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Purpose Quantitative Cone Beam CT (CBCT) imaging is increasing in demand for precise image-guided radiotherapy because it provides a foundation for advanced image-guided techniques, including accurate treatment setup, online tumor delineation, and patient dose calculation. However, CBCT is currently limited only to patient setup in the clinic because of the severe issues in its image quality. In this study, we develop a learning-based approach to improve CBCT's image quality for extended clinical applications. Materials and methods An auto-context model is integrated into a machine learning framework to iteratively generate corrected CBCT (CCBCT) with high-image quality. The first step is data preprocessing for the built training dataset, in which uninformative image regions are removed, noise is reduced, and CT and CBCT images are aligned. After a CBCT image is divided into a set of patches, the most informative and salient anatomical features are extracted to train random forests. Within each patch, alternating RF is applied to create a CCBCT patch as the output. Moreover, an iterative refinement strategy is exercised to enhance the image quality of CCBCT. Then, all the CCBCT patches are integrated to reconstruct final CCBCT images. Results The learning-based CBCT correction algorithm was evaluated using the leave-one-out cross-validation method applied on a cohort of 12 patients' brain data and 14 patients' pelvis data. The mean absolute error (MAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC) indexes, and spatial nonuniformity (SNU) in the selected regions of interest (ROIs) were used to quantify the proposed algorithm's correction accuracy and generat the following results: mean MAE = 12.81 ± 2.04 and 19.94 ± 5.44 HU, mean PSNR = 40.22 ± 3.70 and 31.31 ± 2.85 dB, mean NCC = 0.98 ± 0.02 and 0.95 ± 0.01, and SNU = 2.07 ± 3.36% and 2.07 ± 3.36% for brain and pelvis data. Conclusion Preliminary results demonstrated that the novel learning-based correction method can significantly improve CBCT image quality. Hence, the proposed algorithm is of great potential in improving CBCT's image quality to support its clinical utility in CBCT-guided adaptive radiotherapy.

Frameless radiosurgery is an attractive alternative to the framed procedure if it can be performed with comparable precision in a reasonable time frame. Here, we present a positioning approach for frameless radiosurgery based on in‐room volumetric imaging coupled with an advanced six‐degrees‐of‐freedom (6 DOF) image registration technique which avoids use of a bite block. Patient motion is restricted with a custom thermoplastic mask. Accurate positioning is achieved by registering a cone‐beam CT to the planning CT scan and applying all translational and rotational shifts using a custom couch mount. System accuracy was initially verified on an anthropomorphic phantom. Isocenters of delineated targets in the phantom were computed and aligned by our system with an average accuracy of 0.2 mm, 0.3 mm, and 0.4 mm in the lateral, vertical, and longitudinal directions, respectively. The accuracy in the rotational directions was 0.1°, 0.2°, and 0.1° in the pitch, roll, and yaw, respectively. An additional test was performed using the phantom in which known shifts were introduced. Misalignments up to 10 mm and 3° in all directions/rotations were introduced in our phantom and recovered to an ideal alignment within 0.2 mm, 0.3 mm, and 0.4 mm in the lateral, vertical, and longitudinal directions, respectively, and within 0.3° in any rotational axis. These values are less than couch motion precision. Our first 28 patients with 38 targets treated over 63 fractions are analyzed in the patient positioning phase of the study. Mean error in the shifts predicted by the system were less than 0.5 mm in any translational direction and less than 0.3° in any rotation, as assessed by a confirmation CBCT scan. We conclude that accurate and efficient frameless radiosurgery positioning is achievable without the need for a bite block by using our 6 DOF registration method. This system is inexpensive compared to a couch‐based 6 DOF system, improves patient comfort compared to systems that utilize a bite block, and is ideal for the treatment of pediatric patients with or without general anesthesia, as well as of patients with dental issues. From this study, it is clear that only adjusting for 4 DOF may, in some cases, lead to significant compromise in PTV coverage. Since performing the additional match with 6 DOF in our registration system only adds a relatively short amount of time to the overall process, we advocate making the precise match in all cases. PACS number: 87.55.tm; 87.55.Qr; 87.57.nj

Volumetric modulated arc therapy (VMAT) is a system for intensity-modulated radiotherapy treatment delivery that achieves high dose conformality by optimizing the dose rate, gantry speed, and the leaf positions of the dynamic multileaf collimator (DMLC). The aim of this work is to present a practical approach for patient-specific volumetric reconstruction of the dose delivered of a VMAT treatment using the DMLC and treatment controller log (Dynalog) files. The accuracy of VMAT delivery was analyzed for five prostate patients. For each patient, a clinical treatment was delivered and values recorded in the log files for the gantry angle, dose rate, and leaf positions were converted to a new DICOM-compliant plan using a custom-developed software system. The plan was imported in a treatment planning system and the dose distribution was recreated on the original CT by simply recomputing the dose. Using the standard evaluation tools, it is straightforward to assess if reconstructed dose meets clinical endpoints, as well as to compare side-by-side reconstructed and original plans. The study showed that log files can be directly used for dose reconstruction without resorting to phantom measurements or setups. In all cases, analysis of the leaf positions showed a maximum error of -0.26 mm (mean of 0.15 mm). Gantry angle deviation was less than 1degree and the total MU was within 0.5 from the planned value. Differences between the reconstructed and the intended dose matrices were less than 1.46% for all cases. Measurements using the MATRIXX system in a phantom were used to validate the dosimetric accuracy of the proposed method, with an agreement of at least 96% in all pixels as measured using the gamma index. The methodology provides a volumetric evaluation of the dose reconstructed by VMAT plans which is easily achieved by automated analysis of Dynalog files without additional measurements or phantom setups. This process provides a valuable platform for adaptive therapy in the future.

Purpose: The purpose of this abstract was to evaluate the performance of commercial strategies for artifact reduction in radiation oncology settings. The iterative metal artifact reduction (Siemens iMAR) algorithm and monoenergetic virtual datasets reconstructed from dual energy scans are compared side-by-side in their ability to image in the presence of metal inserts. Methods: A CIRS ATOM Dosimetry Verification Phantom was scanned with and without a metal insert on a SOMATOM Definition AS dual energy scanner. Images with the metal insert were reconstructed with (a) a tradition single energy CT scan with the iMAR option implemented, using different artifact reduction settings and (b) a monoenergetic scan calculated from dual energy scans by recovering differences in the energy-dependence of the attenuation coefficients of different materials and then creating a virtual monoenergetic scan from these coefficients. The iMAR and monoenergetic scans were then compared with the metal-free scan to assess changes in HU numbers and noise within a region around the metal insert. Results: Both the iMAR and dual energy scans reduced artifacts produced by the metal insert. However the iMAR results are dependent of the selected algorithm settings, with a mean HU difference ranging from 0.65 to 90.40 for different options. The mean differences without the iMAR correction were 38.74. When using the dual energy scan, the mean differences were 4.53, that is however attributed to increased noise and not artifacts, as the dual energy scan had the lowest skewness (2.52) compared to the iMAR scans (ranging from 3.90 to 4.88) and the lowest kurtosis (5.72 for dual energy, range of 18.19 to 27.36 for iMAR). Conclusion: Both approaches accurately recovered HU numbers, however the dual energy method provided smaller residual artifacts.

Purpose: The purpose of this study is to investigate a volumetric modulated arc therapy (VMAT) treatment planning technique for supine craniospinal irradiation (CSI). Evaluate the suitability of VMAT for CSI with dosimetric measurements and compare it to 3D conformal planning using specific plan metrics such as dose conformity, homogeneity, and dose of organs at risk (OAR). Methods: Ten CSI patients treated with conventional 3D technique were re-planned with VMAT. The PTV was contoured to include the whole contents of the brain and spinal canal with a uniform margin of 5 mm. VMAT plans were generated with two partial arcs covering the brain, two partial arcs for the superior portion of the spinal cord and two partial arcs covering the remaining inferior portion of the spinal cord. Conformity index (CI), heterogeneity indexes (HI) and max and mean doses of OAR were compared to 3D plans. VMAT plans were delivered onto an anthropomorphic phantom loaded with Gafchromic films and OSLDs placed at specific positions to evaluate the plan dose at the junctions and as well as the plan dose distributions. Results: This VMAT technique was validated with a clinical study of 10 patients. The average CI was 1.03±0.02 for VMAT plans and 1.96±0.32 for conformal plans. And the average HI was 1.15±0.01 for VMAT plans and 1.51±0.21 for conformal plans. The mean and max doses to the all OARs for VMAT plans were significantly lower than conformal plans. The measured dose in phantom for VAMT plans was comparable to the calculated dose in Eclipse and the doses at junctions were verified. Conclusion: VMAT CSI was able to achieve better dose conformity and heterogeneity as well as significantly reducing the dose to Heart, esophagus and larynx. VMAT CSI appears to be a dosimterically advantageous, faster delivery, has better reproducibility CSI treatment.

Purpose: Cone beam computed tomography (CBCT) imaging is on increasing demand for high-performance image-guided radiotherapy such as online tumor delineation and dose calculation. However, the current CBCT imaging has severe scatter artifacts and its current clinical application is therefore limited to patient setup based mainly on the bony structures. This study's purpose is to develop a CBCT artifact correction method. Methods: The proposed scatter correction method utilizes the planning CT to improve CBCT image quality. First, an image registration is used to match the planning CT with the CBCT to reduce the geometry difference between the two images. Then, the planning CT-based prior information is entered into the Bayesian deconvolution framework to iteratively perform a scatter artifact correction for the CBCT mages. This technique was evaluated using Catphan phantoms with multiple inserts. Contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR), and the image spatial nonuniformity (ISN) in selected volume of interests (VOIs) were calculated to assess the proposed correction method. Results: Post scatter correction, the CNR increased by a factor of 1.96, 3.22, 3.20, 3.46, 3.44, 1.97 and 1.65, and the SNR increased by a factor 1.05, 2.09, 1.71, 3.95, 2.52, 1.54 and 1.84 for the Air, PMP, LDPE, Polystryrene, Acrylic, Delrin and Teflon inserts, respectively. The ISN decreased from 21.1% to 4.7% in the corrected images. All values of CNR, SNR and ISN in the corrected CBCT image were much closer to those in the planning CT images. The results demonstrated that the proposed method reduces the relevant artifacts and recovers CT numbers. Conclusion: We have developed a novel CBCT artifact correction method based on CT image, and demonstrated that the proposed CT-guided correction method could significantly reduce scatter artifacts and improve the image quality. This method has great potential to correct CBCT images allowing its use in adaptive radiotherapy.

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel's gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel's gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.

Purpose: Treatment plan compliance to physician's intent is still assessed by hand in clinical practice by visually comparing prescription details against corresponding plan values. We report on a script that uses the Varian's programming interface to automate the scoring of treatment plan dose values to the physician's prescribed constraints. Methods: The Eclipse Scripting Advance Programming Interface (ESAPI) is a FDA-approved scripting environment written in C# that allows programming access to a patient's record in Aria and Eclipse. With the ESAPI, it is possible to create customized add-on software libraries that can be installed in the planning system as a pull-down menu item. We used the flexibility of ESAPI to parse plan quality metrics from the prescription and compare them automatically against the corresponding plan values. The script can check fractionation as well as minimum, mean and maximum doses to an organ specified in the prescription, DVHs metrics such as volume or dose coverage for both targets and critical organs, conformity indexes specific to radio surgery and biological indexes such as EUD, TCP and NCTP. Lists of generally accepted constraints limits, such as QUANTEC or clinical trials constraints are implemented in the script and can be invoked to automatically fill the prescription. Results: The script interprets the prescription and compares plan quality indices parsed from it against the counterpart values extracted from the plan. A coloring scheming is employed to automatically mark with green, yellow or red plan quality metrics that meet, are borderline fail (10%) or fail the prescription criteria. While manually performing this task can take 30 minutes for a complex head and neck case with many constraints, the script takes approximately 1 minute. Conclusion: The script provided easy to understand feedback on quality metrics in a simple and practical solution that significantly streamline plan double-checks in clinical practice.

Purpose: Rotational total skin electron irradiation (RTSEI) is used in the treatment of cutaneous T-cell lymphoma. Due to inter-film uniformity variations the dosimetry measurement of a large electron beam of a very low energy is challenging. This work provides a method to improve the accuracy of flatness and symmetry for a very large treatment field of low electron energy used in dual beam RTSEI. Methods: RTSEI is delivered by dual angles field a gantry of ±20 degrees of 270 to cover the upper and the lower halves of the patient body with acceptable beam uniformity. The field size is in the order of 230cm in vertical height and 120 cm in horizontal width and beam energy is a degraded 6 MeV (6 mm of PMMA spoiler). We utilized parallel plate chambers, Gafchromic films and OSLDs as a measuring devices for absolute dose, B-Factor, stationary and rotational percent depth dose and beam uniformity. To reduce inter-film dosimetric variation we introduced a new specific correction method to analyze beam uniformity. This correction method uses some image processing techniques combining film value before and after radiation dose to compensate the inter-variation dose response differences among films. Results: Stationary and rotational depth of dose demonstrated that the Rp is 2 cm for rotational and the maximum dose is shifted toward the surface (3mm). The dosimetry for the phantom showed that dose uniformity reduced to 3.01% for the vertical flatness and 2.35% for horizontal flatness after correction thus achieving better flatness and uniformity. The absolute dose readings of calibrated films after our correction matched with the readings from OSLD. Conclusion: The proposed correction method for Gafchromic films will be a useful tool to correct inter-film dosimetric variation for the future clinical film dosimetry verification in very large fields, allowing the optimizations of other parameters.

Purpose: To investigate potential dosimetrical differences between the Acuros XB (AXB) and AAA dose calculation algorithms, with a specific focus on lung SBRT treatments involving inherently high degrees of anatomical heterogeneity, small field sizes, and varying tumor locations relative to critical structures. Methods: A cohort of 20 SBRT patients treated in our clinic was selected to include varying lung tumor locations. For each patient, the Eclipse treatment planning system was employed to generate a lung SBRT plan using the AXB dose calculation algorithm, in addition to the AAA plan previously calculated for clinical use. The plans were then compared using common plan evaluation metrics. To assess the accuracies of the algorithms in a highly heterogeneous medium, identical AAA and AXB plans were delivered to a slab phantom consisting of solid water and a low-density insert representing lung. Field sizes of 3 × 3 cm through 12 × 12 cm were considered. The phantom dose was measured with OSLDs and radiochromic film and compared to the calculated dose distributions. Results: The average difference in mean PTV dose between the AAA and AXB plans, expressed as a percentage of the prescription dose, was 2.24% ± 1.58%. The differences in doses to critical structures were negligible. The OSLD and film measurements showed that the AXB dose calculations are more accurate in heterogeneous media. The difference between the algorithms became more significant as field size decreased. Using the same dose normalization, the conformity indices for the AAA plans were slightly closer to unity than the AXB plans. This was expected due to the higher dose calculation accuracy of AXB in heterogeneous media. Conclusion: Our results emphasize the importance of AXB for lung SBRT dose calculations due to its superiority in calculating dose for small lesions in heterogeneous tissue.

Purpose: To determine if SBRT is more susceptible to delivery uncertainties when using either RapidArc or dynamic IMRT. Methods: Systematic or random uncertainties in MLC leaf positions, gantry position and dose rate were incorporated into RapidArc (RA) and sliding-window IMRT (SW) treatment plans for retrospective SBRT lung and liver cases, which also included the use of FFF or SRS energies and therefore higher dose rates. Initial plan comparisons included homogeneity and conformity indices. Dose distributions and dose-value histograms of original and modified plans were compared using Gamma analysis and dose indices of planned treatment volumes (PTV) and organs at risk (OAR). Results: SBRT lung PTVs using RA were more susceptible to systematic MLC delivery errors than SW (∼6%/mm vs. ∼4%/mm), in contrast to a previous study examining hyperfractionated prostate and head-and-neck treatments; esophagus and cord Dmin and Dmax values changed proportionately for both techniques; RA plans were superior globally but not locally (PTV) using Gamma analyses. Uniformly distributed random variations of 2 mm for active MLC leaves had a negligible effect on all PTV dose distributions (Dmin, Dmax < 0.4%). PTV coverage was affected equally when incorporating systematic gantry errors. Conclusion: RapidArc deliveries were found to be more sensitive to systematic errors in MLC leaf positions, in contrast to a previous study on hyperfractionated treatments. However, this is reasonable as both studies correlate average segmental field size or mean leaf gap with adverse dosimetric effects due to such uncertainties; mean leaf gaps for either technique in this study were similar. Gantry angle variations had similar effects on both techniques.

Purpose: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Methods: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Results: Highly attenuating copper rods cause severe streaking artifacts on standard CT images. EDEC improves the image quality, but cannot eliminate the streaking artifacts. Compared to EDEC, the proposed ADEC method further reduces the streaking resulting from metallic inserts and beam-hardening effects and obtains material decomposition images with significantly improved accuracy. Conclusion: We propose an adaptive dual energy calibration method to correct for metal artifacts. ADEC is evaluated with the Shepp-Logan phantom, and shows superior metal artifact correction performance. In the future, we will further evaluate the performance of the proposed method with phantom and patient data.

Purpose: The aim of this study is the use of data mining techniques to establish an automated daily chart check. This automated technique increases the likelihood of error capture before subsequent treatment delivery, allowing the delivery of the prescribed treatment course with high confidence level. Furthermore, the scope of inspected parameters expands compared to that able to be performed manually. Methods: Considering the significant number of parameters that are checked, performing chart check manually has a number of shortfalls such as human error, comparison of incorrect field and inability to verify MLC shape and leaves positions. Developing a computer-driven automatic chart checkers eliminates human error, improves the accuracy and the frequency of the process, shortens the time of error discovery and correction, increases the number of parameters that are checked, allows inspection of parameters that are impossible to check manually and reduces the time the physicist need to spend to check a chart. This work will utilizes in house data mining framework (RT Metrix) to establish this QA function. The system utilize ARIA data base to verify the treatment delivery by comparing the plan record in ARIA to record verification which is the delivery parameters. Acceptable tolerances were defined in the software. If the delivery variation from the tolerance is minor then the system will show a warning flag but if the variation is major the system will flag the delivery as failed. Results: This system has been developed, tested, compared to ARIA Chart QA and is currently able to check parameters that routinely checked by the clinical physicist. Conclusion: The automated chart check system is feasible and offers great potential in the improvement of patient delivery quality assurance. The system can be developed further to include more QA functions.

Purpose: To demonstrate the feasibility of a predictive planning tool which provides SRS planning guidance based on simple patient anatomical properties: PTV size, PTV shape and distance from critical structures. Methods: Ten framed SRS cases treated at Winship Cancer Institute of Emory University were analyzed to extract data on PTV size, sphericity (shape), and distance from critical structures such as the brainstem and optic chiasm. The cases consisted of five pairs. Each pair consisted of two cases with a similar diagnosis (such as pituitary adenoma or arteriovenous malformation) that were treated with different techniques: DCA, or IMRS. A Naive Bayes Classifier was trained on this data to establish the conditions under which each treatment modality was used. This model was validated by classifying ten other randomly-selected cases into DCA or IMRS classes, calculating the probability of each technique, and comparing results to the treated technique. Results: Of the ten cases used to validate the model, nine had their technique predicted correctly. The three cases treated with IMRS were all identified as such. Their probabilities of being treated with IMRS ranged between 59% and 100%. Six of the seven cases treated with DCA were correctly classified. These probabilities ranged between 51%more » and 95%. One case treated with DCA was incorrectly predicted to be an IMRS plan. The model’s confidence in this case was 91%. Conclusion: These findings indicate that a predictive planning tool based on simple patient anatomical properties can predict the SRS technique used for treatment. The algorithm operated with 90% accuracy. With further validation on larger patient populations, this tool may be used clinically to guide planners in choosing an appropriate treatment technique. The prediction algorithm could also be adapted to guide selection of treatment parameters such as treatment modality and number of fields for radiotherapy across anatomical sites.« less

Purpose: To investigate the dosimetric and localization effects of one‐versus two‐isocenter SRS. Methods: A library of 50 retrospective patient plans was compiled for cases of two brain lesions. One‐and two‐isocenter plans were generated. One‐isocenter plans consisted of four non‐coplanar‐VMAT arcs; isocenter was positioned midway between two lesions. In the two‐isocenter approach, each lesion was planned separately using four non‐coplanar DCA. DCA plans were summed. All plans were normalized so that 21 Gy covers 100% of the PTVs. Dosimetry and localization errors were studied for one‐and two‐isocenter plans. Normal tissue dose, V12, was evaluated as a function of lesion morphology and separation distance. Plans were exported to Velocity, where localization errors were simulated using rotations of 0°, 0.5°, 1°, and 2° about each isocenter. The effect of rotational misalignments on PTV coverage was compared for D95 and minimum dose. Results: Findings from 10 cases are reported. Analysis of one‐versus two‐isocenter plans shows that the V12 is comparable at lesion separations of 8 cm or less, while V12 is higher for one‐isocenter plans at greater separations. As lesion volume increases, V12 increases more for one‐isocenter plans. The effects of localization errors on target coverage were investigated. For 2° rotational errors on one‐isocenter plans, D95 decreases on average by 7%, whereas the decrease for two‐isocenter plans is 0.5%. Minimum PTV dose decreases more substantially: 12% versus 1% respectively for the one‐and two‐isocenter plans. The above values are averaged over all lesion separations. For the largest separation of 15 cm, minimum PTV dose decreases by 37% for the one‐isocenter plan. Conclusions: Localization becomes more important as separation increases for one‐isocenter SRS. Findings suggest that lesion morphology and separation should be considered when deciding between one‐and two‐isocenter SRS because of the effects on normal tissue dose and target coverage.

Purpose: To characterize the risks of compromised coverage in single-isocenter multiple-lesion VMAT SRS. Methods: Fifty patients were selected retrospectively from our SRS program. Each patient had two lesions treated to ≥ 21 Gy. Single-isocenter VMAT SRS plans were created in Eclipse. PTV volumes and distances from isocenter were recorded. PTV coverage (D95 and V95) was evaluated across rotational setup errors of 0.5, 1.0, or 2° applied to three axes. Coverage rates were analyzed versus volume, distance, and rotation. For a rotational error of 2°, lesion size and separation distance were compared across coverage rate levels using ANOVA. A multivariate logistic regression model was fit using generalized estimating equations (GEE), modeling the probability of a 95% V95/D95 rate or higher given lesion size and separation distance while accounting for intra-patient correlation. The estimated probabilities from the GEE model were used to capture the operating conditions in a receiver operating characteristic (ROC) curve; area under the curve (AUC) was estimated. Results: Mean lesion volume and distance to isocenter are 0.96±1.25cc and 3.53±1.61cm. V95/D95 proportions above 95% range from 92-100% when rotational errors are ≤1°. At 2.0° rotation, V95/D95 are >95% in only 62–64% of cases; V95 falls to 75% for 90% up to 6cm for lesions >0.9cc. V95 is 4cm from isocenter. Statistical analysis suggests that lesion volume and distance to isocenter could be used to select patients who are good candidates for single-isocenter multiple-lesion SRS.

Purpose: Acoustic neuroma is treated using highly conformal, framed-based radiosurgery. The gross target volume (GTV) is located near the radiosensitive brainstem. Currently, plan evaluation methods that consider GTV dose conformity and dose to organs at risk (OAR) do not account for setup uncertainty, thereby potentially giving a false sense of target coverage and OAR sparing. More realistic plan evaluations should consider delivery uncertainties. In this work, we introduce a new plan evaluation method based on probability and investigate the effect of translational and rotational setup errors. Methods: Clinically approved 18 acoustic neuroma treatment plans were studied retrospectively. For each treatment plan, 200 new dose distributions were re-calculated while introducing both translational (in all cardinal directions) and rotational errors (in all 3 orthogonal rotation angles). The magnitude of errors for each simulation was randomly generated from the Gaussian distribution with one standard deviation of 0.5 mm and 0.5 degree respectively. From the simulated dose distributions, an approximated probability density function of dose objective for both GTV and brainstem were calculated. The probability density function was then used to compute the probability of delivering prescribed dose to 90% of GTV for each patient. For brainstem, the probability of limiting maximum dose to 11Gy was calculated. These probabilistic metrics were then analyzed with respect to GTV volume, conformity index, and min and max dose to the GTV and brainstem. Results: Across all cases, the average probability of delivering prescribed dose to the 90% of GTV volume was 85±14%. Four patients showed > 50% risk of exceeding 11Gy limit to the brainstem. Conclusion: In highly conformal, single fraction radiosurgery, a small setup error can be critical. We found that the probabilistic assessment of plan objectives can be used to quantitatively assess true target coverage better than the conventional plan assessment metrics.

Purpose: To investigate the extent and necessity of 6 DOF corrections for intracranial frameless Stereotactic Radiosurgery Methods: Civco Protura 6D robotic couch top was fitted to the Novalis TX in 2012. The couch enables ± 3 ° rotations in pitch, roll and yaw, ±50 mm in lateral and longitudinal shifts and ±25 mm in vertical shifts. Patient sets up using the room laser; then two orthogonal kV images are taken for confirmation. A CBCT is acquired and registered to the planning CT using two independent systems. The calculated rotational and translational shifts are applied. A second CBCT is acquired to assess the residual translational and rotational errors. The treatment will be carried out if residual rotational shifts are ≤ 0.3 degrees. We treated 113 patients utilizing 6D couch to align a total of 160 targets. Some of the targets were fractionated, with total alignments of 252. Geometrical analysis is performed to assess the system's accuracy and extent of shifts. Results: After the planar kV images alignment, a CBCT was acquired and registered to the planning CT, the average required rotational shifts were (yaw=1.03 °± 0.8, roll=1.16°± 0.9 and Pitch= 0.9°± 0.7). A second CBCT was taken to verify the match and the previous shifts, the residual rotational errors on average were 0.37°± 0.6, 0.27°± 0.28 and 0.24°± 0.29 in the yaw, roll, and pitch directions, respectively. The translational residual shifts (mm) were 0.68 ± 0.57, 0.68 ± 0.57, 0.68 ± 0.57 in lateral, vertical, and longitudinal directions, respectively. Conclusion: The 6D couch is capable of aligning targets with an accuracy of ≤ 0.4 ° in any rotational direction and ≤ 0.7 mm in any translational directions, and not applying the rotational corrections could lead to compromised target dose coverage and may lead to excessive dose to OARs.

Purpose: Evaluate the robustness of two different planning techniques for SBRT patients with two lung lesions: with both PTVs treated simultaneously with one isocenter, or separately with an isocenter for each PTV. Methods: One- and two-isocenter IMRT and VMAT SBRT plans were created in Varian Eclipse for five patients who each had two lung lesions. PTV coverage for the one- and two-isocenter plans was similar when possible. Rotational setup errors were simulated using couch rotations of various angles, and the resulting dose distributions were calculated. Results: With a 2° setup error, the average decrease in PTV volume receiving at least the prescribed dose (V100%) was 1.66% for the oneisocenter plans, and 0.05% for the two-isocenter plans. The changes in V100% ranged from +0.33% to 4.06% for one-isocenter plans, and from +0.23% to −0.30% for two-isocenter plans. With a 5° setup error, the average decrease in V100% was 6.46% for a one-isocenter plan (range: −0.19% to −13.18%), and 0.42% for a two-isocenter plan (range: +0.21% to −1.33%). For one-isocenter plans, the decrease in V100% tended to increase as PTV separation increased. The three patients with PTV separation less than 10 cm each showed a decrease in V100% of less than 1% for a 2° error, while the two patients with larger PTV separations showed decreases of more than 3%. Conclusion: As could be predicted by geometric calculations, when a rotational setup error occurs, the PTV coverage decreased more for a one-isocenter plan than for a two-isocenter plan. These findings suggest that, in general, for lung SBRT patients with two lesions, the two-isocenter technique may be preferable. However, they may also suggest that if the PTVs are separated by less than 10 cm, and there is high confidence that setup errors are small (≤ 2°), a one-isocenter plan may deliver similar coverage.

Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. The CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.

Purpose: The Volumetric Modulated Arc Therapy (VMAT) technology is a novel delivery method that is capable of producing highly conformal dose distributions though concomitant optimization of MLC shapes, dose rate and gantry speed. The aim of this work is to present a practical approach for patient—specific volumetric reconstruction of the dose delivered of a VMAT treatment using the DMLC and treatment controller log (Dynalog) files. Method: The accuracy of VMAT delivery was analyzed for prostate patients. For each patient, a clinical treatment was reconstructed and values recorded in the log files for the gantry angle, dose rate and leaf positions were converted to a new DICOM‐compliant plan using a custom‐developed software system. The plan was imported in a treatment planning system and the reconstructed dose was recreated on the original CT by simply recomputing the dose. Reconstructed and planned doses together with original CT scan and delineated structures are in the same coordinate systems and can be combined directly or verified through dose‐volume histograms to asses treatment objective degradation due to machine imprecision. Results: In all cases, analysis of the leaf positions showed a maximum error of −0.26 mm (mean 0.15 mm). Gantry speed deviation was less than 1° and the delivered MU was within 0.001 % from the planned value. Measurements using the Matrixx system in a phantom were used to validate the dosimetric accuracy of the proposed method, with an agreement of at least 96% using the gamma index. Conclusions: The methodology provides an volumetric evaluation of the dose delivered by VMAT plans, easily achieved by automated analysis of Dynalog files without additional measurements or phantom setups. It provides a valuable platform for adaptive therapy in future.

Purpose: The surface and buildup dose is known to be greater for flattening‐filter‐free (FFF) beams as compared to flattened beams. We compare the effect of this difference in the dose buildup region between the two beam modes, in the context of IMRT plans for the lung and sinuses. Methods:IMRT plans are delivered using both the standard flattened beam mode (6X) and flattening‐filter‐free mode (6XFFF). We compare the dosimetric differences of these two modes, for IMRT treatments for the lung and sinuses. Radiochromic films and parallel‐plate ionization chamber measurements were taken, and evaluated for the following field sizes: 2×2 cm2, 3×3 cm2, 5×5 cm2, 8×8 cm2, 10×10 cm2, and 20×20 cm2. We evaluated the area under the PDD curve (AUC) for the buildup region for both 6X and 6XFFF beams. Ten SBRTlung and five IMRT sinuses plans were generated using the EclipseTM planning system, commissioned with AAA. Plan evaluation involved the comparison of the isodose distributions between plans of the two delivery modes. Results: For small field sizes, the dose in the buildup region is greater for FFF beam than for flattened beam. The percentage differences between 6XFFF and 6X flattened beams for the following field sizes (2×2 cm2, 3×3 cm2, 5×5 cm2, 8×8 cm2, 10×10 cm2, and 20×20 cm2) are 3.4%,2.2%, 7.2%, 4.9%, 0.9%, and −0.5%, respectively. Plan evaluation of the IMRT sinus cases found approximately 3% higher maximum dose within the PTV for FFF plans. No observable differences were found between two types of SBRTlung plans. Conclusions: For small fields, the dose buildup region of FFF beam is slightly greater than that of flattened beams. This effect is more pronounced in IMRT sinus cases, leading to higher dose within the PTV. There was no difference in the SBRTlung plans between the two beam modes.