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Background: Investigations on radiation‐induced lung injury (RILI) have predominantly focused on local effects, primarily those associated with radiation damage to lung parenchyma. However, recent studies from our group and others have revealed that radiation‐induced damage to branching serial structures such as airways and vessels may also have a substantial impact on post‐radiotherapy (RT) lung function. Furthermore, recent results from multiple functional lung avoidance RT trials, although promising, have demonstrated only modest toxicity reduction, likely because they were primarily focused on dose avoidance to lung parenchyma. These observations emphasize the critical need for predictive dose‐response models that effectively incorporate both local and distant RILI effects. Purpose: We develop and validate a predictive model for ventilation loss after lung RT. This model, referred to as P+A, integrates local (parenchyma [P]) and distant (central and peripheral airways [A]) radiation‐induced damage, modeling partial (narrowing) and complete (collapse) obstruction of airways. Methods: In an IRB‐approved prospective study, pre‐RT breath‐hold CTs (BHCTs) and pre‐ and one‐year post‐RT 4DCTs were acquired from lung cancer patients treated with definitive RT. Up to 13 generations of airways were automatically segmented on the BHCTs using a research virtual bronchoscopy software. Ventilation maps derived from the 4DCT scans were utilized to quantify pre‐ and post‐RT ventilation, serving, respectively, as input data and reference standard (RS) in model validation. To predict ventilation loss solely due to parenchymal damage (referred to as P model), we used a normal tissue complication probability (NTCP) model. Our model used this NTCP‐based estimate and predicted additional loss due radiation‐induced partial or complete occlusion of individual airways, applying fluid dynamics principles and a refined version of our previously developed airway radiosensitivity model. Predictions of post‐RT ventilation were estimated in the sublobar volumes (SLVs) connected to the terminal airways. To validate the model, we conducted a k‐fold cross‐validation. Model parameters were optimized as the values that provided the lowest root mean square error (RMSE) between predicted post‐RT ventilation and the RS for all SLVs in the training data. The performance of the P+A and the P models was evaluated by comparing their respective post‐RT ventilation values with the RS predictions. Additional evaluation using various receiver operating characteristic (ROC) metrics was also performed. Results: We extracted a dataset of 560 SLVs from four enrolled patients. Our results demonstrated that the P+A model consistently outperformed the P model, exhibiting RMSEs that were nearly half as low across all patients (13 ± 3 percentile for the P+A model vs. 24 ± 3 percentile for the P model on average). Notably, the P+A model aligned closely with the RS in ventilation loss distributions per lobe, particularly in regions exposed to doses ≥13.5 Gy. The ROC analysis further supported the superior performance of the P+A model compared to the P model in sensitivity (0.98 vs. 0.07), accuracy (0.87 vs. 0.25), and balanced predictions. Conclusions: These early findings indicate that airway damage is a crucial factor in RILI that should be included in dose‐response modeling to enhance predictions of post‐RT lung function. [ABSTRACT FROM AUTHOR]

Purpose: Current radiation therapy (RT) treatment planning relies mainly on pre‐defined dose‐based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population‐based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient‐specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity‐modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient‐specific dose response models into the planning process. In this strategy, we integrate the concept of utility‐based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non‐small cell lung cancer (NSCLC) patients. Methods and materials: We developed a prioritized approach to patient‐specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet‐dose contributions to regions‐of‐interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade‐off based on individualized dose‐response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose‐based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3–5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors. Results: The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility‐based plans resulted in similar local control estimates with decreased estimated toxicity. Conclusion: The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility‐based objective function offers an intuitive, humanized approach to biological optimization in which planning trade‐offs are explicitly optimized. [ABSTRACT FROM AUTHOR]

Purpose: Medical physics residents (MPRs) will define and shape the future of physics in medicine. We sought to better understand the residency experience, as related to resilience and well‐being, through the lens of current MPRs and medical physicists (MPs) working with residents. Methods and materials: From February–May 2019, we conducted 32, 1‐h, confidential, semi‐structured interviews with MPs either currently enrolled in an accredited residency (n = 16) or currently employed by a department with an accredited residency (n = 16). Interviews centered on the topics of mentorship, work/life integration, and discrimination. Qualitative analysis methods were used to derive key themes from the interview transcripts. Results: With regard to the medical physics residency experience, four key themes emerged during qualitative analysis: the demanding nature of medical physics residencies, the negative impacts of residency on MPRs during training and beyond, strategies MPRs use to cope with residency stress, and the role of professional societies in addressing residency‐related change. Conclusions: Residency training is a stress‐inducing time in the path to becoming a board‐certified MP. By uncovering several sources of this stress, we have identified opportunities to support the resiliency and well‐being of MPs in training through recommendations by professional societies, programmatic changes, and interventions at the department and residency program director level for residency programs, as well as strategies that MPRs themselves can use to support well‐being on their career journey. [ABSTRACT FROM AUTHOR]

Purpose: Electron‐based ultra‐high dose rate radiation therapy (UHDR‐RT), also known as Flash‐RT, has shown the ability to improve the therapeutic index in comparison to conventional radiotherapy (CONV‐RT) through increased sparing of normal tissue. However, the extremely high dose rates in UHDR‐RT have raised the need for accurate real‐time dosimetry tools. This work aims to demonstrate the potential of the emerging technology of Ionized Radiation Acoustic Imaging (iRAI) through simulation studies and investigate its characteristics as a promising relative in vivo dosimetric tool for UHDR‐RT. Methods: The detection of induced acoustic waves following a single UHDR pulse of a modified 6 MeV 21EX Varian Clinac in a uniform porcine gelatin phantom that is brain‐tissue equivalent was simulated for an ideal ultrasound transducer. The full 3D dose distributions in the phantom for a 1 × 1 cm2 field were simulated using EGSnrc (BEAMnrc∖DOSXYZnrc) Monte Carlo (MC) codes. The relative dosimetry simulations were verified with dose experimental measurements using Gafchromic films. The spatial dose distribution was converted into an initial pressure source spatial distribution using the medium‐dependent dose–pressure relation. The MATLAB‐based toolbox k‐Wave was then used to model the propagation of acoustic waves through the phantom and perform time‐reversal (TR)‐based imaging reconstruction. The effect of the various linear accelerator (linac) operating parameters, including linac pulse duration and pulse repetition rate (frequency), were investigated as well. Results: The MC dose simulation results agreed with the film measurement results, specifically at the central beam region up to 80% dose within approximately 5% relative error for the central profile region and a local relative error of <6% for percentage dose depth. IRAI‐based FWHM of the radiation beam was within approximately 3 mm relative to the MC‐simulated beam FWHM at the beam entrance. The real‐time pressure signal change agreed with the dose changes proving the capability of the iRAI for predicting the beam position. IRAI was tested through 3D simulations of its response to be based on the temporal changes in the linac operating parameters on a dose per pulse basis as expected theoretically from the pressure‐dose proportionality. The pressure signal amplitude obtained through 2D simulations was proportional to the dose per pulse. The instantaneous pressure signal amplitude decreases as the linac pulse duration increases, as predicted from the pressure wave generation equations, such that the shorter the linac pulse the higher the signal and the better the temporal (spatial) resolutions of iRAI. The effect of the longer linac pulse duration on the spatial resolution of the 3D constructed iRAI images was corrected for linac pulse deconvolution. This correction has improved the passing rate of the 1%/1 mm gamma test criteria, between the pressure‐constructed and dosimetric beam characteristics, to as high as 98%. Conclusions: A full simulation workflow was developed for testing the effectiveness of iRAI as a promising relative dosimetry tool for UHDR‐RT radiation therapy. IRAI has shown the advantage of 3D dose mapping through the dose signal linearity and, hence, has the potential to be a useful dosimeter at depth dose measurement and beam localization and, hence, potentially for in vivo dosimetry in UHDR‐RT. [ABSTRACT FROM AUTHOR]

Purpose: To develop and implement an efficient and accurate commissioning procedure for small‐field static beam animal irradiation studies on an MV research linear accelerator (Linatron‐M9) using radiochromic gel dosimetry. Materials: The research linear accelerator (Linatron‐M9) is a 9 MV linac with a static fixed collimator opening of 5.08 cm diameter. Lead collimators were manually placed to create smaller fields of 2 × 2 cm2, 1 × 1 cm2, and 0.5 × 0.5 cm2. Relative dosimetry measurements were performed, including profiles, percent depth dose (PDD) curves, beam divergence, and relative output factors using various dosimetry tools, including a small volume ionization chamber (A14), GAFCHROMIC™ EBT3 film, and Clearview gel dosimeters. The gel dosimeter was used to provide a 3D volumetric reference of the irradiated fields. The Linatron profiles and relative output factors were extracted at a reference depth of 2 cm with the output factor measured relative to the 2 × 2 cm2 reference field. Absolute dosimetry was performed using A14 ionization chamber measurements, which were verified using a national standards laboratory remote dosimetry service. Results: Absolute dosimetry measurements were confirmed within 1.4% (k = 2, 95% confidence = 5%). The relative output factor of the small fields measured with films and gels agreed with a maximum relative percent error difference between the two methods of 1.1 % for the 1 × 1 cm2 field and 4.3 % for the 0.5 × 0.5 cm2 field. These relative errors were primarily due to the variability in the collimator positioning. The measured beam profiles demonstrated excellent agreement for beam size (measured as FWHM), within approximately 0.8 mm (or less). Film measurements were more accurate in the penumbra region due to the film's finer resolution compared with the gel dosimeter. Following the van Dyk criteria, the PDD values of the film and gel measurements agree within 11% in the buildup region starting from 0.5 cm depth and within 2.6 % beyond maximum dose and into the fall‐off region for depths up to 5 cm. The 2D beam profile isodose lines agree within 0.5 mm in all regions for the 0.5 × 0.5 cm2 and the 1 × 1 cm2 fields and within 1 mm for the larger field of 2 × 2 cm2. The 2D PDD curves agree within approximately 2% of the maximum in the typical therapy region (1–4 cm) for the 1 × 1 cm2 and 2 × 2 cm2 and within 5% for the 0.5 × 0.5 cm2 field. Conclusion: This work provides a commissioning process to measure the beam characteristics of a fixed beam MV accelerator with detailed dosimetric evaluation for its implementation in megavoltage small animal irradiation studies. Radiochromic gel dosimeters are efficient small‐field relative dosimetry tools providing 3D dose measurements allowing for full representation of dose, dosimeter misalignment corrections and high reproducibility with low inter‐dosimeter variability. Overall, radiochromic gels are valuable for fast, full relative dosimetry commissioning in comparison to films for application in high‐energy small‐field animal irradiation studies. [ABSTRACT FROM AUTHOR]

Purpose: Most existing computed tomography (CT)‐ventilation imaging techniques are based on deformable image registration (DIR) of different respiratory phases of a four‐dimensonal CT (4DCT) scan of the lung, followed by the quantification of local breathing‐induced changes in Hounsfield Units (HU) or volume. To date, only moderate correlations have been reported between these CT‐ventilation metrics and standard ventilation imaging modalities for adaptive lung radiation therapy. This study evaluates the use of stress maps derived from biomechanical model‐based DIR as an alternative CT‐ventilation metric. Materials and methods: Six patients treated for lung cancer with conventional radiation therapy were retrospectively analyzed. For each patient, a 4DCT scan and Tc‐99m SPECT‐V image acquired for treatment planning were collected. Biomechanical model‐based DIR was applied between the inhale and exhale phase of the 4DCT scans and stress maps were calculated. The voxel‐wise correlation between the reference SPECT‐V image and map of the maximum principal stress was measured with a Spearman correlation coefficient. The overlap between high (above the 75th percentile) and low (below the 25th percentile) functioning volumes extracted from the reference SPECT‐V and the stress maps was measured with Dice similarity coefficients (DSC). The results were compared to those obtained when using two classical CT‐ventilation metrics: the change in HU and Jacobian determinant. Results: The mean Spearman correlation coefficients were: 0.37 ± 18 and 0.39 ± 13 and 0.59 ± 0.13 considering the changes in HU, Jacobian and maximum principal stress, respectively. The corresponding mean DSC coefficients were 0.38 ± 0.09, 0.37 ± 0.07 and 0.52 ± 0.07 for the high ventilation function volumes and 0.48 ± 0.13, 0.44 ± 0.09 and 0.52 ± 0.07 for the low ventilation function volumes. Conclusion: For presenting a significantly stronger and more consistent correlation with standard SPECT‐V images than previously proposed CT‐ventilation metrics, stress maps derived with the proposed method appear to be a promising tool for incorporation into functional lung avoidance strategies. [ABSTRACT FROM AUTHOR]

Purpose: Modern inverse radiotherapy treatment planning requires nonconvex, large‐scale optimizations that must be solved within a clinically feasible timeframe. We have developed and tested a quantum‐inspired, stochastic algorithm for intensity‐modulated radiotherapy (IMRT): quantum tunnel annealing (QTA). By modeling the likelihood probability of accepting a higher energy solution after a particle tunneling through a potential energy barrier, QTA features an additional degree of freedom (the barrier width, w) not shared by traditional stochastic optimization methods such as Simulated Annealing (SA). This additional degree of freedom can improve convergence rates and achieve a more efficient and, potentially, effective treatment planning process. Methods: To analyze the character of the proposed QTA algorithm, we chose two stereotactic body radiation therapy (SBRT) liver cases of variable complexity. The "easy" first case was used to confirm functionality, while the second case, with a more challenging geometry, was used to characterize and evaluate the QTA algorithm performance. Plan quality was assessed using dose‐volume histogram‐based objectives and dose distributions. Due to the stochastic nature of the solution search space, extensive tests were also conducted to determine the optimal smoothing technique, ensuring balance between plan deliverability and the resulting plan quality. QTA convergence rates were investigated in relation to the chosen barrier width function, and QTA and SA performances were compared regarding sensitivity to the choice of solution initializations, annealing schedules, and complexity of the dose‐volume constraints. Finally, we investigated the extension from beamlet intensity optimization to direct aperture optimization (DAO). Influence matrices were calculated using the Eclipse scripting application program interface (API), and the optimizations were run on the University of Michigan's high‐performance computing cluster, Flux. Results: Our results indicate that QTA's barrier‐width function can be tuned to achieve faster convergence rates. The QTA algorithm reached convergence up to 46.6% faster than SA for beamlet intensity optimization and up to 26.8% faster for DAO. QTA and SA were ultimately found to be equally insensitive to the initialization process, but the convergence rate of QTA was found to be more sensitive to the complexity of the dose‐volume constraints. The optimal smoothing technique was found to be a combination of a Laplace‐of‐Gaussian (LOG) edge‐finding filter implemented as a penalty within the objective function and a two‐dimensional Savitzky–Golay filter applied to the final iteration; this achieved total monitor units more than 20% smaller than plans optimized by commercial treatment planning software. Conclusions: We have characterized the performance of a stochastic, quantum‐inspired optimization algorithm, QTA, for radiotherapy treatment planning. This proof of concept study suggests that QTA can be tuned to achieve faster convergence than SA; therefore, QTA may be a good candidate for future knowledge‐based or adaptive radiation therapy applications. [ABSTRACT FROM AUTHOR]

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision‐making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data. [ABSTRACT FROM AUTHOR]

Purpose: Individualization of therapeutic outcomes in NSCLC radiotherapy is likely to be compromised by the lack of proper balance of biophysical factors affecting both tumor local control (LC) and side effects such as radiation pneumonitis (RP), which are likely to be intertwined. Here, we compare the performance of separate and joint outcomes predictions for response‐adapted personalized treatment planning. Methods: A total of 118 NSCLC patients treated on prospective protocols with 32 cases of local progression and 20 cases of RP grade 2 or higher (RP2) were studied. Sixty‐eight patients with 297 features before and during radiotherapy were used for discovery and 50 patients were reserved for independent testing. A multiobjective Bayesian network (MO‐BN) approach was developed to identify important features for joint LC/RP2 prediction using extended Markov blankets as inputs to develop a BN predictive structure. Cross‐validation (CV) was used to guide the MO‐BN structure learning. Area under the free‐response receiver operating characteristic (AU‐FROC) curve was used to evaluate joint prediction performance. Results: Important features including single nucleotide polymorphisms (SNPs), micro RNAs, pretreatment cytokines, pretreatment PET radiomics together with lung and tumor gEUDs were selected and their biophysical inter‐relationships with radiation outcomes (LC and RP2) were identified in a pretreatment MO‐BN. The joint LC/RP2 prediction yielded an AU‐FROC of 0.80 (95% CI: 0.70–0.86) upon internal CV. This improved to 0.85 (0.75–0.91) with additional two SNPs, changes in one cytokine and two radiomics PET image features through the course of radiotherapy in a during‐treatment MO‐BN. This MO‐BN model outperformed combined single‐objective Bayesian networks (SO‐BNs) during‐treatment [0.78 (0.67–0.84)]. AU‐FROC values in the evaluation of the MO‐BN and individual SO‐BNs on the testing dataset were 0.77 and 0.68 for pretreatment, and 0.79 and 0.71 for during‐treatment, respectively. Conclusions: MO‐BNs can reveal possible biophysical cross‐talks between competing radiotherapy clinical endpoints. The prediction is improved by providing additional during‐treatment information. The developed MO‐BNs can be an important component of decision support systems for personalized response‐adapted radiotherapy. [ABSTRACT FROM AUTHOR]

Purpose Advanced radiotherapy delivery systems designed for high-dose, high-precision treatments often come equipped with high-definition multi-leaf collimators ( HD- MLC) aimed at more finely shaping radiation dose to the target. In this work, we study the effect of a high definition MLC on spine stereotactic body radiation therapy ( SBRT) treatment plan quality and plan deliverability. Methods and Materials Seventeen spine SBRT cases were planned with VMAT using a standard definition MLC (M120), HD- MLC, and HD- MLC with an added objective to reduce monitor units ( MU). M120 plans were converted into plans deliverable on an HD- MLC using in-house software. Plan quality and plan deliverability as measured by portal dosimetry were compared among the three types of plans. Results Only minor differences were noted in plan quality between the M120 and HD- MLC plans. Plans generated with the HD- MLC tended to have better spinal cord sparing (3% reduction in maximum cord dose). HD- MLC plans on average had 12% more MU and 55% greater modulation complexity as defined by an in-house metric. HD- MLC plans also had significantly degraded deliverability. Of the VMAT arcs measured, 94% had lower gamma passing metrics when using the HD- MLC. Conclusion Modest improvements in plan quality were noted when switching from M120 to HD- MLC at the expense of significantly less accurate deliverability in some cases. [ABSTRACT FROM AUTHOR]

Purpose: Apertures obtained during volumetric modulated arc therapy (VMAT) planning can be small and irregular, resulting in dosimetric inaccuracies during delivery. Our purpose is to develop and integrate an aperture-regularization objective function into the optimization process for VMAT, and to quantify the impact of using this objective function on dose delivery accuracy and optimized dose distributions. Methods: An aperture-based metric ('edge penalty') was developed that penalizes complex aperture shapes based on the ratio of MLC side edge length and aperture area. To assess the utility of the metric, VMAT plans were created for example paraspinal, brain, and liver SBRT cases with and without incorporating the edge penalty in the cost function. To investigate the dose calculation accuracy, Gafchromic EBT2 film was used to measure the 15 highest weighted apertures individually and as a composite from each of two paraspinal plans: one with and one without the edge penalty applied. Films were analyzed using a triple-channel nonuniformity correction and measurements were compared directly to calculations. Results: Apertures generated with the edge penalty were larger, more regularly shaped and required up to 30% fewer monitor units than those created without the edge penalty. Dose volume histogram analysis showed that the changes in doses to targets, organs at risk, and normal tissues were negligible. Edge penalty apertures that were measured with film for the paraspinal plan showed a notable decrease in the number of pixels disagreeing with calculation by more than 10%. For a 5% dose passing criterion, the number of pixels passing in the composite dose distributions for the non-edge penalty and edge penalty plans were 52% and 96%, respectively. Employing gamma with 3% dose/1 mm distance criteria resulted in a 79.5% (without penalty)/95.4% (with penalty) pass rate for the two plans. Gradient compensation of 3%/1 mm resulted in 83.3%/96.2% pass rates. Conclusions: The use of the edge penalty during optimization has the potential to markedly improve dose delivery accuracy for VMAT plans while still maintaining high quality optimized dose distributions. The penalty regularizes aperture shape and improves delivery efficiency. [ABSTRACT FROM AUTHOR]

Purpose: Inverse planned intensity modulated radiation therapy (IMRT) has helped many centers implement highly conformal treatment planning with beamlet-based techniques. The many comparisons between IMRT and 3D conformal (3DCRT) plans, however, have been limited because most 3DCRT plans are forward-planned while IMRT plans utilize inverse planning, meaning both optimization and delivery techniques are different. This work avoids that problem by comparing 3D plans generated with a unique inverse planning method for 3DCRT called inverse-optimized 3D (IO-3D) conformal planning. Since IO-3D and the beamlet IMRT to which it is compared use the same optimization techniques, cost functions, and plan evaluation tools, direct comparisons between IMRT and simple, optimized IO-3D plans are possible. Though IO-3D has some similarity to direct aperture optimization (DAO), since it directly optimizes the apertures used, IO-3D is specifically designed for 3DCRT fields (i.e., 1-2 apertures per beam) rather than starting with IMRT-like modulation and then optimizing aperture shapes. The two algorithms are very different in design, implementation, and use. The goals of this work include using IO-3D to evaluate how close simple but optimized IO-3D plans come to nonconstrained beamlet IMRT, showing that optimization, rather than modulation, may be the most important aspect of IMRT (for some sites). Methods: The IO-3D dose calculation and optimization functionality is integrated in the in-house 3D planning/optimization system. New features include random point dose calculation distributions, costlet and cost function capabilities, fast dose volume histogram (DVH) and plan evaluation tools, optimization search strategies designed for IO-3D, and an improved, reimplemented edge/octree calculation algorithm. The IO-3D optimization, in distinction to DAO, is designed to optimize 3D conformal plans (one to two segments per beam) and optimizes MLC segment shapes and weights with various user-controllable search strategies which optimize plans without beamlet or pencil beam approximations. IO-3D allows comparisons of beamlet, multisegment, and conformal plans optimized using the same cost functions, dose points, and plan evaluation metrics, so quantitative comparisons are straightforward. Here, comparisons of IO-3D and beamlet IMRT techniques are presented for breast, brain, liver, and lung plans. Results: IO-3D achieves high quality results comparable to beamlet IMRT, for many situations. Though the IO-3D plans have many fewer degrees of freedom for the optimization, this work finds that IO-3D plans with only one to two segments per beam are dosimetrically equivalent (or nearly so) to the beamlet IMRT plans, for several sites. IO-3D also reduces plan complexity significantly. Here, monitor units per fraction (MU/Fx) for IO-3D plans were 22%-68% less than that for the 1 cm × 1 cm beamlet IMRT plans and 72%-84% than the 0.5 cm × 0.5 cm beamlet IMRT plans. Conclusions: The unique IO-3D algorithm illustrates that inverse planning can achieve high quality 3D conformal plans equivalent (or nearly so) to unconstrained beamlet IMRT plans, for many sites. IO-3D thus provides the potential to optimize flat or few-segment 3DCRT plans, creating less complex optimized plans which are efficient and simple to deliver. The less complex IO-3D plans have operational advantages for scenarios including adaptive replanning, cases with interfraction and intrafraction motion, and pediatric patients. [ABSTRACT FROM AUTHOR]

Inverse-planned intensity modulated radiation therapy (IMRT) is often able to achieve complex treatment planning goals that are unattainable with forward three-dimensional (3D) conformal planning. However, the common use of IMRT has introduced several new challenges. The potentially high degree of modulation in IMRT beams risks the loss of some advantages of 3D planning, such as excellent target coverage and high delivery efficiency. Previous attempts to reduce beam complexity by smoothing often result in plan degradation because the smoothing algorithm cannot distinguish between areas of desirable and undesirable modulation. The purpose of this work is to introduce and evaluate adaptive diffusion smoothing (ADS), a novel procedure designed to preferentially reduce IMRT beam complexity. In this method, a discrete diffusion equation is used to smooth IMRT beams using diffusion coefficients, automatically defined for each beamlet, that dictate the degree of smoothing allowed for each beamlet. This yields a method that can distinguish between areas of desirable and undesirable modulation. The ADS method has been incorporated into our optimization system as a weighted cost function penalty, with two diffusion coefficient definitions designed to promote: (1) uniform smoothing everywhere or (2) smoothing based on cost function gradients with respect to the plan beamlet intensities. The ADS method (with both coefficient types) has been tested in a phantom and in two clinical examples (prostate and head/neck). Both types of diffusion coefficients produce plans with reduced modulation and minimal dosimetric impact, but the cost function gradient-based coefficients show more potential for reducing beam modulation without affecting dosimetric plan quality. In summary, adaptive diffusion smoothing is a promising tool for ensuring that only the necessary amount of beam modulation is used, promoting more efficient and accurate IMRT planning, QA, and delivery. [ABSTRACT FROM AUTHOR]

Inverse planned intensity modulated radiation therapy (IMRT) has become commonplace in treatment centers across the world. Due to the implications of beam complexity on treatment planning, delivery, and quality assurance, several methods have been proposed to reduce the complexity. These methods include beamlet intensity restrictions, smoothing procedures, and direct aperture optimization. Many of these methods typically sacrifice target coverage and/or normal tissue sparing in return for increased beam smoothness and delivery efficiency. In the present work, we penalize beam modulation in the inverse planning cost function to reduce beam complexity and increase delivery efficiency, while maintaining dosimetric quality. Three modulation penalties were tested: two that penalized deviation from Savitzky-Golay filtered versions of the optimized beams, and one that penalized the plan intensity map variation (a measure of overall beam modulation). The modulation penalties were applied at varying weights in a weighted sum objective (or cost) function to investigate their ability to reduce beam complexity while preserving IMRT plan quality. The behavior of the penalties was characterized on a CT phantom, and then clinical optimization comparisons were performed in the brain, prostate, and head/neck. Comparisons were made between (i) plans with a baseline cost function (ii) plans with a baseline cost function employing maximum beamlet intensity limits, and (iii) plans with each of the modulation penalties added to the baseline cost function. Plan analysis was based upon dose-volume histograms, relevant dose metrics, beam modulation, and monitor units required for step and shoot delivery. Each of the techniques yielded improvements over a baseline cost function in terms of MU reduction. In most cases, this was achieved with minimal change to the plan DVHs and metrics. In all cases, an acceptable plan was reached with each of the methods while reducing MU substantially. Each individual method has merit as a tool for reducing IMRT beam complexity and could be easily applied in the clinic to improve overall inverse plan quality. However, the penalty based upon the plan intensity map variation consistently produced the most delivery-efficient plans with the fewest computations. [ABSTRACT FROM AUTHOR]

Purpose: This study aims at developing and testing a novel rigidity penalty suitable for the deformable registration of tightly located skeletal components in the head and neck from planning computed tomography (CT) and daily cone-beam CT (CBCT) scans of patients undergoing radiotherapy. Methods: The proposed rigidity penalty is designed to preserve intervoxel distances within each bony structure. This penalty was tested in the intensity-based B-spline deformable registration of five cervical vertebral bodies (C1-C5). The displacement vector fields (DVFs) from the registrations were compared to the DVFs generated by using rigid body motions of the cervical vertebrae, measured by the surface registration of vertebrae delineated on CT and CBCT images. Twenty five pairs of planning CT (reference) and treatment CBCTs (target) from five patients were aligned without and with the penalty. An existing penalty based on the orthonormality of the deformation gradient tensor was also tested and the effects of the penalties compared. Results: The mean magnitude of the maximum registration error with the proposed distance-preserving penalty was (0.86, 1.12, 1.33) mm compared to (2.11, 2.49, 2.46) without penalty and (1.53, 1.64, 1.64) with the existing orthonormality-based penalty. The improvement in the accuracy of the deformable image registration was also verified by comparing the Procrustes distance between the DVFs. With the proposed penalty, the average distance was 0.11 (σ 0.03 mm) which is smaller than 0.53 (0.1 mm) without penalty and 0.28 (0.04 mm) with the orthonormality-based penalty. Conclusions: The accuracy of aligning multiple bony elements was improved by using the proposed distance-preserving rigidity penalty. The voxel-based statistical analysis of the registration error shows that the proposed penalty improved the integrity of the DVFs within the vertebral bodies. [ABSTRACT FROM AUTHOR]

Purpose: To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT. Methods: A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT/hybrid beams. Results: The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%-43.7% fewer MU/Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost-32.9%-55.2% compared to single-arc VMAT-the decrease in MU/Gy compared to IMRT was noticeably smaller at 12.2%-18.5%, when compared to IMRT. Conclusions: A hybrid VMAT/IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom. This optimization method will allow patients to be simultaneously planned for dosimetric quality and delivery efficiency without switching between delivery techniques. Example phantom and clinical cases suggest that the conversion of only three VMAT segments to modulated beams may result in a good combination of quality and efficiency. [ABSTRACT FROM AUTHOR]

Purpose: Plan degradation resulting from compromises made to enhance delivery efficiency is an important consideration for intensity modulated radiation therapy (IMRT) treatment plans. IMRT optimization and/or multileaf collimator (MLC) sequencing schemes can be modified to generate more efficient treatment delivery, but the effect those modifications have on plan quality is often difficult to quantify. In this work, the authors present a method for quantitative assessment of overall plan quality degradation due to tradeoffs between delivery efficiency and treatment plan quality, illustrated using comparisons between plans developed allowing different numbers of intensity levels in IMRT optimization and/or MLC sequencing for static segmental MLC IMRT plans. Methods: A plan quality degradation method to evaluate delivery efficiency and plan quality tradeoffs was developed and used to assess planning for 14 prostate and 12 head and neck patients treated with static IMRT. Plan quality was evaluated using a physician's predetermined 'quality degradation' factors for relevant clinical plan metrics associated with the plan optimization strategy. Delivery efficiency and plan quality were assessed for a range of optimization and sequencing limitations. The 'optimal' (baseline) plan for each case was derived using a clinical cost function with an unlimited number of intensity levels. These plans were sequenced with a clinical MLC leaf sequencer which uses >100 segments, assuring delivered intensities to be within 1% of the optimized intensity pattern. Each patient's optimal plan was also sequenced limiting the number of intensity levels (20, 10, and 5), and then separately optimized with these same numbers of intensity levels. Delivery time was measured for all plans, and direct evaluation of the tradeoffs between delivery time and plan degradation was performed. Results: When considering tradeoffs, the optimal number of intensity levels depends on the treatment site and on the stage in the process at which the levels are limited. The cost of improved delivery efficiency, in terms of plan quality degradation, increased as the number of intensity levels in the sequencer or optimizer decreased. The degradation was more substantial for the head and neck cases relative to the prostate cases, particularly when fewer than 20 intensity levels were used. Plan quality degradation was less severe when the number of intensity levels was limited in the optimizer rather than the sequencer. Conclusions: Analysis of plan quality degradation allows for a quantitative assessment of the compromises in clinical plan quality as delivery efficiency is improved, in order to determine the optimal delivery settings. The technique is based on physician-determined quality degradation factors and can be extended to other clinical situations where investigation of various tradeoffs is warranted. [ABSTRACT FROM AUTHOR]