.4% of pixels had a disagreement of 3% or less between measured and predicted dose; for the 4D dose distribution, 97.6% of pixels had a disagreement of 3% or less. Using a Gamma function with a passing criterion of 5% dose difference or 3mm distance to agreement, 94.9% of pixels pass for the 3D dose and 100.0% of pixels pass for 4D dose. Conclusion: The 4D Planning module accurately calculated dose in this phantom test for a moving target.

Fast and robust adaptation of organs-at-risk delineations from planning scans to match daily anatomy in pre-treatment scans for online-adaptive radiotherapy of abdominal tumors

PURPOSE To validate a novel deformable image registration (DIR) method for online adaptation of planning organ-at-risk (OAR) delineations to match daily anatomy during hypo-fractionated RT of abdominal tumors. MATERIALS AND METHODS For 20 liver cancer patients, planning OAR delineations were adapted to daily anatomy using the DIR on corresponding repeat CTs. The DIRs accuracy was evaluated for the entire cohort by comparing adapted and expert-drawn OAR delineations using geometric (Dice Similarity Coefficient (DSC), Modified Hausdorff Distance (MHD) and Mean Surface Error (MSE)) and dosimetric (Dmax and Dmean) measures. RESULTS For all OARs, DIR achieved average DSC, MHD and MSE of 86%, 2.1 mm, and 1.7 mm, respectively, within 20 s for each repeat CT. Compared to the baseline (translations), the average improvements ranged from 2% (in heart) to 24% (in spinal cord) in DSC, and 25% (in heart) to 44% (in right kidney) in MHD and MSE. Furthermore, differences in dose statistics (Dmax, Dmean and D2%) using delineations from an expert and the proposed DIR were found to be statistically insignificant (p > 0.01). CONCLUSION The validated DIR showed potential for online-adaptive radiotherapy of abdominal tumors as it achieved considerably high geometric and dosimetric correspondences with the expert-drawn OAR delineations, albeit in a fraction of time required by experts.

Feasibility of real‐time motion management with helical tomotherapy

PURPOSE This study investigates the potential application of image-based motion tracking and real-time motion correction to a helical tomotherapy system. METHODS A kV x-ray imaging system was added to a helical tomotherapy system, mounted 90 degrees offset from the MV treatment beam, and an optical camera system was mounted above the foot of the couch. This experimental system tracks target motion by acquiring an x-ray image every few seconds during gantry rotation. For respiratory (periodic) motion, software correlates internal target positions visible in the x-ray images with marker positions detected continuously by the camera, and generates an internal-external correlation model to continuously determine the target position in three-dimensions (3D). Motion correction is performed by continuously updating jaw positions and MLC leaf patterns to reshape (effectively re-pointing) the treatment beam to follow the 3D target motion. For motion due to processes other than respiration (e.g., digestion), no correlation model is used - instead, target tracking is achieved with the periodically acquired x-ray images, without correlating with a continuous camera signal. RESULTS The systems ability to correct for respiratory motion was demonstrated using a helical treatment plan delivered to a small (10 mm diameter) target. The phantom was moved following a breathing trace with an amplitude of 15 mm. Film measurements of delivered dose without motion, with motion, and with motion correction were acquired. Without motion correction, dose differences within the target of up to 30% were observed. With motion correction enabled, dose differences in the moving target were less than 2%. Nonrespiratory system performance was demonstrated using a helical treatment plan for a 55 mm diameter target following a prostate motion trace with up to 14 mm of motion. Without motion correction, dose differences up to 16% and shifts of greater than 5 mm were observed. Motion correction reduced these to less than a 6% dose difference and shifts of less than 2 mm. CONCLUSIONS Real-time motion tracking and correction is technically feasible on a helical tomotherapy system. In one experiment, dose differences due to respiratory motion were greatly reduced. Dose differences due to nonrespiratory motion were also reduced, although not as much as in the respiratory case due to less frequent tracking updates. In both cases, beam-on time was not increased by motion correction, since the system tracks and corrects for motion simultaneously with treatment delivery.

SU-E-J-203: Reconstruction of the Treatment Area by Use of Sinogram in Helical Tomotherapy

PURPOSE TomoTherapy (Accuray Co.) has an image-guided radiotherapy system with megavoltage (MV) X-ray source and the on-board imaging device. With the MV computed tomography (MVCT), it became feasible to perform the efficient daily-3D registration of the patient position before each treatment delivery. This system also allows one to acquire the delivery sinogram during the actual treatment, which partly includes the information of the irradiated object. In this study, we try to develop the image reconstruction during treatment in helical Tomotherapy. METHODS Sinogram data were acquired during helical Tomotherapy delivery using an arc-shaped detector array that consists of 738 xenon-gas filled detector cells. In preprocessing, these were normalized by full air-scan data. A software program was developed that reconstructs 3D images during treatment with corrections as; (1) the regions outside the field were masked not to be added in the backprojection (a masking correction), and (2) each voxel of the reconstructed image was divided by the number of the X-ray passing through its voxel (a ray-passing correction). RESULTS Without masking and ray-passing corrections, the image reconstruction was failed. The masking correction made the image clear, however, the streak artifact was accompanied. The ray-passing correction reduced this artifact. Although the SNR (the ratio of mean to standard deviation in homogeneous region) and the contrast of the reconstructed image were slightly improved with the ray-passing correction, the masking correction only is enough for the visualization purpose. CONCLUSION The visualization of the treatment area was feasible by use of the sinogram in helical Tomotherapy. This proposed method can be utilized in the treatment verification. This work was partly supported by JSPS KAKENHI 24234567. No COI, but the data in this paper were prepared by collaborators in Accuray.