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In proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions.A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU.Neutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared.Integrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries.VPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.

Purpose Due to the employment of quadratic programming using soft constraints to implement dose volume constraints and the "trial-and-error" procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity-modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per-voxel constraints to minimize hot spots in LET-guided robust optimization. Methods and materials Ten BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: 1) diagnosis of brain necrosis during follow-up; 2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose-only robust optimization, the other using LET-guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per-voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose-volume histogram (DVH) and xBD dose-volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose-LET-volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed-rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose-only and the LET-guided robustly optimized plans. Results Per-voxel constraints effectively and efficiently minimized dose hot spots in both dose-only and LET-guided robust optimization and LET hot spots in LET-guided robust optimization. Compared to the conventional dose-only robust optimization, the LET-guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50Gy[RBE], P = 0.009; VxBD,60Gy[RBE], P = 0.025; xBD1cc, P = 0.017; xBD2cc, P = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET-guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions. Conclusion Per-voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET-guided robustly optimized plans outperformed the conventional dose-only robustly optimized plans in terms of xBD hot spots control. This article is protected by copyright. All rights reserved.

Purpose: Recent studies of radiotherapy (RT) for stage III non-small-cell lung cancer (NSCLC) have associated high dose to the heart with cardiac toxicity and decreased overall survival (OS). We used advanced statistical techniques to account for correlations between dosimetric variables and more accurately determine the range of heart doses which are associated with reduced OS in patients receiving RT for stage III NSCLC. Methods: From 2006 to 2013, 119 patients with stage III NSCLC received definitive RT at our institution. OS data was obtained from institutional tumor registry. We used multivariate Cox model to determine patient specific covariates predictive for reduced overall survival. We examined age, prescription dose, mean lung dose, lung V20, RT technique, stage, chemotherapy, tumor laterality, tumor volume, and tumor site as candidate covariates. We subsequently used novel statistical techniques within multivariate Cox model to systematically search the whole heart dose-volume histogram (DVH) for dose parameters associated with OS. Results: Patients were followed until death or 2.5 to 81.2 months (median 30.4 months) in those alive at last follow up. On multivariate analysis of whole heart DVH, the dose of 51 Gy was identified as a threshold dose above which the dose volume relationship becomes predictive for OS. We identified V55Gy (percentage of the whole heart volume receiving at least 55 Gy) as the best single DVH index which can be used to set treatment optimization constraints (Hazard Ratio = 1.044 per 1% increase in heart volume exposed to at least 55 Gy, P = 0.03). Additional characteristics correlated with OS on multivariate analysis were age, stage (IIIA/IIIB), and administration of chemotherapy. Conclusion: Doses above 51 Gy, applied to small volumes of the heart, are associated with worse OS in stage III NSCLC patients treated with definitive RT. Higher stage, older age and lack of chemotherapy were also associated with reduced OS.

We proposed a novel tool-a dose linear energy transfer (LET)-volume histogram (DLVH)-and performed an exploratory study to investigate rectal bleeding in prostate cancer treated with intensity modulated proton therapy.The DLVH was constructed with dose and LET as 2 axes, and the normalized volume of the structure was contoured in the dose-LET plane as isovolume lines. We defined the DLVH index, DLv%(d,l) (ie, v% of the structure) to have a dose of ≥d Gy and an LET of ≥l keV/μm, similar to the dose-volume histogram index Dv%. Nine patients with prostate cancer with rectal bleeding (Common Terminology Criteria for Adverse Events grade ≥2) were included as the adverse event group, and 48 patients with no complications were considered the control group. A P value map was constructed by comparison of the DLVH indices of all patients between the 2 groups using the Mann-Whitney U test. Dose-LET volume constraints (DLVCs) were derived based on the P value map with a manual selection procedure facilitated by Spearman's correlation tests. The obtained DLVCs were further cross-validated using a multivariate support vector machine (SVM)-based normal tissue complication probability (NTCP) model with an independent testing data set composed of 8 adverse event and 13 control patients.We extracted 2 DLVC constraints. One DLVC was obtained, Vdose/LETboundary:2.5keVμmat 75 Gy to 3.2keVμmat8.65Gy1.27% (DLVC1), revealing a high LET volume effect. The second DLVC, V(72.2Gy,0keVμm)2.23% (DVLC2), revealed a high dose volume effect. The SVM-based NTCP model with 2 DLVCs provided slightly superior performance than using dose only, with an area under the curve of 0.798 versus 0.779 for the testing data set.Our results demonstrated the importance of rectal "hot spots" in both high LET (DLVC1) and high dose (DLVC2) in inducing rectal bleeding. The SVM-based NTCP model confirmed the derived DLVCs as good predictors for rectal bleeding when intensity modulated proton therapy is used to treat prostate cancer.

Purpose To compare the dosimetric performances of small-spot three-dimensional (3D) and four-dimensional (4D) robustly optimized intensity-modulated proton (IMPT) plans in the presence of uncertainties and interplay effect simultaneously for distal esophageal carcinoma. Method and materials Thirteen (13) patients were selected and re-planned with small-spot ( σ ~ 2-6 mm) 3D and 4D robust optimization in IMPT, respectively. The internal clinical target volumes (CTVhigh3d , CTVlow3d ) were used in 3D robust optimization. Different CTVs (CTVhigh4d , CTVlow4d ) were generated by subtracting an inner margin of the motion amplitudes in three cardinal directions from the internal CTVs and used in 4D robust optimization. All patients were prescribed the same dose to CTVs (50 Gy[RBE] for CTVhigh3d /CTVhigh4d and 45 Gy[RBE] for CTVlow3d /CTVlow4d ). Dose-volume histogram (DVH) indices were calculated to assess plan quality. Comprehensive plan robustness evaluations that consisted of 300 perturbed scenarios (10 different motion patterns to consider irregular motion (sampled from a Gaussian distribution) and 30 different uncertainties scenarios (sampled from a 4D uniform distribution) combined), were performed to quantify robustness to uncertainties and interplay effect simultaneously. Wilcoxon signed-rank test was used for statistical analysis. Results Compared to 3D robustly optimized plans, 4D robustly optimized plans had statistically improved target coverage and better sparing of lungs and heart (heart Dmean , P = 0.001; heart V30Gy[RBE] , P = 0.001) in the nominal scenario. 4D robustly optimized plans had better robustness in target dose coverage (CTVhigh4d V100% , P = 0.002) and the protection of lungs and heart (heart Dmean , P = 0.001; heart V30Gy[RBE] , P = 0.001) when uncertainties and interplay effect were considered simultaneously. Conclusions Even with small spots in IMPT, 4D robust optimization outperformed 3D robust optimization in terms of normal tissue protection and robustness to uncertainties and interplay effect simultaneously. Our findings support the use of 4D robust optimization to treat distal esophageal carcinoma with small spots in IMPT.

Purpose: To examine possible association between heart irradiation and Overall Survival (OS) in lung SBRT patients and to compare observed associations with cardiac toxicity models previously derived in LA-NSCLC patient studies. Materials and Methods: 197 Patients treated with lung SBRT at Mayo Clinic Arizona were selected for this IRB-approved study. Multivariate Cox model with Akaike Information Criterion (AIC) was used to select patient specific covariates associated with OS. Heart dosimetry was represented by VD indices, which is a percentage of volume exposed to dose D or greater. Multivariate Cox models with patient specific covariates and single VD index per model was used to find a range of doses which were predictive for OS. A digital subdivision of the heart was further used to determine the spatial distribution of doses which were predictive for OS. A coarse subdivision divided heart into 4 segments, while the fine subdivision divided heart into 64 segments. Knowledge constrained Fused Lasso operator was used to derive a more complete model which correlated heart dosimetry with OS. Results of statistical analysis were compared to predictions of a model of cardiac toxicity in LA-NSCLC patients. Results: Higher age (p < 0.001), higher stage (p < 0.001) and squamous cell histology (p = 0.001) were associated with reduced OS. Whole heart DVH analysis did not reveal associations between heart irradiation and reduced OS. Coarse subdivision of the heart into four segments revealed that the irradiation of two inferior segments of the heart with low doses was associated with reduced OS, V2Gy in the right-inferior segment (HR = 1.012/1%, p = 0.02), and V1Gy in the left-inferior segment (HR = 1.01/1%, p = 0.04). Maximum dose in the right-inferior segment of the heart was also associated with reduced OS (HR = 1.02/Gy, p = 0.02). Fine subdivision of the heart into 64 segments revealed that approximately 25% of heart volume in the inferior part of the heart (15/64 segments), when irradiated to doses in the 1 Gy - 5 Gy range, were predictive for reduced OS (HR = 1.01/1%, p = 0.01). A previously derived model of cardiac toxicity in LA-NSCLC patients did not predict a reduction of OS due to heart irradiation in lung SBRT patients, because of relatively low doses to the heart in most lung SBRT patients. Conclusions: Doses lower than 5 Gy in the inferior segments of the heart may be associated with reduced overall survival in patients treated for lung lesions with SBRT. Stage and histology of the disease, as well as patients’ age, were also associated with overall survival. Comparisons of cardiac toxicity patterns in LA-NSCLC patients and lung SBRT patients suggest different etiology of cardiac toxicity in the two groups.

To develop an online graphic processing unit (GPU)-accelerated Monte Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS.A four-step workflow was developed using our in-house developed GPU-accelerated Monte Carlo-based treatment planning system to implement online Monte Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient-specific quality assurance (PSQA) of the reoptimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS.For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833-0.983) and DSC (0.909-0.992)] but suboptimal boundary coincidence [HD (2.37-20.76 mm)] for organs-at-risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention.The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.

Purpose To compare the dosimetric performances of intensity-modulated proton therapy (IMPT) plans generated with two different beam angle configurations (the Right-Left oblique posterior beams and the Superior-Inferior oblique posterior beams) for the treatment of distal esophageal carcinoma in the presence of uncertainties and interplay effect. Methods and materials Twenty patients' IMPT plans were retrospectively selected, with 10 patients treated with the R-L oblique posterior beams (Group R-L) and the other 10 patients treated with the S-I oblique posterior beams (Group S-I). Patients in both groups were matched by their clinical target volumes (CTVs-high and low dose levels) and respiratory motion amplitudes. Dose-volume-histogram (DVH) indices were used to assess plan quality. DVH bandwidth was calculated to evaluate plan robustness. Interplay effect was quantified using four-dimensional (4D) dynamic dose calculation with random respiratory starting phase of each fraction. Normal tissue complication probability (NTCP) for heart, liver, and lung was calculated, respectively, to estimate the clinical outcomes. Wilcoxon signed-rank test was used for statistical comparison between the two groups. Results Compared with plans in Group R-L, plans in Group S-I resulted in significantly lower liver Dmean and lung V30Gy[RBE] with slightly higher but clinically acceptable spinal cord Dmax . Similar plan robustness was observed between the two groups. When interplay effect was considered, plans in Group S-I performed statistically better for heart Dmean and V30Gy[RBE] , lung Dmean and V5Gy[RBE] , and liver Dmean , with slightly increased but clinically acceptable spinal cord Dmax . NTCP for liver was significantly better in Group S-I. Conclusions IMPT plans in Group S-I have better sparing of liver, heart, and lungs at the slight cost of spinal cord maximum dose protection, and are more interplay-effect resilient compared to IMPT plans in Group R-L. Our study supports the routine use of the S-I oblique posterior beams for the treatments of distal esophageal carcinoma.

PURPOSE Intensity-modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient's outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them. METHODS We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient-specific breathing pattern parameters as acquired during the four-dimensional (4D)-computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients' respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose-volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application's example, we compared plan robustness under both three-dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non-small cell lung cancer. RESULTS The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D95% , P = 0.002), CTV homogeneity (D5% -D95% , P = 0.002) with less target hot spots (D5% , P = 0.002), and target coverage robustness (CTV D95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung Dmean , P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min. CONCLUSION A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real-time intra-fractional interplay effect evaluation as a potential application for future use.

Purpose To commission an open source Monte Carlo (MC) dose engine, “MCsquare” for a synchrotron‐based proton machine, integrate it into our in‐house C++‐based I/O user interface and our web‐based software platform, expand its functionalities, and improve calculation efficiency for intensity‐modulated proton therapy (IMPT). Methods We commissioned MCsquare using a double Gaussian beam model based on in‐air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread‐out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++‐based dose calculation code and web‐based second check platform “DOSeCHECK.” We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well‐benchmarked GPU‐accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)‐related model‐dependent biological dose calculation. Results Differences between MCsquare calculations and SOBP measurements were

A successful proton beam therapy (PBT) center relies heavily on the proper function and maintenance of a proton beam therapy machine. However, when a PBT machine is non-operational, a proton facility is hindered with delays that can potentially lead to inferior treatment outcome due to treatment interruption. This article reports a viable solution for a photon back-up plan in a proton down event.The implementation of a workflow for which proton plans are converted to photon plans so that patients can be treated using photons has been a successful strategy to reduce delays and mitigate its effect on patient care. This workflow was established through collaboration of physicians, physicists, dosimetrists, therapists, nurses, and schedulers.A tiered system established by disease site, number of fractions, and individualized circumstances is used to prioritize patients. Proton-photon backup planning strategy and physics check details were described. This article provides an overview of workflow of conversion of PBT to photon when the PBT machine is down. Specific needs of patients undergoing proton beam therapy are addressed.

PURPOSE The multiple energy extraction (MEE) delivery technique for synchrotron-based proton delivery systems reduces beam delivery time by decelerating the beam multiple times during one accelerator spill, but this might cause additional plan quality degradation due to intrafractional motion. We seek to determine whether MEE causes significantly different plan quality degradation compared to single energy extraction (SEE) for lung cancer treatments due to the interplay effect. METHODS Ten lung cancer patients treated with IMPT at our institution were nonrandomly sampled based on a representative range of tumor motion amplitudes, tumor volumes, and respiratory periods. Dose-volume histogram (DVH) indices from single-fraction SEE and MEE four-dimensional (4D) dynamic dose distributions were compared using the Wilcoxon signed-rank test. Distributions of monitor units (MU) to breathing phases were investigated for features associated with plan quality degradation. SEE and MEE DVH indices were compared in fractionated deliveries of the worst-case patient treatment scenario to evaluate the impact of fractionation. RESULTS There were no clinically significant differences in target mean dose, target dose conformity, or dose to organs-at-risk between SEE and MEE in single-fraction delivery. Three patients had significantly worse dose homogeneity with MEE compared to SEE (single-fraction mean D5% -D95% increased by up to 9.6% of prescription dose), and plots of MU distribution to breathing phases showed synchronization patterns with MEE but not SEE. However, after 30 fractions the patient in the worst-case scenario had clinically acceptable target dose homogeneity and coverage with MEE (mean D5% -D95% increased by 1% compared to SEE). CONCLUSIONS For some patients with breathing periods close to the mean spill duration, MEE resulted in significantly worse single-fraction target dose homogeneity compared to SEE due to the interplay effect. However, this was mitigated by fractionation, and target dose homogeneity and coverage were clinically acceptable after 30 fractions with MEE.

PURPOSE/OBJECTIVE(S) To determine if heart radiation dose and location affects overall survival (OS) in patients treated with Stereotactic Body Radiation Therapy (SBRT) to the lung. MATERIALS/METHODS Patients treated with SBRT to the lung at a single institution were identified. Pertinent information regarding patient characteristics, treatment delivered, and patient outcomes were obtained from a prospectively maintained cancer registry and the medical record. Radiation treatment information was obtained from the treatment planning system. Radiation dose in each voxel was extracted from the treatment planning system, mapped on anatomical organs, and converted to 2 Gy equivalent dose using linear quadratic model. The V% dosimetric variable, a percentage of volume receiving the dose 'D' or greater, was used in the statistical analysis. Multivariate Cox regression analysis with Akaike Information Criterion (AIC) was used to determine which patient specific variables were predictive for OS. All predictive variables were further used in the Cox model with an addition of dosimetric variables for the heart. We examined V%_D variables for the whole heart, heart digitally subdivided into four segments (right-superior, left-superior, right-inferior, left-inferior), and heart digitally subdivided into 64 segments. RESULTS 197 patients treated for lung lesions with SBRT were selected for this study. 135 patients were treated for primary lung cancer (117 stage I, 18 stage II) and 42 patients were treated for lung metastasis from other primary sites. There were 79 patients with lung adenocarcinoma, 38 with lung squamous cell carcinoma (SCC), and 62 patients with other histologies. Dose prescriptions were 50 Gy in 5 fractions (35%) and 48 Gy in 4 fractions (65%). The reference patient was 72.2 years old, with stage I, primary lung adenocarcinoma. Mean OS was 76.8 months and mean follow up was 40 months (2 - 230). Patient age (HR = 1.08/year, P < 0.01), histology (HR = 2.8 for SCC, P < 0.01) and stage (HR = 3.5 for stage II primary lung cancer, P < 0.01) were predictive for OS. Patients with right lung disease had longer OS than patients with left lung disease (HR = 0.6, P = 0.03). Whole heart DVH analysis did not reveal statistically significant predictors for OS. A DVH analysis of the heart divided into four segments suggested that low doses in the inferior segments of the heart decreased OS (V%_2 Gy, HR = 1.007/1%, P = 0.02). Maximum dose in the right-inferior portion of the heart was also predictive for OS (HR = 1.02/Gy, P = 0.02). A more detailed analysis of 3D dose distributions in the heart, using a digital subdivision of the heart into 64 segments, confirmed that low doses to the inferior part of the heart decreased OS (P = 0.01). CONCLUSION Low doses to the inferior portion of the heart may be associated with reduced OS in patients treated with SBRT to the lung. Age, histology and stage were associated with OS.

Radiation therapy (RT) is a commonly used approach for treating lung cancer. Because the lungs are close to the heart, radiation dose may inevitably spill to the heart, causing heart damage and diminishing treatment outcomes. There is an urgent need to better understand how treatment outcomes are affected by radiation dose spilled to the heart in order to optimize RT planning. However, despite the fact that dose distribution on the heart is 3-D, most existing research collapses the 3-D dose map into a 1-D histogram to be linked with outcomes. This ignores the spatial information. We propose a novel method that automatically searches for subregions of the heart that are susceptible to radiation toxicity, called Toxicity-Susceptible Subregions (TSSs), based on the 3-D dose distribution. We apply the proposed method to a real-world dataset and find TSSs that harbor the sinoatrial node of the electronic conduction system of the heart. Damage of the sinoatrial node by radiation toxicity disrupts the crucial function of the heart, leading to shortening of the overall survival. Our finding suggests that protective strategies may be developed to spare the TSSs, and thus helping RT planning achieve optimal results in treating lung cancer patients.

Radiation Therapy (RT) is one of the most common treatments for cancer. To understand the impact of radiation toxicity on normal tissue, a Normal Tissue Complication Probability (NTCP) model is nee...

Patient- and provider-reported outcomes are recognized as important in evaluating quality of care, guiding health care policy, comparative effectiveness research, and decision-making in radiation oncology. Combining patient and provider outcome data with a detailed description of disease and therapy is the basis for these analyses. We report on the combination of technical solutions and clinical process changes at our institution that were used in the collection and dissemination of this data. This initiative has resulted in the collection of treatment data for 23 541 patients, 20 465 patients with provider-based adverse event records, and patient-reported outcome surveys submitted by 5622 patients. All of the data is made accessible using a self-service web-based tool.

Purpose/Objective(s) High linear energy transfer (LET) radiotherapy may cause unexpected adverse events (AEs) in head and neck (H&N) cancer patients treated by intensity-modulated proton therapy (IMPT). In this exploratory study, we propose to investigate the effects of LET upon AEs in IMPT using dose-linear-energy-transfer volume histograms (DLVHs) and seed spots analysis. Materials/Methods We included 14 H&N patients with unanticipated CTCAEv4.0 grade≥3 AEs for analysis. The AE regions were contoured and the corresponding DLVHs of the AE regions were generated. DLVH was constructed with physical dose (Gy) and LET (keV/µm) as independent variables. The normalized volume of the structure was contoured as iso-volume lines in the dose-LET plane. All voxels in the structure were mapped into the dose-LET plane as dots to see how the dots with similar dose and LET were clustered. For seed spot analysis, we selected voxels at the top edge of the DLVH plots as critical voxels. Individually clustered critical voxels that are geometrically apart were considered as independent seed spots. Median dose/LET from seed spots were extracted. Bivariate-linear-regression models were established for all AEs. The dose and LET product (xBD) volume constraint of osteoradionecrosis was obtained using the receiver operating characteristic curve of 4 osteoradionecrosis patients and 15 additional independent control patients. Results Dose played a dominant role for in-field AEs such as hemorrhage and ulceration, while LET played an important role in out-of-field AEs such as osteoradionecrosis and mucositis. Intercept-free linear models between the reciprocal of dose and LET were found for different AEs. The corresponding xBD threshold values were included in Table 1. The xBD volume constraint of osteoradionecrosis was derived V (xBD≥275.18 Gy•keV/μm) Conclusion Our observations suggested that dose and LET can contribute to AEs in a complicated fashion. Using the intercept-free bivariate linear regression model, we found a LET-enhancing effect for all 6 AEs included in the study, substantiated by the positive slopes of the empirical dose-LET models. The xBD volume constraint of osteoradionecrosis was derived and showed good performance. We believe that both DLVH and seed spot analysis could be powerful tools for patient outcome studies in IMPT.

Purpose Custom-fabricated lead shields are often used for superficial radiation treatments to reduce radiation doses to adjacent healthy tissue. However, the process for fabricating these lead shields is time consuming, labor intensive, and uncomfortable for patients. Alternatively, patient-specific shields can be 3-dimensionally (3D) printed from a high-density bronze-based filament to address these concerns. This study was performed to assess the shielding characteristics of 3D-printed bronze (3DPB) shields, demonstrate their clinical viability, and report the first ever published case of a patient treated with a 3DPB shield. Methods and Materials The transmission of 6 and 9 MeV electron beams through varying thicknesses of 3DPB was first measured. Percent depth doses and beam profiles were measured with flat 3DPB shields and equivalent lead shields to determine surface dose enhancement, output factors, and field widths. Two 3DPB shields were designed and fabricated for an anthropomorphic phantom, and phantom measurements were performed using optically stimulated luminescence dosimeters and film. Finally, 3DPB shields were used during the treatment of 7 patients' skin lesions. Results Ten and 15 mm of 3DPB were sufficient to shield 6 and 9 MeV electrons, respectively, by 95%. The 3DPB and lead shields had nearly identical beam widths (within 1%). Output factors were on average within 0.8% for bronze shields and 1.2% for lead shields relative to an unshielded field. The skin enhancement for bronze was higher than for lead by an average of 6.3%. Phantom measurements using 3DPB shields generally showed less than 3% transmission of the primary beam under the 3DPB shield. The patients' shields fit as designed and were all deemed clinically acceptable by their physicians. Conclusions The 3DPB shields fit better than lead shields, are easier to design and manufacture, and have similar dosimetric properties. 3DPB shields are a viable clinical option for patient-specific superficial shielding.

Purpose Intensity Modulated Radiation Therapy (IMRT) allows for significant dose reductions to organs at risk in prostate cancer patients. However, the accurate delivery of IMRT plans can be compromised by patient positioning errors. The purpose of this study was to determine if the modeling of grade ≥ 2 acute rectal toxicity could be used to monitor the quality of IMRT protocols. Materials and methods 79 patients treated with Image and Fiducial Markers Guided IMRT (FMIGRT) and 302 patients treated with trans-abdominal ultrasound guided IMRT (USGRT) was selected for this study. Treatment plans were available for the FMIGRT group, and hand recorded dosimetric indices were available for both groups. We modeled toxicity in the FMIGRT group using the Lyman Kutcher Burman (LKB) and Univariate Logistic Regression (ULR) models, and we modeled toxicity in USGRT group using the ULR model. We performed Receiver Operating Characteristics (ROC) analysis on all of the models and compared the Area under the ROC curve (AUC) for the FMIGRT and the USGRT groups. Results The observed Incidence of grade ≥ 2 rectal toxicity was 20% in FMIGRT patients and 54% in USGRT patients. LKB model parameters in the FMIGRT group were TD50=56.8 Gy, slope m=0.093, and exponent n=0.131. The most predictive indices in the ULR model for the FMIGRT group were D25% and V50 Gy. AUC for both models in the FMIGRT group was similar (AUC=0.67). The FMIGRT URL model predicted less than a 37% incidence of grade ≥ 2 acute rectal toxicity in the USGRT group. A fit of the ULR model to USGRT data did not yield a predictive model (AUC=0.5). Conclusion Modeling of acute rectal toxicity provided a quantitative measure of the correlation between planning dosimetry and this clinical endpoint. Our study suggests that an unusually weak correlation may indicate a persistent patient positioning error.

Purpose The purpose of this study is to evaluate the impact of two methods of reporting planned dose distributions on the Gamma analysis pass rates for comparison with measured 2D film dose and simulated delivered 3D dose for proton pencil beam scanning treatment of the Imaging and Radiation Oncology Core (IROC) proton lung and liver mobile phantoms. Methods and materials Four-dimensional (4D) computed-tomography (CT) image sets were acquired for IROC proton lung and liver mobile phantoms, which include dosimetry inserts that contains targets, thermoluminescent dosimeters and EBT2 films for plan dose verification. 4DCT measured fixed motion magnitudes were 1.3 and 1.0 cm for the lung and liver phantoms, respectively. To study the effects of motion magnitude on the Gamma analysis pass rate, three motion magnitudes for each phantom were simulated by creating virtual 4DCT image sets with motion magnitudes scaled from the scanned phantom motion by 50, 100, and 200%. The internal target volumes were contoured on the maximum intensity projection CTs of the 4DCTs for the lung phantom and on the minimum intensity projection CTs of the 4DCTs for the liver phantom. Treatment plans were optimized on the average intensity projection (AVE) CTs of the 4DCTs using the RayStation treatment planning system. Plan doses were calculated on the AVE CTs, which was defined as the planned AVE dose (method one). Plan doses were also calculated on all 10 phase CTs of the 4DCTs and were registered using target alignment to and equal-weight-summed on the 50% phase (T50) CT, which was defined as the planned 4D dose (method two). The planned AVE doses and 4D doses for phantom treatment were reported to IROC, and the 2D-2D Gamma analysis pass rates for measured film dose relative to the planned AVE and 4D doses were compared. To evaluate motion interplay effects, simulated delivered doses were calculated for each plan by sorting spots into corresponding respiratory phases using spot delivery time recorded in the log files by the beam delivery system to calculate each phase dose and accumulate dose to the T50 CTs. Ten random beam starting phases were used for each beam to obtain the range of the simulated delivered dose distributions. 3D-3D Gamma analyses were performed to compare the planned 4D/AVE doses with simulated delivered doses. Results The planned 4D dose matched better with the measured 2D film dose and simulated delivered 3D dose than the planned AVE dose. Using planned 4D dose as institution reported planned dose to IROC improved IROC film dose 2D-2D Gamma analysis pass rate from 92 to 96% on average for three films for the lung phantom (7% 5 mm), and from 92 to 94% in the sagittal plane for the liver phantom (7% 4 mm), respectively, compared with using the planned AVE dose. The 3D-3D Gamma analysis (3% 3 mm) pass rate showed that the simulated delivered doses for lung and liver phantoms using 10 random beam starting phases for each delivered beam matched the planned 4D dose significantly better than the planned AVE dose for phantom motions larger than 1 cm (p ≤ 0.04). Conclusions It is recommended to use the planned 4D dose as the institution reported planned dose to IROC to compare with the measured film dose for proton mobile phantoms to improve film Gamma analysis pass rate in the IROC credentialing process.

Introduction Establishment of standards within a practice and across disease site groups for nomenclatures, prescription formatting, and measured dose-volume histogram (DVH) metrics is a key enabling step for creating software and database solutions to make routine aggregation of dosimetric data for all patients treated in a practice, practical. A process of physician-driven, iterative dialogs coupled with development of technical tools is required to implement the cultural and procedural changes. The cumulative reward for this effort is a database that can be used for defining practice norms, benchmarking against national standards, and tracking dosimetric effects of longitudinal practice pattern changes. Methods and materials A 4-year project was carried out to develop and introduce standardizations, modify processes, and develop computer-based tools for reporting, aggregation, and analysis of prescription and DVH metrics. Physician disease site groups developed 42 target and 81 normal tissue templates. From the database of 32,002 DVH metrics, benchmarking was illustrated for a subgroup of breast (281) and prostate (324) patients treated with conventional fractionation over a 16-month period. Breast patients were segregated according to prescription template used: simple (S, tangents only) vs complex (C, tangents + supraclavicular ± intramammary nodes) and left (S-L or C-L) versus right (S-R or C-R). Results Prostate patients' median and 50% confidence intervals (CIs) for bladder, stated according to the nomenclature: the percentage of bladder volume receiving doses of ≥40 Gy (V40[%]), V65Gy[%], V70Gy[%], V75Gy[%], and V80Gy[%] were 45.5 (24.9-57.0), 15.6 (9.0-23.8), 7.6 (3.3-13.6), 2.0 (0.0-7.9), and 0.0 (0.0-1.4), respectively. Values for rectum: V50Gy[%], V60 Gy[%], V65Gy[%], V70Gy[%], and V75Gy[%] were 37.1 (27.8-43.5), 21.8 (15.6-25.5), 14.6 (9.6-18.0), 7.7 (1.9-12.3), and 1.0 (0–7.0), respectively. For breast patients, heart:mean Gray values were 1.5 (1.0-2.0), 3.1 (2.2-4.8), 0.4 (0.3-0.7), and 1.1 (0.8-2.2) for S-L, C-L, S-R, and C-R, respectively. Longitudinal, moving window plots of median, 50% CI, and 90% CI for 6-month periods demonstrated the effect of practice changes to reduce heart doses. Conclusions Standardization was challenging as a practice change, but has resulted in significant improvements for both our clinical and research efforts.

Purpose At our institution, all proton patient plans undergo patient-specific quality assurance (PSQA) prior to treatment delivery. For intensity-modulated proton beam therapy, quality assurance is complex and time consuming, and it may involve multiple measurements per field. We reviewed our PSQA workflow and identified the steps that could be automated and developed solutions to improve efficiency. Methods We used the treatment planning system's (TPS) capability to support C# scripts to develop an Eclipse scripting application programming interface (ESAPI) script and automate the preparation of the verification phantom plan for measurements. A local area network (LAN) connection between our measurement equipment and shared database was established to facilitate equipment control, measurement data transfer, and storage. To improve the analysis of the measurement data, a Python script was developed to automatically perform a 2D-3D γ-index analysis comparing measurements in the plane of a two-dimensional detector array with TPS predictions in a water phantom for each acquired measurement. Results Device connection via LAN granted immediate access to the plan and measurement information for downstream analysis using an online software suite. Automated scripts applied to verification plans reduced time from preparation steps by at least 50%; time reduction from automating γ-index analysis was even more pronounced, dropping by a factor of 10. On average, we observed an overall time savings of 55% in completion of the PSQA per patient plan. Conclusions The automation of the routine tasks in the PSQA workflow significantly reduced the time required per patient, reduced user fatigue, and frees up system users from routine and repetitive workflow steps allowing increased focus on evaluating key quality metrics.

Purpose: To quantitatively investigate the effect of range shifter materials on single-spot characteristics of a proton pencil beam. Methods: An analytic approximation for multiple Coulomb scattering (“differential Moliere” formula) was adopted to calculate spot sizes of proton spot scanning beams impinging on a range shifter. The calculations cover a range of delivery parameters: six range shifter materials (acrylonitrile butadiene styrene, Lexan, Lucite, polyethylene, polystyrene, and wax) and water as reference material, proton beam energies ranging from 75 to 200 MeV, range shifter thicknesses of 4.5 and 7.0 g/cm2, and range shifter positions from 5 to 50 cm. The analytic method was validated by comparing calculation results with the measurements reported in the literature. Results: Relative to a water-equivalent reference, the spot size distal to a wax or polyethylene range shifter is 15% smaller, while the spot size distal to a range shifter made of Lexan or Lucite is about 6% smaller. The relative spot size variations are nearly independent of beam energy and range shifter thickness and decrease with smaller air gaps. Conclusions: Among the six material investigated, wax and polyethylene are desirable range shifter materials when the spot size is kept small. Lexan and Lucite are the desirable range shifter materials when the scattering power is kept similar to water.

Purpose: To evaluate two deformable image registration (DIR) algorithms for the purpose of contour mapping to support image guided adaptive radiotherapy (IGART) with 4D cone beam CT (4DCBCT). Methods: Eleven locally advanced non‐small cell lungcancer(NSCLC) patients underwent one planning 4D fan‐ beam CT (4DFBCT) and seven weekly 4DCBCT scans. Gross tumor volume (GTV) and carina were delineated by a physician in all 4D images. For day to day registration, the end of inspiration 4DFBCT phase was deformably registered to the corresponding phase in each 4DCBCT image. For phase to phase registration, the end of inspiration phase from each 4D image was registered to end of expiration phase. The delineated contours were warped using the resulting transforms and compared to the manual contours through Dice similarity coefficient (DSC), false positive and false negative indices, and, for carina, target registration error (TRE). Two DIR algorithms were tested: 1) small deformation, inverse consistent linear elastic (SICLE) algorithm and 2) Insight Toolkit diffeomorphic demons (DEMONS). Results: For day to day registrations, the mean DSC was 0.59 ± 0.16 after rigid registration, 0.72 ± 0.13 with SICLE and to 0.66 ± 0.18 with DEMONS. SICLE and DEMONS reduced TRE to 4.1 ± 2.1 mm and 5.8 ± 3.7 mm respectively, from 6.2 ± 3.5 mm; and reduced false positive index to 0.27 and 0.26 respectively from 0.46. Registration with the cone beam as the fixed image resulted in higher DSC than with the fan beam as fixed (p < 0.001). SICLE and DEMONS increased the DSC on average by 10.0% and 8.0% and reduced TRE by 2.8 mm and 2.9 mm respectively for phase to phase DIR. Conclusions: DIR achieved more congruent mapping of target structures to delineations than rigid registration alone, although DIR performance varied with algorithm and patient. This work was supported by National Cancer Institute Grant No. P01 CA 116602.

Background: A possible association between the level of prostate specific antigen (PSA) and the use of some commonly prescribed medications has been reported in recent studies. Most of these studies were carried out in general populations of men who were screened for prostate cancer using the PSA test. We reported on the association between the initial PSA level and the use of statins, metformin and alpha-blockers in patients who were diagnosed with prostate cancer and presented for radiation therapy. Methods: Three hundred and eighty one patients treated between the years of 2000-2005 and 2009-2012 were included in this retrospective study. The information about statin, metformin and alpha-blockers use was recorded immediately prior to treatment. Differences in PSA levels prior to treatment by medication status were estimated using univariate and multivariate linear regression on log PSA values. Results: Compared with men who were not on these medications, the PSA level at presentation was 20% lower for statin users (p = 0.002) and 33% lower for metformin users (p = 0.004). We did not observe statistically significant associations between the use of statins or metformin and cancer stage, National Comprehensive Cancer Network (NCCN) risk score, or therapy outcome. A statistically significant association between the NCCN risk score and the use of alpha-blockers was observed (p = 0.002). Conclusions: We found that statins and metformin were associated with lower PSA levels in prostate cancer patients to an extent that could influence management decisions. We found no statistically significant associations between the use of these medications and treatment outcomes.

Purpose To test the feasibility of a planned phase 1 study of image-guided adaptive radiation therapy in locally advanced lung cancer. Methods and Materials Weekly 4-dimensional fan beam computed tomographs (4D FBCT) of 10 lung cancer patients undergoing concurrent chemoradiation therapy were used to simulate adaptive radiation therapy: After an initial intensity modulated radiation therapy plan (0-30 Gy/2 Gy), adaptive replanning was performed on week 2 (30-50 Gy/2 Gy) and week 4 scans (50-66 Gy/2 Gy) to adjust for volume and shape changes of primary tumors and lymph nodes. Week 2 and 4 clinical target volumes (CTV) were deformably warped from the initial planning scan to adjust for anatomical changes. On the week 4 scan, a simultaneous integrated volume-adapted boost was created to the shrunken primary tumor with dose increases in 5 0.4-Gy steps from 66 Gy to 82 Gy in 2 scenarios: plan A, lung isotoxicity; plan B, normal tissue tolerance. Cumulative dose was assessed by deformably mapping and accumulating biologically equivalent dose normalized to 2 Gy-fractions (EQD2). Results The 82-Gy level was achieved in 1 in 10 patients in scenario A, resulting in a 13.4-Gy EQD2 increase and a 22.1% increase in tumor control probability (TCP) compared to the 66-Gy plan. In scenario B, 2 patients reached the 82-Gy level with a 13.9 Gy EQD2 and 23.4% TCP increase. Conclusions The tested image-guided adaptive radiation therapy strategy enabled relevant increases in EQD2 and TCP. Normal tissue was often dose limiting, indicating a need to modify the present study design before clinical implementation.

Purpose To evaluate 2 deformable image registration (DIR) algorithms for the purpose of contour mapping to support image-guided adaptive radiation therapy with 4-dimensional cone-beam CT (4DCBCT). Methods and Materials One planning 4D fan-beam CT (4DFBCT) and 7 weekly 4DCBCT scans were acquired for 10 locally advanced non-small cell lung cancer patients. The gross tumor volume was delineated by a physician in all 4D images. End-of-inspiration phase planning 4DFBCT was registered to the corresponding phase in weekly 4DCBCT images for day-to-day registrations. For phase-to-phase registration, the end-of-inspiration phase from each 4D image was registered to the end-of-expiration phase. Two DIR algorithms—small deformation inverse consistent linear elastic (SICLE) and Insight Toolkit diffeomorphic demons (DEMONS)—were evaluated. Physician-delineated contours were compared with the warped contours by using the Dice similarity coefficient (DSC), average symmetric distance, and false-positive and false-negative indices. The DIR results are compared with rigid registration of tumor. Results For day-to-day registrations, the mean DSC was 0.75 ± 0.09 with SICLE, 0.70 ± 0.12 with DEMONS, 0.66 ± 0.12 with rigid-tumor registration, and 0.60 ± 0.14 with rigid-bone registration. Results were comparable to intraobserver variability calculated from phase-to-phase registrations as well as measured interobserver variation for 1 patient. SICLE and DEMONS, when compared with rigid-bone (4.1 mm) and rigid-tumor (3.6 mm) registration, respectively reduced the average symmetric distance to 2.6 and 3.3 mm. On average, SICLE and DEMONS increased the DSC to 0.80 and 0.79, respectively, compared with rigid-tumor (0.78) registrations for 4DCBCT phase-to-phase registrations. Conclusions Deformable image registration achieved comparable accuracy to reported interobserver delineation variability and higher accuracy than rigid-tumor registration. Deformable image registration performance varied with the algorithm and the patient.

Aim: To model acute rectal toxicity in Intensity Modulated Radiation Therapy (IMRT) for prostate cancer using dosimetry and patient specific characteristics. Methods: A database of 79 prostate cancer patients treated with image guided IMRT was used to fit parameters of Lyman-Kutcher-Burman (LKB) and logistic regression Normal Tissue Complications Probability (NTCP) models to acute grade ≥ 2 rectal toxicities. We used a univariate regression model to find the dosimetric index which was most correlated with toxicity and a multivariate logistic regression model with machine learning algorithm to integrate dosimetry with patient specific characteristics. We used Receiver Operating Characteristics (ROC) analysis and the area under the ROC curve (AUC) to quantify the predictive power of models. Results: Sixteen patients (20.3%) developed acute grade≥2 rectal toxicity. Our best estimate (95% confidence interval) of LKB model parameters for acute rectal toxicity are exponent n=0.13 (0.1-0.16), slope m=0.09 (0.08–0.11), and threshold dose TD50=56.8 (53.7-59.9) Gy. The best dosimetric indices in the univariate logistic regression NTCP model were D25% and V50Gy. The best AUC of dosimetry only modeling was 0.67 (0.54, 0.8). In the multivariate logistic regression two patient specific variables were particularly strongly correlated with acute rectal toxicity, the use of statin drugs and PSA level prior to IMRT, while two additional variables, age and diabetes were weakly correlated. The AUC of the logistic regression NTCP model improved to 0.88 (0.8, 0.96) when patient specific characteristics were included. In a group of 79 patients, 40 took Statins and 39 did not. Among patients who took statins, (4/40)=10% developed acute grade ≥2 rectal toxicity, compared to (12/39)=30.8% who did not take statins (p=0.03). The average and standard deviation of PSA distribution for patients with acute rectal toxicity was 5.77 2.27 tox PSA = ± and it was 9.5 7.8 notox PSA = ± for the remainder (p=0.01). Conclusions: Patient specific characteristics strongly influence the likelihood of acute grade ≥ 2 rectal toxicity in radiation therapy for prostate cancer.

Research computing in radiation therapy is transitioning from small-scale computing to large software systems. Accelerator-mounted imaging devices collect multiple images at every treatment fraction, creating datasets of hundreds of images per patient. Compounding this challenge is the fact that software infrastructure upgrades are difficult to manage in academic environments, due to inadequate experience in large-scale software development.

Purpose: To evaluate incidental doses to benign lung tissue for patients with minimally moving lung lesions treated with respiratory gating. Methods and Materials: Seventeen lung patient plans were studied retrospectively. Tumor motion was less than 5 mm in all cases. For each patient, mid-ventilation (MidVen) and mid-inhalation (MidInh) breathing phases were reconstructed. The MidInh phase was centered on the end-of-inhale (EOI) phase within a 30% gating window. Planning target volumes, heart, and spinal cord were delineated on the MidVen phase and transferred to the MidInh phase. Lungs were contoured separately on each phase. Intensity-modulated radiotherapy plans were generated on the MidVen phases. The plans were transferred to the MidInh phase, and doses were recomputed. The evaluation metric was based on dose indices, volume indices, generalized equivalent uniform doses, and mass indices for targets and critical structures. Statistical tests were used to establish the significance of the differences between the reference (MidVen) and compared (MidInh) dose distributions. Results: Statistical tests demonstrated that the indices evaluated for targets, cord, and heart differed by within 2.3%. The index differences in the lungs, however, are in excess of 6%, indicating the potentially achievable lung sparing and/or dose escalation. Conclusions: Respiratory gating isaclinical optionfor patientswith minimally moving lunglesions treated at EOI. Gating will be more beneficial for larger tumors, since dose escalation in those cases will result in a larger increase in the tumor control probability. 2010 Elsevier Inc. Gating, 4D, Dose, IMRT, Lung, Motion management.

A course of one to three large fractions of high dose rate (HDR) interstitial brachytherapy is an attractive alternative to intensity modulated radiation therapy (IMRT) for delivering boost doses to the prostate in combination with additional external beam irradiation for intermediate risk disease. The purpose of this work is to quantitatively compare single-fraction HDR boosts to biologically equivalent fractionated IMRT boosts, assuming idealized image guided delivery (igIMRT) and conventional delivery (cIMRT). For nine prostate patients, both seven-field IMRT and HDR boosts were planned. The linear-quadratic model was used to compute biologically equivalent dose prescriptions. The cIMRT plan was evaluated as a static plan and with simulated random and setup errors. The authors conclude that HDR delivery produces a therapeutic ratio which is significantly better than the conventional IMRT and comparable to or better than the igIMRT delivery. For the HDR, the rectal gBEUD analysis is strongly influenced by high dose DVH tails. A saturation BED, beyond which no further injury can occur, must be assumed. Modeling of organ motion uncertainties yields mean outcomes similar to static plan outcomes.

Purpose To develop a deliverable four-dimensional (4D) intensity-modulated radiation therapy (IMRT) planning method for dynamic multileaf collimator (MLC) tumor tracking delivery. Methods and Materials The deliverable 4D IMRT planning method involves aligning MLC leaf motion parallel to the major axis of target motion and translating MLC leaf positions by the difference in the target centroid position between respiratory phases of the 4D CT scan. This method ignores nonlinear respiratory motion and deformation. A three-dimensional (3D) optimal method whereby an IMRT plan on each respiratory phase of the 4D CT scan was independently optimized was used for comparison. For 12 lung cancer patient 4D CT scans, individual phase plans and deformable dose-summed 4D plans using the two methods were created and compared. Results For each of the individual phase plans, the deliverable method yielded similar isodose distributions and dose–volume histograms. The deliverable and 3D optimal methods yielded statistically equivalent dose–volume metrics for both individual phase plans and 4D plans ( p > 0.05 for all metrics compared). The deliverable method was affected by 4D CT artifacts in one case. Both methods were affected by high vector field variations from deformable registration. Conclusions The deliverable method yielded similar dose distributions for each of the individual phase plans and statistically equivalent dosimetric values compared with the 3D optimal method, indicating that the deliverable method is dosimetrically robust to the variations of fractional time spent in respiratory phases on a given 4D CT scan. Nonlinear target motion and deformation did not cause significant dose discrepancies.

Received 20 August 2007; revised 10 December 2007; accepted for publication 2 January 2008;published 27 February 2008Purpose: To measure the sensitivity of deformable image registration to image noise. Deformableimage registration can be used to map organ contours and other treatment planning data from oneCT to another. These CT studies can be acquired with either conventional fan-beam CT systems ormore novel cone-beam CT techniques. However, cone-beam CT images can have higher noiselevels than fan-beam CT, which might reduce registration accuracy. We have investigated the effectof image quality differences on the deformable registration of fan-beam CTs and CTs with simu-lated cone-beam noise. Method: Our study used three CT studies for each of five prostate patients.Each CT was contoured by three experienced radiation oncologists. For each patient, one CT wasdesignated the source image and the other two were target images.Adeformable image registrationprocess was used to register each source CT to each target CT and then transfer the manually drawntreatment planning contours from the source CT to the target CTs. The accuracy of the automati-cally transferred contours and thus of the deformable registration process was assessed by com-paring them to the manual contours on the target CTs, with the differences evaluated with respectto interobserver variability in the manual contours. Then each of the target CTs was modified toinclude increased noise characteristic of cone-beam CT and the tests were repeated. Changes inregistration accuracy due to increased noise were detected by monitoring changes in the automati-cally transferred contours. Results: We found that the additional noise caused no significant loss ofregistration accuracy at magnitudes that exceeded what would normally be found in an actualcone-beam CT. Summary: We conclude that noise levels in cone-beam CTs that might reducemanual contouring accuracy do not reduce image registration and automatic contouringaccuracy. ©

This study quantifies the dose prediction errors (DPEs) in dynamic IMRT dose calculations resulting from (a) use of an intensity matrix to estimate the multi-leaf collimator (MLC) modulated photon fluence (DPE(IGfluence) instead of an explicit MLC particle transport, and (b) handling of tissue heterogeneities (DPE(hetero)) by superposition/convolution (SC) and pencil beam (PB) dose calculation algorithms. Monte Carlo (MC) computed doses are used as reference standards. Eighteen head-and-neck dynamic MLC IMRT treatment plans are investigated. DPEs are evaluated via comparing the dose received by 98% of the GTV (GTV D 98%), the CTV D 95%, the nodal D 90%, the cord and the brainstem D 02%, the parotid D 50%, the parotid mean dose (D (Mean)), and generalized equivalent uniform doses (gEUDs) for the above structures. For the MC-generated intensity grids, DPE(IGfluence) is within +/- 2.1% for all targets and critical structures. The SC algorithm DPE(hetero) is within +/- 3% for 98.3% of the indices tallied, and within +/- 3.4% for all of the tallied indices. The PB algorithm DPE(hetero) is within +/- 3% for 92% of the tallied indices. Statistical equivalence tests indicate that PB DPE(hetero) requires a +/- 3.6% interval to state equivalence with the MC standard, while the intervals are < 1.5% for SC DPE(hetero) and DPE(IGfluence). Overall, these results indicate that SC and MC IMRT dose calculations which use MC-derived intensity matrices for fluence prediction do not introduce significant dose errors compared with full Monte Carlo dose computations; however, PB algorithms may result in clinically significant dose deviations.

Background: Commonly used methods of assessing the accuracy of deformable image registration (DIR) rely on image segmentation or landmark selection. These methods are very labor intensive and thus limited to relatively small number of image pairs. The direct voxel-by-voxel comparison can be automated to examine fluctuations in DIR quality on a long series of image pairs. Methods: A voxel-by-voxel comparison of three DIR algorithms applied to lung patients is presented. Registrations are compared by comparing volume histograms formed both with individual DIR maps and with a voxel-by-voxel subtraction of the two maps. When two DIR maps agree one concludes that both maps are interchangeable in treatment planning applications, though one cannot conclude that either one agrees with the ground truth. If two DIR maps significantly disagree one concludes that at least one of the maps deviates from the ground truth. We use the method to compare 3 DIR algorithms applied to peak inhale-peak exhale registrations of 4DFBCT data obtained from 13 patients. Results: All three algorithms appear to be nearly equivalent when compared using DICE similarity coefficients. A comparison based on Jacobian volume histograms shows that all three algorithms measure changes in total volume of the lungs with reasonable accuracy, but show large differences in the variance of Jacobian distribution on contoured structures. Analysis of voxel-by-voxel subtraction of DIR maps shows differences between algorithms that exceed a centimeter for some registrations. Conclusion: Deformation maps produced by DIR algorithms must be treated as mathematical approximations of physical tissue deformation that are not self-consistent and may thus be useful only in applications for which they have been specifically validated. The three algorithms tested in this work perform fairly robustly for the task of contour propagation, but produce potentially unreliable results for the task of DVH accumulation or measurement of local volume change. Performance of DIR algorithms varies significantly from one image pair to the next hence validation efforts, which are exhaustive but performed on a small number of image pairs may not reflect the performance of the same algorithm in practical clinical situations. Such efforts should be supplemented by validation based on a longer series of images of clinical quality.

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy(IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan ( SC opt ) , B: an SC opt plan recalculated with Monte Carlo [ MC ( SC opt ) ] , and C: an MC optimized plan ( MC opt ) . For each structure, DPEs and OCEs were estimated as DPE SC = D B − D A and OCE SC = D C − D B where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE SC in the GTV D 98 varied from − 1.9 % to − 4.9 % , while the OCE SC ranged from 0.9% to 7.0%. The DPE SC in the contralateral parotid D 50 reached 8.2%, while the OCE SC in the contralateral parotid D 50 varied from 0.91% to 6.99%. The DPE SC in cord D 2 reached − 3.0 % , while the OCE SC reached to − 7.0 % . The magnitude of the DPE SC and OCE SC differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRToptimization process, especially for the estimation of normal structure doses.

Purpose We compared conventionally optimized intensity modulated proton therapy (IMPT) treatment plans against worst-case scenario optimized treatment plans for lung cancer. The comparison of the 2 IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient setup, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods and materials For each of the 9 lung cancer cases, 2 treatment plans were created that accounted for treatment uncertainties in 2 different ways. The first used the conventional method: delivery of prescribed dose to the planning target volume that is geometrically expanded from the internal target volume (ITV). The second used a worst-case scenario optimization scheme that addressed setup and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of changes in patient anatomy attributable to respiratory motion were investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the 2 groups were compared with 2-sided paired Student t tests. Results Without respiratory motion considered, we affirmed that worst-case scenario optimization is superior to planning target volume–based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, worst-case scenario optimization still achieved more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality (D 95% ITV, 96.6% vs 96.1% [ P = .26]; D 5% − D 95% ITV, 10.0% vs 12.3% [ P = .082]; D 1% spinal cord, 31.8% vs 36.5% [ P = .035]). Conclusions Worst-case scenario optimization led to superior solutions for lung IMPT. Despite the fact that worst-case scenario optimization did not explicitly account for respiratory motion, it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.

Purpose: Models of rectal toxicity which include dosimetry only are known to have a relatively low predictive power, at least as measured by the area under the ROC curve (AUC). It has been suggested that the predictive power of models can be improved by including non-dosimetric patient specific characteristics. Methods: We compiled a database of 79 prostate patients who were treated with an IMRT technique to a dose of 77.4 Gy, 1.8Gy/fx, with an integrated boost to 81–83Gy in a sub-volume of a prostate which was identified on a pre-treatment MRI study. Acute grade 2+ rectal toxicities were graded according to CTCAE v4 by a physician who retrospectively reviewed patient’s medical records. We modified the LKB model to include one patient specific variable at a time, and we also used an NTCP model based on logistic regression to perform multi-variate analysis. We used patient specific variables available to us in a retrospective study: age, diabetes, hormonal treatment, Gleason Score, PSA, Statin use, prostate volume, boost volume and rectal volume. Results: Grade 2+ acute rectal toxicity occurred in 20% (16/79 patients). The LKB model with dosimetry alone gives AUC=0.65. Four variables, age, diabetes, PSA, Statin use, increase the AUC in LKB model to a maximum of 0.79. The same four variables in the logistic regression model increase AUC to 0.87. The most significant correlations are with PSA and with Statin use. Conclusion: Including patient specific variables in toxicity models can significantly increase apparent predictive power of a model. Somewhat surprising finding of a strong correlation between rectal toxicity and PSA in our dataset suggests that conclusions from each individual study should be treated with caution, until independently confirmed. Larger databases from prospective studies or meta-analysis of multiple studies may be needed to find patient characteristics that are truly predictive.

Particle detection instrumentation to address the in vivo verifications of proton dose and range is under development as part of a proton therapy research program focused on patient quality assurance. For in vivo proton range verification, a collimated gamma detector array is under construction to indirectly measure the position of the Bragg peak for each proton beam spot to within 1–2 mm precision. For dose flux verification, a proton fluence detector based on the technology of the Micromegas is under construction. This detector has an active area of about 100 cm2, coordinate resolution of better than 1 mm, and handling of incident proton beam fluxes of 109–1013 particles/s.

Purpose To investigate the potential benefits achievable with biological optimization for modulated volumetric arc (VMAT) treatments of prostate carcinoma. Methods and Materials Fifteen prostate patient plans were studied retrospectively. For each case, planning target volume, rectum, and bladder were considered. Three optimization schemes were used: dose–volume histogram (DVH) based, generalized equivalent uniform dose (gEUD) based, and mixed DVH/gEUD based. For each scheme, a single or dual 6-MV, 356° VMAT arc was used. The plans were optimized with Pinnacle 3 (v. 9.0 beta) treatment planning system. For each patient, the optimized dose distributions were normalized to deliver the same prescription dose. The quality of the plans was evaluated by dose indices (DIs) and gEUDs for rectum and bladder. The tallied DIs were D 1% , D 15% , D 25% , and D 40% , and the tallied gEUDs were for a values of 1 and 6. Statistical tests were used to quantify the magnitude and the significance of the observed differences. Monitor units and treatment times for each optimization scheme were also assessed. Results All optimization schemes generated clinically acceptable plans. The statistical tests indicated that biological optimization yielded increased organs-at-risk sparing, ranging from ∼1% to more than ∼27% depending on the tallied DI, gEUD, and anatomical structure. The increased sparing was at the expense of longer treatment times and increased number of monitor units. Conclusions Biological optimization can significantly increase the organs-at-risk sparing in VMAT optimization for prostate carcinoma. In some particular cases, however, the DVH-based optimization resulted in superior treatment plans.

To measure the sensitivity of deformable image registration to image noise. Deformable image registration can be used to map organ contours and other treatment planning data from one CT to another. These CT studies can be acquired with either conventional fan-beam CT systems or more novel cone-beam CT techniques. However, cone-beam CT images can have higher noise levels than fan-beam CT, which might reduce registration accuracy. We have investigated the effect of image quality differences on the deformable registration of fan-beam CTs and CTs with simulated cone-beam noise.Our study used three CT studies for each of five prostate patients. Each CT was contoured by three experienced radiation oncologists. For each patient, one CT was designated the source image and the other two were target images. A deformable image registration process was used to register each source CT to each target CT and then transfer the manually drawn treatment planning contours from the source CT to the target CTs. The accuracy of the automatically transferred contours (and thus of the deformable registration process) was assessed by comparing them to the manual contours on the target CTs, with the differences evaluated with respect to interobserver variability in the manual contours. Then each of the target CTs was modified to include increased noise characteristic of cone-beam CT and the tests were repeated. Changes in registration accuracy due to increased noise were detected by monitoring changes in the automatically transferred contours.We found that the additional noise caused no significant loss of registration accuracy at magnitudes that exceeded what would normally be found in an actual cone-beam CT.We conclude that noise levels in cone-beam CTs that might reduce manual contouring accuracy do not reduce image registration and automatic contouring accuracy.