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Purpose Halcyon linear accelerators employ intensity‐modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT) techniques. The Halcyon offers translational, but not rotational, couch correction, which only allows a 3 degrees of freedom (3‐DOF) correction. In contrast, the TrueBeam (TB) linear accelerator offers full 6‐DOF corrections. This study aims to evaluate the difference in treatment plan quality for single thoracic or lumbar vertebral segment SBRT between the Halcyon and TB linear accelerators. In addition, this study will also investigate the effect of patient rotational setup errors on the final plan quality. Methods We analyzed 20 patients with a single‐level spine metastasis located between the T7 and L5 vertebrae near the spinal canal. The median planning target volume was 52.0 cm3 (17.9–138.7 cm3). The median tumor diameter in the axial plane was 4.6 cm (range 1.7–6.8 cm), in the sagittal plane was 3.3 cm (range 2–5 cm). The prescription doses were either 12–16 Gy in 1 fraction or 18–24 Gy in 3 fractions. All patients were treated on the TB linear accelerator with a 2.5 mm Multi‐Leaf Collimator (MLC) leaf width. Treatment plans were retrospectively created for the Halcyon, which has a 5 mm effective MLC leaf width. The 20 patients had a total of 50 treatments. Analysis of the 50 cone beam computed tomography (CBCT) scans showed average rotational setup errors of 0.6°, 1.2°, and 0.8° in pitch, yaw, and roll, respectively. Rotational error in roll was not considered in this study, as the original TB plans used a coplanar volumetric modulated arc therapy (VMAT) technique, and each 1° of roll will contribute an error of 1/360. If a plan has 3 arcs, the contribution from errors in roll will be 1° in the absence of 6‐DOF correction capabilities.

Purpose/Objective(s) Biology-guided Radiotherapy (BgRT) is a new external beam radiotherapy delivery modality combining positron emission tomography-computed tomography (PET-CT) with a linear accelerator. Our research group has previously introduced the BgRT specific prospective process map for developing an initial clinical workflow and has performed the risk analysis for the BgRT process that will bring in a new treatment paradigm. However, due to a lack of experience and historical data, assigning an accurate value of each risk factor in traditional FMEA leads to difficulties for evaluators. Also, there are certain sub-processes where the differences in weights of risk factors needs to be considered. Therefore, in this study, we introduced the fuzzy FMEA to perform a comprehensive analysis of failure modes (FMs) of BgRT and overcome weaknesses of conventional FMEA. Materials/Methods Five sub-processes unique to BgRT out of a total of 15 sub-processes were selected and relevant 84 FMs were identified. The evaluators used the fuzzy linguistic variables (very low, low, medium, high, and very high) to evaluate the importance of risk factors for assigning weights as well as the evaluation of each risk factor (occurrence, severity, and detectability) of each failure mode. Then, the fuzzy measure was used to calculate the weights of risk factors and the fuzzy integral method was used to fuse every value of risk factor of FMs to obtain the final fuzzy risk priority number value. Results Top 3 FMs are the machine down/emergency during beam delivery, failure to meet activity before PET pre-scan, and failure/delay of tracer delivery from a local vendor. The mitigation plans are discussed by team members including complete guidelines for the emergencies on the treatment machine, maintenance program of PET tracers by dedicated staffs, and staff training program for the BgRT procedure. Strong cooperation with a local PET tracer vendor and timely patient scheduling to allow multiple PET images at the treatment machine were also included in mitigation plans. Conclusion The proposed fuzzy FMEA presents a more reasonable and effective method for assessing potential failures allowing fuzzy linguistic variables terms that are easier to use than numerical assignments to evaluate the FMs, especially with the new prototype machine for BgRT. The results have been shared with team members, and mitigation plans will be implemented.

PURPOSE/OBJECTIVE(S) MR image based HDR brachytherapy is a complex, time-constrained and resource-intensive procedure requiring significant coordination and cooperation of multi-departmental efforts. Failure modes and effects analysis (FMEA) is an effective risk evaluation tool for identifying all possible failure modes (FMs) that could potentially impact negatively on the patient's treatment. Given the complexity of the MR image based HDR brachytherapy clinical workflow, FMEA can play a critical role in improving quality measures for each task. However, assigning a value between 1 to 10 to each of risk factor in traditional FMEA is a subjective and challenging task for the relevant multi-disciplinary team and potentially can cause considerable discrepancy and inconsistency. In this study, we introduced fuzzy inference based FMEA to provide better understanding of FMs to improve the quality assurance program for an efficient workflow and improved patient safety. MATERIALS/METHODS A total of four major sub-processes and forty-five FMs were identified from "applicator insertion" to "treatment delivery". The fuzzy inference rule-based model uses three inputs of risk factors (severity, occurrence, and detectability) and single output of fuzzy risk priority number (RPN) consisting of five fuzzy linguistic terms (very low, low, medium, high, and very high) of triangular membership functions. This rule-based model is generated based on a set of fuzzy if-then rules by decision makers that relate input to output variables. Then, the defuzzification method was used to obtain a fuzzy RPN value. RESULTS The team identified top three FMs of traditional FMEA. These were incorrect insertion of applicators by wrong identification ultrasound track, applicator moves, and incorrect channel length. Different rankings were produced depending on the rules of decision maker in fuzzy inference FMEA. Top 3 FMs of fuzzy FMEA were identified as missed/not detecting errors during physics second check, wrong applicator reconstruction, and poor quality of MR image set. The differences between the two RPN rankings are due to rules of decision making considering the probability of detecting errors in later process and severity. CONCLUSION This is the first report for fuzzy inference based FMEA on MRI based HDR brachytherapy. The fuzzy FMEA model exhibits desirable properties that help overcome the drawbacks of the traditional FMEA and RPN, especially when dealing with multi-disciplinary team practice where their priorities on FMs are different. The results have been shared with team members, and mitigation plans are to be implemented for enhancing quality of care and improving patient safety.

The same fractionation scheme of accelerated partial breast irradiation (APBI) with brachytherapy is usually applied to APBI patients without considering the radiaton effect on the planning target and organs at risk (OARs) for an individual patient. The purpose of this study is to report the results of optimization of the fractionation scheme by evaluating the radiation effect on target and OARs with a modified linear-quadratic model, universal survival curve (USC), based on dose-volume histograms (DVHs). Ten breast patients treated with multilumen balloon brachytherapy were selected. The minimum skin and chest wall/rib (CW/rib) spacing ranged from 2.5 to 14.3 mm and from 0.5 to 25.0 mm, respectively. The USC model parameters were set as: (1) breast:α = 0.3, β = 0.05; (2) skin: acute reaction α = 0.101, β = 0.009; late reaction α = 0.064, β = 0.029; (3) CW/rib: α = 0.3, β = 0.12. Boundary dose Dt was 6 Gy for both target and OARs. The relation between radiation effects on the target (ET) and OARs (EOAR) were plotted for fraction numbers (N) from 1 to 20. If ET is set at a certain value, the fractionation that results in a minimum EOAR value corresponds to the optimal fractionation. The results show that the optimal fractionation is different for different OAR damage effects. For most of the patients, N = 2 is best for minimizing skin acute reactions while N = 20 is best for minimizing skin late reactions. N varies from 3 to 20 among patients for minimizing CW/rib toxicity. The determined unique optimal N for treatment delivery was found to vary from 1 to 20 among these 10 patients resulted from balancing the different damage effects considering the spatial dose for a given patient geometry. Optimal fractionation can be achieved for an individual patient by evaluating the radiation effect on tumor and OARs with the USC model based on the patient specific DVHs with APBI brachytherapy.

This study is aimed at providing a dosimetric evaluation of the irregular motion of lung tumors due to variations in patients' respiration. Twenty-three lung cancer patients are retrospectively enrolled in this study. The motion of the patient clinical target volume is simulated and two types of irregularities are defined: characteristic and uncharacteristic motions. Characteristic irregularities are representative of random fluctuations in the observed target motion. Uncharacteristic irregular motion is classified as systematic errors in determination of the target motion during the planning session. Respiratory traces from measurement of patient abdominal motion are also used for the target motion simulations. Characteristic irregular motion was observed to cause minimal changes in target dosimetry with the largest effect of 2.5% ± 0.9% (1σ) reduction in the minimum target dose (D(min)) observed for targets that move 2 cm on average and exhibiting 50% amplitude variations within a session. However, uncharacteristic irregular motion introduced more drastic changes in the clinical target volume (CTV) dose; 4.1% ± 1.7% reduction for 1 cm motion and 9.6% ± 1.7% drop for 2 cm. In simulations with patients' abdominal motion, corresponding changes in target dosimetry were observed to be negligible (0.1%). Only uncharacteristic irregular motion was identified as a clinically significant source of dosimetric uncertainty.

This study assesses the feasibility and implementation of respiratory-gated whole-abdominal intensity-modulated radiation therapy (RG-WAIMRT). Three patients were treated with RG-WAIMRT. The planning target volume (PTV1) included the entire peritoneal cavity and a pelvic boost field was created (PTV2). The dose prescribed was 30 Gy to PTV1 and 14.4 Gy to PTV2. For comparison, a conventional three-dimensional (3D) plan was generated for each patient. In the WAIMRT plan, an average of 90% of PTV1 received 30 Gy compared to 70% for the conventional 3D plan. The percent volume receiving 30 Gy (V30) for liver averaged 54% (WAIMRT) vs 43% (3D). The percent volume receiving 20 Gy (V20) for kidneys averaged 19% vs 0%, and the mean V20 for bone marrow was 74% vs 83%, respectively. Major acute toxicities were anemia (grade 2: 1/3), leukopenia (grade 3: 2/3 patients), and thrombocytopenia (grade 2: 1/3 patients, grade 3: 1/3 patients). One patient could not complete the whole-abdomen field after 19.5 Gy because of persistent nausea. No major subacute toxicity has been reported. WAIMRT demonstrated superior target coverage and reduced dose to bone marrow, with a slightly increased dose to liver and kidneys. WAIMRT is a novel and feasible technique for ovarian cancer treatment.

This Hands-on Workshop will be focused on providing participants with experience with the principal tools of TG 100 and hence start to build both competence and confidence in the use of risk-based quality management techniques. The three principal tools forming the basis of TG 100's risk analysis: Process mapping, Failure-Modes and Effects Analysis and fault-tree analysis will be introduced with a 5 minute refresher presentation and each presentation will be followed by a 30 minute small group exercise. An exercise on developing QM from the risk analysis follows. During the exercise periods, participants will apply the principles in 2 different clinical scenarios. At the conclusion of each exercise there will be ample time for participants to discuss with each other and the faculty their experience and any challenges encountered. Learning Objectives: 1.To review the principles of Process Mapping, Failure Modes and Effects Analysis and Fault Tree Analysis. 2.To gain familiarity with these three techniques in a small group setting. 3.To share and discuss experiences with the three techniques with faculty and participants. Director, TreatSafely, LLC. Director, Center for the Assessment of Radiological Sciences. Occasional Consultant to the IAEA and Varian.

The volume of normal lung receiving 20 Gy (V20) and the mean lung dose (MLD) represent dosimetric parameters used for identifying risk of radiation pneumonitis. However, the total lung volume for dosimetric analysis has been defined differently. Herein we investigate to quantify the dosimetric differences when analysis is based on either definition (ie, excluding planning target volume [PTV] vs. gross tumor volume [GTV] from the total bilateral lung volume).Sixty-one patients with lung cancer who had undergone definitive radiation therapy were retrospectively reviewed. Dosimetric parameters were calculated when excluding GTV or PTV from the total bilateral lung volume.Median GTV to PTV margin was 1.3 cm (range, 0.4 to 3.8 cm). Median heterogeneity-corrected RT dose was 74 Gy with the median GTV of 110 mL (range, 13.79 to 665.8 mL) and the median PTV of 346 mL (range, 39.8 to 1258 mL).The MLD, V5, V10, V20, and V30 were all slightly higher and significant when excluding GTV from the total bilateral lung volume compared with similar dosimetric parameters when excluding PTV (P0.001). Average MLD was 14.8 and 16.7 Gy when excluding PTV and GTV, respectively. Mean V5, V10, V20, and V30 were 49.8%, 38%, 25%, and 18.8% when excluding PTV versus 51.3%, 40%, 28%, and 21.5% when excluding GTV. There were 4 patients with clinical pneumonitis and all had the V2023% when excluding the PTV versus the V2027% when excluding the GTV from total bilateral lung volume.A small but significant difference exists between the 2 approaches used to calculate dosimetric variables for lung dose. This difference should be taken into account when comparing dosimetric information between different institutions and when optimizing treatment plans.

The purpose of this study is to investigate the interplay effect between dynamic MLC movement and tumor respiratory motion in volumetric‐modulated arc therapy (VMAT)‐based lung SBRT treatment delivered by the flattening filter‐free (FFF) beam of a Varian TrueBeam machine. Six lung cancer patients with tumor motions ranging between 0.5–1.6 cm were recruited in this study. All patients underwent 4D‐CT scan with audiocoaching. A two‐arc VMAT plan was retrospectively generated using Varian's Eclipse planning system for each patient. To explicitly describe the interplay effect, the contributions of each control point in the original static VMAT plans to each respiratory phase were calculated, and then ten new VMAT plans corresponding to different respiratory phases were generated and imported back into Eclipse planning system to calculate the radiation dose based on the CT images of related respiratory phase. An in‐house 4D dose calculation program with deformable registration capacity was used to calculate the accumulative 4D dose distribution of the targets. For all patients, the PTV coverage dropped significantly with increased respiratory motion amplitude. However, V100 and D90 of the GTV and GTV+5mm, which mimic the target with setup error of less than 5 mm, were either unchanged or slightly increased up to 1.2%, and the variations of their minimum doses were less than 3.2%. Our results indicated that for VMAT‐based lung SBRT treatment delivered by FFF beam of TrueBeam machine, the impact of interplay effects on target coverage is insignificant, as long as a sufficient margin was given. PACS number: 87.53.Ly

This SAMs Therapy Educational Course will introduce participants to the tools recommended by TG 100 for use in the development of a risk-based Quality Management Program. The Course will start with an Overview of the background and rationale behind the TG 100 initiative, from which its charge was developed. After setting the scene, four 15 minute presentations will introduce the principal components of the soon to be published Report of TG 100. These are Process Mapping, Failure Modes and Effects Analysis, Fault Tree Analysis and the development of a QA/QM risk-based Program. There will be time for two short exercises based on Failure Modes and Effects Analysis and a Discussion before the SAMs questions which will conclude the session. Learning Objectives: 1. To appreciate the underlying philosophy of the TG 100 initiative. 2. To gain a brief overview of the principal risk-based tools recommended by TG 100. 3. In an informal workshop format, to explore, at an introductory level, the use of risk analysis as proposed by TG 100 as a prelude to the development of a Quality Management Program.

Purpose: This work investigated the development of EBT3 film as a function of dose rate, and also the accuracy of a commercial calibrationrescaling analysis method, to determine potential application to patientspecific QA of CyberKnife MLC treatments. Methods: EBT3 films were exposed to 300cGy at dose rates ranging from 5–300cGy/min, and scanned repeatedly from 2–5760min after exposure using a flatbed scanner. All other films were scanned 1 and 24hr after exposure. Ten calibration films were exposed to doses between 0 and 800cGy. Four verification films were exposed to doses between 80 and 290cGy, and 0 to 30min later, reference films were exposed to 450cGy. The verification and reference films were scanned together and analyzed both with and without calibration rescaling. The dose distribution of a 36min treatment plan was measured. Immediately prior to the measurement, a reference film was exposed. Both films were scanned together and analyzed both with and without calibration rescaling. Results: The development of EBT3 film is linear with the logarithm of time after exposure. If the midpoint of the exposure duration is taken as time zero, then film development is independent of dose rate. The doses measured with the verification films agreed with the expected dose within 1- 2% with calibration rescaling for all reference films. The delay between the exposure of the reference and QA films was 24min relative to the midpoint of exposure. Analysis of the scan at 60min post-exposure using rescaling of the calibration at 24hr had a gamma passing rate of 92% with 2%/1mm criteria, consistent with analysis of the scan at 24hr post-exposure without calibration rescaling. Conclusion: Using calibration rescaling, measured doses were accurate within 1–2% 60min after exposure. If the midpoint of exposure is taken as time zero, then calibration rescaling can be applied to patient-specific QA for CyberKnife MLC treatments.

Purpose: The accelerated partial breast irradiation (APBI) with brachytherapy prescribes 34Gy to be delivered in 10 fractions over 5 consecutive working days without considering the physical dose to the target and organs at risk (OARs) for an individual patient. The purpose of this study is to optimize the fractionation scheme by evaluating the radiation effect on tumor and OARs with a modified linear-quadratic (LQ) model based on dose-volume histograms (DVHs). Methods: Five breast patients treated with multilumen balloon brachytherapy were selected. The minimum skin and rib spacing were ranged from 2.5mm to 14.3mm and from 1.0mm to 25.0mm, respectively. The LQ model parameters were set as: (1) breast: α=0.08, β=0.028, doubling time Tpot=14.4 days, and starting time Tk=21days; (2) skin: acute reaction α=0.101, β=0.009; late reaction α=0.064, β=0.029; (3) rib: α=0.3, β=0.12. Boundary dose Dt was 6 Gy for both target and OARs. The relation between radiation effects on the tumor (ET) and OARs (EOAR) were plotted for fraction number from 1 to 20. Results: The value of radiation effect from routine 3.4Gyx10 fractions was used as reference, ETref and EOARref. If set ET=ETref, the fractionation that results in minimum EOAR values correspond to the optimal fractionation. For these patients, the optimal numbers are 10 fractions for skin acute reaction, 18 fractions for skin and rib late reaction while the doses per fraction are 3.4Gy and 2.05–2.10Gy, respectively. If set EOAR=EOARref, the fractionation that results in a maximum ET value corresponds to the optimal fractionation. The optimal fractionation is 3.4Gyx10 fractions for skin acute reaction, and 2.10–2.25Gyx18 fractions for skin late reaction and rib. Conclusion: For APBI brachytherapy, the routine 3.4Gyx10 fractions is optimal fractionation for skin acute reaction, while 2.05–2.25Gyx18 fractions is optimal fractionation for late reaction of skin and rib.

Purpose: The planning margins necessary to safely treat targets in the lung can be reduced depending upon the use of gating or abdominal compression to manage respiratory motion, but these may be uncomfortable for the patient, involve expensive equipment, or increase the length of each treatment fraction. The goal of this project is to use knowledge-based-planning (KBP) to evaluate which patients may benefit most from motion management. Methods: The Varian RapidPlan” KBP module was used to estimate doses for VMAT SBRT lung treatment plans with different planning margins corresponding to 1) standard lung setup (1.0 cm radial margin, 2.0 cm S-I margin), 2) daily IGRT (0.7 cm radial 1.5 cm S-I), 3) daily IGRT with motion management (0.5 cm radial, 1.0 cm S-I). The estimated doses were then compared with treatment plan doses (AAA dose calculation) generated using the RapidPlan™ optimization constraints. Treatment plan doses were then compared against RTOG protocol dose limits for organs at risk. Results: The OAR doses were within or below the estimated range generated by the KBP system in 100% of plans. With standard margins, only 10% of the plans were able to meet all RTOG dose goals, compared with 75% of plans with IGRT margins. All plans were able to meet RTOG dose guidelines with motion management. The DVH estimation was able to correctly identify 100% of the plans in which one or more OAR doses exceeded RTOG guidelines. Also, the dose estimates correctly identified 88% of individual OAR doses exceeding RTOG guidelines. Conclusion: The KBP system was able to accurately predict the achievable doses in treatment plans, and predict patients in which RTOG dose guidelines would be exceeded. The system may be a useful tool in identifying patients where motion management may be necessary for SBRT treatment. This work was supported by Varian Medical Systems.

Purpose: To determine the accuracy of position monitoring with BrainLAB ExacTrac snap verification following couch rotations during intracranial SRS. Methods: A CT scan of an anthropomorphic head phantom was acquired using 1.25mm slices. The isocenter was positioned near the centroid of the frontal lobe. The head phantom was initially aligned on the treatment couch using cone-beam CT, then repositioned using ExacTrac x-ray verification with residual errors less than 0.2mm and 0.2°. Snap verification was performed over the full range of couch angles in 15° increments with known positioning offsets of 0–3mm applied to the phantom along each axis. At each couch angle, the smallest tolerance was determined for which no positioning deviation was detected. Results: For couch angles 30°–60° from the center position, where the longitudinal axis of the phantom is approximately aligned with the beam axis of one x-ray tube, snap verification consistently detected positioning errors exceeding the maximum 8mm tolerance. Defining localization error as the difference between the known offset and the minimum tolerance for which no deviation was detected, the RMS error is mostly less than 1mm outside of couch angles 30°–60° from the central couch position. Given separate measurements of patient position from the two imagers, whether to proceed with treatment can be determined by the criterion of a reading within tolerance from just one (OR criterion) or both (AND criterion) imagers. Using a positioning tolerance of 1.5mm, snap verification has sensitivity and specificity of 94% and 75%, respectively, with the AND criterion, and 67% and 93%, respectively, with the OR criterion. If readings exceeding maximum tolerance are excluded, the sensitivity and specificity are 88% and 86%, respectively, with the AND criterion. Conclusion: With a positioning tolerance of 1.5mm, ExacTrac snap verification can be used during intracranial SRS with sensitivity and specificity between 85% and 90%.

Purpose: To evaluate possible inter-fractional tumor motion variability for pancreatic SBRT with length measurement of the fiducial depiction on the scan and to develop an empirical correlation using a moving phantom and fiducials for adjusting gating window on a daily basis Methods: In this retrospective study, motion data for fifty pancreatic SBRT patients with fiducials were selected to find the tumor motion statistics. Three gold fiducials of 5mm were placed around a solid target inside the Quasar Phantom and the 4D CT images of the Phantom were acquired with tumor motion of 1cm in superior-inferior direction. The breathing period was set to 4 seconds with a sinusoidal breathing form. After 4D-CT acquisition, CT50% images were imported into the Eclipse and setup fields were created for acquiring CBCT images. CBCT images were acquired by using the TrueBeam-STx and Pelvis technique. For sinusoidal tumor motions, CBCT images were acquired with tumor motion from zero to 2cm with 0.5cm increment along SI direction. The breathing period was varied from 2∼6 seconds with 2-second increment. Also, real patients’ breathing files acquired from Varian-RPM system were used to simulate real patients’ breathing patterns. Then length of fiducial depiction was measured with a HU threshold of zero and was used to find its correlation with real tumor motion. Results: Tumor motions in SI, AP, and LR directions were 0.7±0.5cm, 0.2±0.3cm, and 0.1±0.2cm, respectively. Breathing period was 4.3±0.8seconds. For a sinusoidal breathing form, there was a significant correlation between length of fiducial and real tumor motions with R2 of 0.98. However, the length of fiducial was independent of varying breathing periods. For a real patient's breathing file, the correlation between fiducial length(Y) and tumor motion(X) was Y=1.1268X+0.2696 with R2 of 0.99. Conclusion: With daily fiducial length measurement, we can evaluate possible changes in the inter-fractional tumor motion in pancreatic SBRT.

Purpose: To quantify differences between the TG51 and TG51 addendum calibration protocols. Methods: Beam energies of 6X, 6XSRS, 10X, 15X, 23X, 6XFFF, and 10XFFF were calibrated following both the TG51 and TG51 addendum protocols using both a Farmer and a scanning ionization chamber with traceable absorbed dose-to-water calibrations. For the TG51 addendum procedure, the collimating jaws were positioned to define a 10×10cm2 radiation field, a lead foil was only used for kQ measurements of FFF energies, and a volume-averaging correction was applied based on crossline and inline dose profiles. For the TG51 procedure, the collimating jaws were set to 10×10cm2 according to the digital readout, and a lead foil was used for kQ measurements of energies greater than 10MV. Results: For beam energies with a flattening filter, absorbed dose-to-water determined by the two protocols differed by 0.1%–0.3%. For FFF beam energies, differences between the protocols were up to 0.2% and 0.8% for the scanning and Farmer ionization chambers, respectively. Differences between the protocols were due to kQ determination, volume-averaging correction, and measurement of raw ionization. Differences in kQ values between the two protocols were up to 0.4% and 0.2% for the scanning and Farmer ionization chambers, respectively. Volume-averaging corrections were less than 0.1% for the scanning ionization chamber, and up to 0.4% and 0.6% for the Farmer ionization chamber in beams with a flattening filter and FFF beams, respectively. Raw ionization measurements differed up to 0.3%±0.07% due to differences in jaw settings. Conclusion: The TG51 and TG51 addendum calibration protocols differed less than 0.3% for the scanning ionization chamber. For the Farmer chamber in FFF energies, volume-averaging corrections of up to 0.6% contributed to calibration differences of up to 0.8%. Failure to verify the radiation field size can produce calibration differences of up to 0.3%.

Purpose: The goal of the present work was to evaluate the process maps for stereotactic radiosurgery (SRS) treatment at three radiotherapy centers in Brazil and apply the FMEA technique to evaluate similarities and differences, if any, of the hazards and risks associated with these processes. Methods: A team, consisting of professionals from different disciplines and involved in the SRS treatment, was formed at each center. Each team was responsible for the development of the process map, and performance of FMEA and FTA. A facilitator knowledgeable in these techniques led the work at each center. The TG100 recommended scales were used for the evaluation of hazard and severity for each step for the major process “treatment planning”. Results: Hazard index given by the Risk Priority Number (RPN) is found to range from 4–270 for various processes and the severity (S) index is found to range from 1–10. The RPN values > 100 and severity value ≥ 7 were chosen to flag safety improvement interventions. Number of steps with RPN ≥100 were found to be 6, 59 and 45 for the three centers. The corresponding values for S ≥ 7 are 24, 21 and 25 respectively. The range of RPN and S values for each center belong to different process steps and failure modes. Conclusion: These results show that interventions to improve safety is different for each center and it is associated with the skill level of the professional team as well as the technology used to provide radiosurgery treatment. The present study will very likely be a model for implementation of risk-based prospective quality management program for SRS treatment in Brazil where currently there are 28 radiotherapy centers performing SRS. A complete FMEA for SRS for these three radiotherapy centers is currently under development.

Current quality assurance and quality management guidelines provided by various professional organizations are prescriptive in nature, focusing principally on performance characteristics of planning and delivery devices. However, published analyses of events in radiation therapy show that most events are often caused by flaws in clinical processes rather than by device failures. This suggests the need for the development of a quality management program that is based on integrated approaches to process and equipment quality assurance. Industrial engineers have developed various risk assessment tools that are used to identify and eliminate potential failures from a system or a process before a failure impacts a customer. These tools include, but are not limited to, process mapping, failure modes and effects analysis, fault tree analysis. Task Group 100 of the American Association of Physicists in Medicine has developed these tools and used them to formulate an example risk-based quality management program for intensity-modulated radiotherapy. This is a prospective risk assessment approach that analyzes potential error pathways inherent in a clinical process and then ranks them according to relative risk, typically before implementation, followed by the design of a new process or modification of the existing process. Appropriate controls are then put in place to ensure that failures are less likely to occur and, if they do, they will more likely be detected before they propagate through the process, compromising treatment outcome and causing harm to the patient. Such a prospective approach forms the basis of the work of Task Group 100 that has recently been approved by the AAPM. This session will be devoted to a discussion of these tools and practical examples of how these tools can be used in a given radiotherapy clinic to develop a risk based quality management program. Learning Objectives: 1. Learn how to design a process map for a radiotherapy process 2. Learn how to perform failure modes and effects analysis analysis for a given process 3. Learn what fault trees are all about 4. Learn how to design a quality management program based upon the information obtained from process mapping, failure modes and effects analysis and fault tree analysis. Dunscombe: Director, TreatSafely, LLC and Center for the Assessment of Radiological Sciences; Consultant to IAEA and Varian Thomadsen: President, Center for the Assessment of Radiological Sciences Palta: Vice President of the Center for the Assessment of Radiological Sciences

Purpose: Knowledge-based planning programs have become available to assist treatment planning in radiation therapy. Such programs can be used to generate estimated DVHs and planning constraints for organs at risk (OARs), based upon a model generated from previous plans. These estimates are based upon the planning CT scan. However, for distensible OARs like the bladder and rectum, daily variations in volume may make the dose estimates invalid. The purpose of this study is to determine whether knowledge-based DVH dose estimates may be valid for distensible OARs. Methods: The Varian RapidPlan™ knowledge-based planning module was used to generate OAR dose estimates and planning objectives for 10 prostate cases previously planned with VMAT, and final plans were calculated for each. Five weekly setup CBCT scans of each patient were then downloaded and contoured (assuming no change in size and shape of the target volume), and rectum and bladder DVHs were recalculated for each scan. Dose volumes were then compared at 75, 60,and 40 Gy for the bladder and rectum between the planning scan and the CBCTs. Results: Plan doses and estimates matched well at all dose points., Volumes of the rectum and bladder varied widely between planning CT and the CBCTs, ranging from 0.46 to 2.42 for the bladder and 0.71 to 2.18 for the rectum, causing relative dose volumes to vary between planning CT and CBCT, but absolute dose volumes were more consistent. The overall ratio of CBCT/plan dose volumes was 1.02 ±0.27 for rectum and 0.98 ±0.20 for bladder in these patients. Conclusion: Knowledge-based planning dose volume estimates for distensible OARs are still valid, in absolute volume terms, between treatment planning scans and CBCT’s taken during daily treatment. Further analysis of the data is being undertaken to determine how differences depend upon rectum and bladder filling state. This work has been supported by Varian Medical Systems.

Purpose: For small field dosimetry, such as measurements of output factors for cones or MLC-shaped irregular small fields, ion chambers often Result in an underestimation of the dose, due to both the volume averaging effect and the lack of lateral charged particle equilibrium. This work presents a mathematical model for correction matrix for a PTW PinPoint ionization chamber for dosimetric measurements made in the newly released Incise™ Multileaf collimator fields of the CyberKnife M6™ machine. Methods: A correction matrix for a PTW 0.015cc PinPoint ionization chamber was developed by modeling its 3D dose response in twelve cone-shaped circular fields created using the 5mm, 7.5mm, 10mm, 12.5mm, 15mm, 20mm, 25mm, 30mm, 35mm, 40mm, 50mm, 60mm cones in a CyberKnife M6™ machine. For each field size, hundreds of readings were recorded for every 2mm chamber shift in the horizontal plane. The contribution of each dose pixel to a measurement point depended on the radial distance and the angle to the chamber axis. These readings were then compared with the theoretical dose as obtained with Monte Carlo calculation. A penalized least-square optimization algorithm was developed to generate the correction matrix. After the parameter fitting, the mathematical model was validated for MLC-shaped irregular fields. Results: The optimization algorithm used for parameter fitting was stable and the resulted response factors were smooth in spatial domain. After correction with the mathematical model, the chamber reading matched with the calculation for all the tested fields to within 2%. Conclusion: A novel mathematical model has been developed for PinPoint chamber for dosimetric measurements in small MLC-shaped irregular fields. The correction matrix is dependent on detector, treatment unit and the geometry of setup. The model can be applied to non-standard composite fields and provides an access to IMRT point dose validation.

Purpose: In cone beam computerized tomography(CBCT), the reconstructed image contains significant image artifacts induced by scatter effects. The purpose of this study is to develop a scatter reduction method to improve CBCTimage quality with piecewise prior image knowledge. Methods: The hypothesis of the proposed method is that in scatter‐free CBCTimage, the image intensities of different kind of materials are approximately globally uniform, i.e. piecewise property. However, the scatter induced image artifacts diminish the piecewise property of the CBCTimage. In the proposed scatter reduction method, an extended fuzzy C‐mean (EFCM) function is used to describe the degree of piecewise property of the CBCTimage. Since the scatter components in projection domain can be characterized as low frequency, by minimizing the EFCM function in image domain, the proposed method removes an appropriate low frequency component from projection domain so that the reconstructedCBCTimage achieves a piecewise property.Results: The performance of the proposed scatter reduction algorithm was tested using both digital phantom and pelvis CBCTimages. In a phantom study, the proposed method reduced the maximum HU errors from 420HU to about 80HU; in a pelvis case, the HU errors were reduced from 580HU to 150HU. All those maximum HU errors occur around area with high imagecontrast. For soft tissues, the proposed method reduced the HU errors to less than 60HU. In addition, there are severe shading‐artifacts that appeared in the uncorrected CBCTimages in which the proposed method significantly improved the image intensity uniformity of different tissue types in the corrected CBCTimage.Conclusions: For an object with piecewise property, the proposed scatter reduction method demonstrated substantial reductions in scatter‐induced image artifacts commonly encountered in CBCTimaging. This methodology may be an avenue to significantly improve the image quality of clinical CBCTimages.

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same is for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project

Purpose: With the sequential optimization algorithm in MultiPlan system, clinical objectives (homogeneity, PTV coverage, conformity, normal tissue protection) can be optimized in sequence. However, the prescription isodose line (RxIDL) varies widely among institutions, which can influence the optimized dose distribution. The aim of this study is to investigate the impact of different prescription isodose lines on plan quality for the treatment of brain metastases using CyberKnife Multiplan system. Methods: Ten patients with multiple metastases were selected for this study. Four plans were generated for each patient such that 100% of the target volume receives the prescribed dose of 18 Gy, which was 50%, 60%, 70%, and 80% prescription Isodose line, separately. The prescription isodose was calculated as the ratio of the prescription dose and the maximum dose in target volume. The dosimetric parameters, including PTV coverage, conformity index (CI), gradient index (GI) and the volume covered by 12 Gy (V12Gy) were analyzed. The plan Monitor Units (MU) and treatment time were also compared. Results: All plans can provide the same target coverage (100%) and similar conformity index (1.26, 1.30, 1.32, and 1.29 on average for 80%, 70%, 60%, and 50% RxIDL plans, separately); there was no difference in critical structure dose. The 50% RxIDL plans have much lower GI (4.21±1.79 for 50% and 5.56±2.92 for 80% RxIDL plans) and V12Gy (13.36±10.31cc for 50% and 15.87±11.85cc for 80% RxIDL plans). The variation in estimated treatment delivery time was insignificant. Conclusion: The dose falloff is much faster for the lower RxIDL plans in terms of GI and V12Gy. For 50% RxIDL plans, the average V12Gy decreases by 16% compared to 80% RxIDL plans, which indicates that the normal tissue can be better protected by decreasing the prescription Isodose line.

Purpose: Evaluating the dosimetric-impact on multiple-targets placed away from the isocenter-target with varying rotational-error introduced by initial setup uncertainty and/or intrafractional-movement Methods: CyberKnife-Phantom was scanned with the Intracranial SRS-protocol of 1.25mm slice-thickness and the multiple-targets(GTV) of 1mm and 10mm in diameter were contoured on the Eclipse. PTV for distal-target only was drawn with 1mm expansion around the GTV to find out how much margin is needed to compensate for the rotational-error. The separation between the isocenter-target and distal-target was varied from 3cm to 7cm. RapidArc-based IMRS plans of 16Gy single-fraction were generated with five non-coplanar arcs by using Varian TrueBeam-STx equipped with high resolution MLC leaves of 2.5mm at center and with dose-rate of 1400MU/min at 6MV for flatteringfilter- free(FFF). An identical CT image with intentionally introduced 1° rotational-error was registered with the planning CT image, and the isodose distribution and Dose-Volume-Histogram(DVH) were compared with the original plans. Additionally, the dosimetric-impact of rotational error was evaluated with that of 6X photon energy which was generated with the same target-coverage. Results: For the 1mm-target with 6X-FFF, PTV-coverage(D100) of the distal-target with 1° rotational-error decreased from 1.00 to 0.35 as the separation between isocenter-target and distal-target increased from 3cm to 7cm. However, GTV-coverage(D100) was 1.0 except that of 7cm-separation(0.55), which resulted from the 1mm-margin around the distal-target. For 6X photon, GTV-coverage remained at 1.0 regardless of the separation of targets, showing that the dosimetric-impact of rotational error depends on the degree of rotational-error, separation of targets, and dose distribution around targets. For 10mm-target, PTV-coverage of distaltarget located 3cm-away was better than that of 1mm-target(0.93 versus 0.7) and GTV-coverage was 1.0 regardless of 6X-FFF/6X photon beams. Conclusion: RapidArc-based Multiple-target IMRS may Resultin a compromised outcome due to the setup-error for distal-targets. With 1mm-margin, GTV-coverage of distal-target was 1.0 although the separation of targets was up to 5cm.