Measurement of the temporal latency of a respiratory gating system using two distinct approaches.

PURPOSE: To develop a methodology that can be used to measure the temporal latency of a respiratory gating system. METHODS: The gating system was composed of an automatic gating interface (Response) and an in-house respiratory motion monitoring system featuring an optically tracked surface marker. Two approaches were used to measure gating latencies. A modular approach involved measuring separately the latency of the gating system's complementary metal-oxide-semiconductor tracking camera, tracking software, and a gating latency of the LINAC. Additionally, an end-to-end approach was used to measure the total latency of the gating system. End-to-end latencies were measured using the displacement of a radiographic target moving at known velocities during the gating process. RESULTS: Summing together the latencies of each of the modular components investigated yielded a total beam-on latency of 1.55 s and a total beam-off latency of 0.49 s. End-to-end beam-on and beam-off latency was found to be 1.49 and 0.34 s, respectively. In each case, no statistically significant differences were found between the end-to-end latency of the gating system and the summation of the individually measured components. CONCLUSION: Two distinct approaches to quantify gating latencies were presented. Measuring the end-to-end latency of the gating system provided an independent means of validating the modular approach. It is expected that the beam-on latencies reported in this work could be reduced by altering the control system configuration of the LINAC. The modular approach can be used to decouple the individual latencies of the gating system, but future improvements in the temporal resolution of the service graphing feature are needed to reduce the uncertainty of LINAC-related gating latencies measured using this approach. Both approaches are generalizable and can be used together when designing a quality assurance program for a respiratory gating system.

Bilevel Positive Airway Pressure Ventilation for Improving Respiratory Reproducibility in Radiation Oncology: A Pilot Study.

BACKGROUND: Strategies for managing respiratory motion, specifically motion-encompassing methods, in radiation therapy typically assume reproducible breathing. In reality, respiratory motion variations occur and ultimately cause tumor motion variations, which can result in differences between the planned and delivered dose distributions. Therefore, breathing guidance techniques have been investigated to improve respiratory reproducibility. To our knowledge, bilevel positive airway pressure (BIPAP) ventilation assistance has not been previously investigated as a technique for improving respiratory reproducibility and is the focus of this work. METHODS AND MATERIALS: Ten patients undergoing radiation therapy treatment for cancers affected by respiratory motion (eg, lung and esophagus) participated in sessions in which their breathing was recorded during their course of treatment; these sessions occurred either before or after radiation treatments. Both unassisted free-breathing (FB) and BIPAP ventilation-assisted respiratory volume data were collected from each patient using spirometry. Patients used 2 different BIPAP ventilators (fixed BIPAP and flexible BIPAP), each configured to deliver the same volume of air per breath (ie, tidal volume). The flexible BIPAP ventilator permitted patient triggering (ie, it permitted patients to initiate each breath), and the fixed BIPAP did not. Intrasession and intersession metrics quantifying tidal volume variations were calculated and compared between the specific breathing platforms (FB or BIPAP). In addition, patient tolerance of both BIPAP ventilators was qualitatively assessed through verbal feedback. RESULTS: Both BIPAP ventilators were tolerated by patients, although the fixed BIPAP was not as well tolerated as the flexible BIPAP. Both BIPAP ventilators showed significant reductions (P < .05) in intrasession tidal volume variation compared with FB. However, only the fixed BIPAP significantly reduced the intersession tidal volume variation compared with FB. CONCLUSIONS: Based on the established correlation between tidal volume and tumor motion, any reduction of the tidal volume variation could result in reduced tumor motion variation. Fixed BIPAP ventilation was found to be tolerated by patients and was shown to significantly reduce intrasession and intersession tidal volume variations compared with FB. Therefore, future investigation into the potential of fixed BIPAP ventilation is warranted to define the possible clinical benefits.

Analytical setup margin for spinal stereotactic body radiotherapy based on measured errors.

BACKGROUND: No consensus currently exists about the correct margin size to use for spinal SBRT. Margins have been proposed to account for various errors individually, but not with all errors combined to result in a single margin value. The purpose of this work was to determine a setup margin for five-fraction spinal SBRT based on known errors during radiotherapy to achieve at least 90% coverage of the clinical target volume with the prescription dose for at least 90% of patients and not exceed a 30 Gy point dose or 23 Gy to 10% of the spinal cord subvolume. METHODS: The random and systematic error components of intrafraction motion, residual setup error, and end-to-end system accuracy were measured. The patient's surface displacement was measured to quantify intrafraction motion, the residual setup error was quantified by re-registering accepted daily cone beam computed tomography setup images, and the displacement between measured and planned dose profiles in a phantom quantified the end-to-end system accuracy. These errors and parameters were used to identify the minimum acceptable margin size. The margin recommendation was validated by assessing dose delivery across 140 simulated patient plans suffering from various random shifts representative of the measured errors. RESULTS: The errors were quantified in three dimensions and the analytical margin generated was 2.4 mm. With this margin applied in the superior/inferior direction only, at least 90% of the CTV was covered with the prescription dose for 96% of the 140 patients simulated with minimal negative effect on the spinal cord dose levels. CONCLUSIONS: The findings of this work support that a 2.4 mm margin applied in the superior/inferior direction can achieve at least 90% coverage of the CTV for at least 90% of dual-arc volumetric modulated arc therapy spinal SBRT patients in the presence of errors when immobilized with vacuum bags.

AAPM MEDICAL PHYSICS PRACTICE GUIDELINE 2.b.: Commissioning and quality assurance of X-ray-based image-guided radiotherapy systems.

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized.

Quality assurance-based optimization (QAO): Towards improving patient-specific quality assurance in volumetric modulated arc therapy plans using machine learning.

INTRODUCTION: Previous literature has shown general trade-offs between plan complexity and resulting quality assurance (QA) outcomes. However, existing solutions for controlling this trade-off do not guarantee corresponding improvements in deliverability. Therefore, this work explored the feasibility of an optimization framework for directly maximizing predicted QA outcomes of plans without compromising the dosimetric quality of plans designed with an established knowledge-based planning (KBP) technique. MATERIALS AND METHODS: A support vector machine (SVM) was developed - using a database of 500 previous VMAT plans - to predict gamma passing rates (GPRs; 3%/3mm percent dose-difference/distance-to-agreement with local normalization) based on selected complexity features. A heuristic, QA-based optimization (QAO) framework was devised by utilizing the SVM model to iteratively modify mechanical treatment features most commonly associated with suboptimal GPRs. Specifically, leaf gaps (LGs) <50 mm were widened by random amounts, which impacts all aperture-based complexity features. 13 prostate KBP-guided VMAT plans were optimized via QAO using user-specified maximum LG displacements before corresponding changes in predicted GPRs and dose were assessed. RESULTS: Predicted GPRs increased by an average of 1.14 ± 1.25% (p = 0.006) with QAO using a 3 mm maximum random LG displacement. There were small differences in dose, resulting in similarly small changes in tumor control probability (maximum increase = 0.05%) and normal tissue complication probabilities in the bladder, rectum, and femoral heads (maximum decrease = 0.2% in the rectum). CONCLUSION: This study explored the feasibility of QAO and warrants future investigations of further incorporating QA endpoints into plan optimization.

A method for predictive modeling of tumor regression for lung adaptive radiotherapy.

PURPOSE: The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer. METHODS: A predictive algorithm was developed as a decision support tool to determine the potential utility of mid-treatment adaptive radiotherapy based on anatomic changes observed on 1158 daily CBCT images across 43 patients. The anatomic changes on each axial slice within specified regions-of-interest were quantified into a single value utilizing imaging similarity criteria comparing the daily CBCT to the initial simulation CT. The range of the quantified metrics for each fraction across all axial slices are reduced to specified quantiles, which are used as the predictive input to train a logistic regression algorithm. A "ground-truth" of the need for adaptive radiotherapy based on tumor regression was evaluated systematically on each of the daily CBCTs and used as the classifier in the logistic regression algorithm. Accuracy of the predictive model was assessed utilizing both a tenfold cross validation and an independent validation dataset, with the sensitivity, specificity, and fractional accuracy compared to the ground-truth. RESULTS: The sensitivity and specificity for the individual daily fractions ranged from 87.9%-94.3% and 91.9%-98.6% for a probability threshold of 0.2-0.5, respectively. The corresponding average treatment fraction difference between the model predictions and assessed ART "ground-truth" ranged from -2.25 to -0.07 fractions, with the model predictions consistently predicting the potential need for ART earlier in the treatment course. By initially utilizing a lower probability threshold, the higher sensitivity minimizes the chance of false negative by alerting the clinician to review a higher number of questionable cases. CONCLUSIONS: The proposed methodology accurately predicted the first fraction at which individual patients may benefit from ART based on quantified anatomic changes observed in the on-treatment volumetric imaging. The generalizability of the proposed method has potential to expand to additional modes of adaptive radiotherapy for lung cancer patients with observed underlying anatomic changes.

Interplay effects in highly modulated stereotactic body radiation therapy lung cases treated with volumetric modulated arc therapy.

Interplay effects in highly modulated stereotactic body radiation therapy lung cases treated with volumetric modulated arc therapy. PURPOSE: To evaluate the influence of tumor motion on dose delivery in highly modulated stereotactic body radiotherapy (SBRT) of lung cancer using volumetric modulated arc therapy (VMAT). METHODS: 4D-CT imaging data of the quasar respiratory phantom were acquired, using a GE Lightspeed 16-slice CT scanner, while the phantom reproduced patient specific respiratory traces. Flattening filter-free (FFF) dual-arc VMAT treatment plans were created on the acquired images in Pinnacle3 treatment planning system. Each plan was generated with varying levels of complexity characterized by the modulation complexity score. Static and dynamic measurements were delivered to GafChromic EBT3 film inside the respiratory phantom using an Elekta Versa HD linear accelerator. The treatment prescription was 10 Gy per fraction for 5 fractions. Comparisons of the planned and delivered dose distribution were performed using Radiological Imaging Technology (RIT) software. RESULTS: For the motion amplitudes and periods studied, the interplay effect is insignificant to the GTV coverage. The mean dose deviations between the planned and delivered dose distribution never went below -2.00% and a minimum dose difference of -5.05% was observed for a single fraction. However for amplitude of 2 cm, the dose error could be as large as 20.00% near the edges of the PTV at increased levels of complexity. Additionally, the modulation complexity score showed an ability to provide information related to dose delivery. A correlation value (R) of 0.65 was observed between the complexity score and the gamma passing rate for GTV coverage. CONCLUSIONS: As expected, respiratory motion effects are most evident for large amplitude respirations, complex fields, and small field margins. However, under all tested conditions target coverage was maintained.

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

PURPOSE: Knowledge-based planning (KBP) techniques have been reported to improve plan quality, efficiency, and consistency in radiation therapy. However, plan complexity and deliverability have not been addressed previously for treatment plans guided by an established in-house KBP system. The purpose of this work was to assess dosimetric, mechanical, and delivery properties of plans designed with a common KBP method for prostate cases treated via volumetric modulated arc therapy (VMAT). METHODS: Thirty-one prostate patients previously treated with VMAT were replanned with an in-house KBP method based on the overlap volume histogram. VMAT plan complexities of the KBP plans and the reference clinical plans were quantified via monitor units, modulation complexity scores, the edge metric, and average leaf motion per degree of gantry rotation. Each set of plans was delivered to the same diode array and agreement between computed and measured dose distributions was evaluated using the gamma index. Varying percent dose-difference (1-3%) and distance-to-agreement (1 mm to 3 mm) thresholds were assessed for gamma analyses. RESULTS: Knowledge-based planning (KBP) plans achieved average reductions of 6.4 Gy (P < 0.001) and 8.2 Gy (P < 0.001) in mean bladder and rectum dose compared to reference plans, while maintaining clinically acceptable target dose. However, KBP plans were significantly more complex than reference plans in each evaluated metric (P < 0.001). KBP plans also showed significant reductions (P < 0.05) in gamma passing rates at each evaluated criterion compared to reference plans. CONCLUSIONS: While KBP plans had significantly reduced bladder and rectum dose, they were significantly more complex and had significantly worse quality assurance outcomes than reference plans. These results suggest caution should be taken when implementing an in-house KBP technique.

Impact of database quality in knowledge-based treatment planning for prostate cancer.

PURPOSE: This article investigates dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared with using a conventional, clinical plan database. METHODS AND MATERIALS: Two plan databases were created using retrospective, anonymized data of 124 volumetric modulated arc therapy (VMAT) prostate cancer patients. The clinical plan database (CPD) contained planning data from each patient's clinically treated VMAT plan, which were manually optimized by various planners. The multicriteria optimization database (MCOD) contained Pareto-optimal plan data from VMAT plans created using a standardized multicriteria optimization protocol. Overlap volume histograms, incorporating fractional organ at risk volumes only within the treatment fields, were computed for each patient and used to match new patient anatomy to similar database patients. For each database patient, CPD and MCOD KBP predictions were generated for D10, D30, D50, D65, and D80 of the bladder and rectum in a leave-one-out manner. Prediction achievability was evaluated through a replanning study on a subset of 31 randomly selected database patients using the best KBP predictions, regardless of plan database origin, as planning goals. RESULTS: MCOD predictions were significantly lower than CPD predictions for all 5 bladder dose-volumes and rectum D50 (P = .004) and D65 (P < .001), whereas CPD predictions for rectum D10 (P = .005) and D30 (P < .001) were significantly less than MCOD predictions. KBP predictions were statistically achievable in the replans for all predicted dose-volumes, excluding D10 of bladder (P = .03) and rectum (P = .04). Compared with clinical plans, replans showed significant average reductions in Dmean for bladder (7.8 Gy; P < .001) and rectum (9.4 Gy; P < .001), while maintaining statistically similar planning target volume, femoral head, and penile bulb dose. CONCLUSION: KBP dose-volume predictions derived from Pareto plans were more optimal overall than those resulting from manually optimized clinical plans, which significantly improved KBP-assisted plan quality. SUMMARY: This work investigates how the plan quality of knowledge databases affects the performance and achievability of dose-volume predictions from a common knowledge-based planning approach for prostate cancer. Bladder and rectum dose-volume predictions derived from a database of standardized Pareto-optimal plans were compared with those derived from clinical plans manually designed by various planners. Dose-volume predictions from the Pareto plan database were significantly lower overall than those from the clinical plan database, without compromising achievability.

An improved distance-to-dose correlation for predicting bladder and rectum dose-volumes in knowledge-based VMAT planning for prostate cancer.

The overlap volume histogram (OVH) is an anatomical metric commonly used to quantify the geometric relationship between an organ at risk (OAR) and target volume when predicting expected dose-volumes in knowledge-based planning (KBP). This work investigated the influence of additional variables contributing to variations in the assumed linear DVH-OVH correlation for the bladder and rectum in VMAT plans of prostate patients, with the goal of increasing prediction accuracy and achievability of knowledge-based planning methods. VMAT plans were retrospectively generated for 124 prostate patients using multi-criteria optimization. DVHs quantified patient dosimetric data while OVHs quantified patient anatomical information. The DVH-OVH correlations were calculated for fractional bladder and rectum volumes of 30, 50, 65, and 80%. Correlations between potential influencing factors and dose were quantified using the Pearson product-moment correlation coefficient (R). Factors analyzed included the derivative of the OVH, prescribed dose, PTV volume, bladder volume, rectum volume, and in-field OAR volume. Out of the selected factors, only the in-field bladder volume (mean R = 0.86) showed a strong correlation with bladder doses. Similarly, only the in-field rectal volume (mean R = 0.76) showed a strong correlation with rectal doses. Therefore, an OVH formalism accounting for in-field OAR volumes was developed to determine the extent to which it improved the DVH-OVH correlation. Including the in-field factor improved the DVH-OVH correlation, with the mean R values over the fractional volumes studied improving from -0.79 to -0.85 and -0.82 to -0.86 for the bladder and rectum, respectively. A re-planning study was performed on 31 randomly selected database patients to verify the increased accuracy of KBP dose predictions by accounting for bladder and rectum volume within treatment fields. The in-field OVH led to significantly more precise and fewer unachievable KBP predictions, especially for lower bladder and rectum dose-volumes.

Development of a Monte Carlo multiple source model for inclusion in a dose calculation auditing tool.

PURPOSE: The Imaging and Radiation Oncology Core Houston (IROC-H) (formerly the Radiological Physics Center) has reported varying levels of agreement in their anthropomorphic phantom audits. There is reason to believe one source of error in this observed disagreement is the accuracy of the dose calculation algorithms and heterogeneity corrections used. To audit this component of the radiotherapy treatment process, an independent dose calculation tool is needed. METHODS: Monte Carlo multiple source models for Elekta 6 MV and 10 MV therapeutic x-ray beams were commissioned based on measurement of central axis depth dose data for a 10 × 10 cm2 field size and dose profiles for a 40 × 40 cm2 field size. The models were validated against open field measurements consisting of depth dose data and dose profiles for field sizes ranging from 3 × 3 cm2 to 30 × 30 cm2 . The models were then benchmarked against measurements in IROC-H's anthropomorphic head and neck and lung phantoms. RESULTS: Validation results showed 97.9% and 96.8% of depth dose data passed a ±2% Van Dyk criterion for 6 MV and 10 MV models respectively. Dose profile comparisons showed an average agreement using a ±2%/2 mm criterion of 98.0% and 99.0% for 6 MV and 10 MV models respectively. Phantom plan comparisons were evaluated using ±3%/2 mm gamma criterion, and averaged passing rates between Monte Carlo and measurements were 87.4% and 89.9% for 6 MV and 10 MV models respectively. CONCLUSIONS: Accurate multiple source models for Elekta 6 MV and 10 MV x-ray beams have been developed for inclusion in an independent dose calculation tool for use in clinical trial audits.

Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

PURPOSE: Increasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment. METHODS: Test-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rank correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features' interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set. RESULTS: Of the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol were kept consistent, 4-13 of these 37 features passed our criteria for reproducibility more than 50% of the time, depending on the manufacturer-protocol combination. Almost all of the features changed substantially when scatter material was added around the phantom. For the dense cork, 23 features passed in the thoracic scans and 11 features passed in the head scans when the differences between one and two layers of scatter were compared. Using the same test for the shredded rubber, five features passed the thoracic scans and eight features passed the head scans. Motion substantially impacted the reproducibility of the features. With 4 mm of motion, 12 features from the entire volume and 14 features from the center slice measurements were reproducible. With 6-8 mm of motion, three features (Laplacian of Gaussian filtered kurtosis, gray-level nonuniformity, and entropy), from the entire volume and seven features (coarseness, high gray-level run emphasis, gray-level nonuniformity, sum-average, information measure correlation, scaled mean, and entropy) from the center-slice measurements were considered reproducible. CONCLUSIONS: Some radiomics features are robust to the noise and poor image quality of CBCT images when the imaging protocol is consistent, relative changes in the features are used, and patients are limited to those with less than 1 cm of motion.

Output calculation of electron therapy at extended SSD using an improved LBR method.

PURPOSE: To calculate the output factor (OPF) of any irregularly shaped electron beam at extended SSD. METHODS: Circular cutouts were prepared from 2.0 cm diameter to the maximum possible size for 15 × 15 applicator cone. In addition, two irregular cutouts were prepared. For each cutout, percentage depth dose (PDD) at the standard SSD and doses at different SSD values were measured using 6, 9, 12, and 16 MeV electron beam energies on a Varian 2100C LINAC and the distance at which the central axis electron fluence becomes independent of cutout size was determined. The measurements were repeated with an ELEKTA Synergy LINAC using 14 × 14 applicator cone and electron beam energies of 6, 9, 12, and 15 MeV. The PDD measurements were performed using a scanning system and two diodes-one for the signal and the other a stationary reference outside the tank. The doses of the circular cutouts at different SSDs were measured using PTW 0.125 cm(3) Semiflex ion-chamber and EDR2 films. The electron fluence was measured using EDR2 films. RESULTS: For each circular cutout, the lateral buildup ratio (LBR) was calculated from the measured PDD curve using the open applicator cone as the reference field. The effective SSD (SSDeff) of each circular cutout was calculated from the measured doses at different SSD values. Using the LBR value and the radius of the circular cutout, the corresponding lateral spread parameter [σR(z)] was calculated. Taking the cutout size dependence of σR(z) into account, the PDD curves of the irregularly shaped cutouts at the standard SSD were calculated. Using the calculated PDD curve of the irregularly shaped cutout along with the LBR and SSDeff values of the circular cutouts, the output factor of the irregularly shaped cutout at extended SSD was calculated. Finally, both the calculated PDD curves and output factor values were compared with the measured values. CONCLUSIONS: The improved LBR method has been generalized to calculate the output factor of electron therapy at extended SSD. The percentage difference between the calculated and the measured output factors of irregularly shaped cutouts in a clinical useful SSD region was within 2%. Similar results were obtained for all available electron energies of both Varian 2100C and ELEKTA Synergy machines.

Evaluation of a novel secondary check tool for intensity-modulated radiotherapy treatment planning.

The purpose of this study was to assess the accuracy and efficacy of an automated treatment plan verification, or "secondary check", tool (Mobius3D), which uses a reference dataset to perform an independent three-dimensional dose verification of the treatment planning system (TPS) dose calculation and assesses plan quality by comparing dose-volume histograms to reference benchmarks. The accuracy of the Mobius3D (M3D) system was evaluated by comparing dose calculations from IMRT and VMAT plans with measurements in phantom geometries and with TPS calculated dose distributions in prostate, lung, and head and neck patients (ten each). For the patient cases, instances of DVH limits exceeding reference values were also recorded. M3D showed agreement with measured point and planar doses that was comparable to the TPS in phantom geometries. No statistically significant differences (p < 0.05) were noted. M3D dose distributions from VMAT plans in patient cases were in good agreement with the TPS, with an average of 99.5% of dose points showing γ5%,3mm < 1. The M3D system also identified several plans that had exceeded dose-volume limits specified by RTOG protocols for those sites. The M3D system showed dosimetric accuracy comparable with the TPS, and identified several plans that exceeded dosimetric benchmarks. The M3D system possesses the potential to enhance the current treatment plan verification paradigm and improve safety in the clinical treatment planning and review process.