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Purpose: To develop an angular correction methodology and characterize a high-resolution complementary metal-oxide-semiconductor (CMOS) array for patient specific quality assurance on a robotic arm linear accelerator., Methods: Beam path files from the treatment planning software (TPS) were used to calculate the angle of radiation beam with respect to the detector plane. Beams from multiple discrete angles were delivered to the CMOS detector array and an angular dependency look up table (LUT) was created. The LUT was then used to correct for the angular dependency of the detector. An iso-centric 5 mm fixed cone, non iso-centric multi-target fixed cone, 10 mm Iris and a multi-leaf collimator (MLC) based collimated plan were delivered to the phantom and compared to the TPS with and without angular correction applied. Additionally, the CMOS array was compared to gafchromic film and a diode array., Results: Large errors of up to 30% were observed for oblique angles. When angular correction was applied, the gamma passing rate increased from 99.2% to 100% (average gamma value decreased from 0.29 to 0.14) for the 5-mm iso-centric cone plan. Similarly, the passing rate increased from 84.0% to 100% for the Iris plan and from 49.98% to 98.4% for the MLC plan when angular correction was applied. For the multi-target plan, applying angular correction improved the gamma passing rate from 94% to 99.6%. The 5 mm iso-centric fixed cone plan was also delivered to film, and the gamma passing rate was 91.3% when using gafchromic film as the reference dataset, whereas the diode array provided insufficient sampling for this plan., Conclusion: A methodology of calculating the beam angle based on the beam path files was developed and validated. The array was demonstrated to be superior to other quality assurance tools because of its sub-millimeter spatial resolution and immediate read out of the results., (© 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

Purpose: Many radiotherapy modalities can deliver concentrated radiation in the form of spots, such as Gamma Knife (GK), GammaPod (GP), intensity-modulated proton therapy, and brachytherapy, and can be generalized as spot-based treatments. These treatments have a great therapeutic advantage of creating potent target dose while sparing the surrounding normal tissues. However, global optimization to determine the spot positions, shapes, and intensities is an intractable combinatorial problem for any real 3D problem. The conventional approach adopts heuristic spot selection and intensity optimization in a sequential manner to mitigate the problem complexity. In this work, we propose a novel framework that enables global optimization of spot-based treatment planning., Methods: The framework is based on kernel decomposition (KD) dose calculation, which models each spot dose as a scaled shift-invariant kernel, with the reference kernels and scales pre-calculated. During optimization, the framework incorporates Fast Fourier Transform (FFT) for objective and derivative evaluations and accommodates all spot candidates in optimization search with a temporal complexity of O(N 3 log N) as opposed to O(N 6 ) complexity in the conventional beamlet framework for volume dimensions of N × N × N. We demonstrated the FFT framework using simulations with different objectives. The framework's planning performance was illustrated using clinical GK and GP cases., Results: Pre-processing involves only a small number of reference kernels and a scale map for the KD model with marginal spatial and temporal overheads. For simulations with 512 × 512 image dimensions, plan optimization finished in ∼2 seconds with FFT, whereas it took 100× longer with the beamlet approach. For clinical cases, the FFT attained solutions within a minute with improved plan quality compared to clinical plans: better conformity and less integral dose because of using a global fine search space for optimal spots., Conclusions: The scaled shift-invariance and FFT framework opens a new paradigm for spot-based treatment planning, as it can substantially reduce both the spatial and temporal complexities. The framework makes global optimization for spot-based treatment planning clinically feasible., (© 2022 American Association of Physicists in Medicine.)

Total body irradiation is an important part of the conditioning regimens frequently used to prepare patients for allogeneic hematopoietic stem cell transplantation (SCT). Volumetric-modulated arc therapy enabled total body irradiation (VMAT-TBI), an alternative to conventional TBI (cTBI), is a novel radiotherapy treatment technique that has been implemented and investigated in our institution. The purpose of this study is to (1) report our six-year clinical experience in terms of treatment planning strategy and delivery time and (2) evaluate the clinical outcomes and toxicities in our cohort of patients treated with VMAT-TBI. This is a retrospective single center study. Forty-four patients at our institution received VMAT-TBI and chemotherapy conditioning followed by allogeneic SCT between 2014 and 2020. Thirty-two patients (73%) received standard-dose TBI (12-13.2 Gy in 6-8 fractions twice daily), whereas 12 (27%) received low-dose TBI (2-4 Gy in one fraction). Treatment planning, delivery, and treatment outcome data including overall survival (OS), relapse-free survival (RFS), and toxicities were analyzed. The developed VMAT-TBI planning strategy consistently generated plans satisfying our dose constraints, with planning target volume coverage >90%, mean lung dose ∼50% to 75% of prescription dose, and minimal hotspots in critical organs. Most of the treatment deliveries were <100 minutes (range 33-147, mean 72). The median follow-up was 26 months. At the last follow-up, 34 of 44 (77%) of patients were alive, with 1- and 2-year OS of 90% and 79% and RFS of 88% and 71%, respectively. The most common grade 3+ toxicities observed were mucositis (31 patients [71%]) and nephrotoxicity (6 patients [13%]), both of which were deemed multifactorial in cause. Four patients (9%) in standard-dose cohort developed grade 3+ pneumonitis, with 3 cases in the setting of documented respiratory infection and only 1 (2%) deemed likely related to radiation alone. VMAT-TBI provides a safe alternative to cTBI. The dose modulation capability of VMAT-TBI may lead to new treatment strategies, such as simultaneous boost and further critical organ sparing, for better malignant cell eradication, immune suppression, and lower toxicities., (Published by Elsevier Inc.)

Purpose: Pre-calculation of accurate dose deposition kernels for treatment planning of spot-based radiotherapies, such as Gamma Knife (GK) and Gamma Pod (GP), can be very time-consuming and may require large data storage with an enormous number of possible spots. We proposed a novel kernel decomposition (KD) model to address accurate and fast (real-time) dose calculation with reduced data storage requirements for spot-based treatment planning. The application of the KD model was demonstrated for clinical GK and GP radiotherapy platforms., Methods: The dose deposition kernel at each spot (shot position) is modeled as the product of a shift-invariant kernel based on a reference kernel and spatially variant scale factor. The reference kernel, one for each collimator, is defined at the center of the commissioning phantom for GK and at the center of the treatment target for GP and calculated using the Monte Carlo (MC) method. The spatially variant scale factor is defined as the ratio of the mean tissue maximum ratio (TMR) at the candidate shot position to that at the reference kernel position, and the mean TMR map is calculated within the entire volume through parallel beam ray tracing on the density image followed by averaging over all source directions. The proposed KD dose calculations were compared with the MC method and with the GK and GP treatment planning system (TPS) computations for various shot positions and collimator sizes utilizing a phantom and 14 and 12 clinical plans for GK and GP, respectively., Results: For the phantom study, the KD Gamma index (3%/1 mm) passing rates were greater than 99% (median 100%) relative to the MC doses, except for the shots close to the boundary. The passing rates dropped below 90% for 8 mm (16 mm) shots positioned within ∼1 cm (∼2 cm) of the boundary. For the clinical GK plans, the KD Gamma passing rates were greater than 99% (median 100%) compared to the MC and greater than 92% (median 99%) compared to the TPS. For the clinical GP plans, the KD Gamma passing rates were greater than 95% (median 98%) compared to the MC and greater than 91% (median 97%) compared to the TPS. The scale factors were calculated in sub-seconds with GPU implementation and only need to be calculated once before treatment plan optimization. The calculation of the dose kernel was also within sub-seconds without requiring beam-by-beam calculation commonly done in the TPS., Conclusion: The proposed model can provide an accurate dose and enables real-time dose and derivative calculations by kernel shifting and scaling without pre-calculating or requiring large data storage for GK and GP dose deposition kernels during treatment planning. This model could be useful for spot-based radiotherapy treatment planning by allowing an efficient global fine search for optimal spots., (© 2021 American Association of Physicists in Medicine.)

Background and Purpose: Involuntary motion due to swallowing cause inaccurate dose delivery during larynx radiotherapy, a deviation that may be particularly problematic during stereotactic body radiation therapy (SBRT). The goal of this study was to develop a motion management solution for larynx SBRT using surface imaging., Material and Methods: Ten patients were recently treated on a phase II study of larynx SBRT on a LINAC equipped with a surface guidance system. A small region of the immobilization mask was manually cut open to allow surface tracking. Pre-treatment and intra-fractional CBCTs were acquired to verify internal anatomy. Patients were verbally instructed not to swallow during treatment. During treatment delivery, beam hold was initiated by the Motion Management Interface if surface motion exceeded a patient-specific threshold. Patient motion was recorded in log files and analyzed. We also performed phantom studies to assess the theoretical impact of gating on dose delivery., Results: The frequency (6.5 ± 5.2 times per fraction) and duration (3.9 ± 2.5 seconds per swallow) of swallowing varied both between patients and fractions. The magnitude of each swallow showed mean peak amplitude at 5.8 ± 3.8 mm above baseline, mostly in the longitudinal direction. Beam duty cycle was 95.0% ± 7.0% (absolute range: 76-100%), with inefficiency most prominent in the early fractions. The 95th percentile residual motion was reduced from 3.4 mm to 2.3 mm with both verbal instruction and gating. Phantom studies confirmed dose delivery accuracy represented by gamma pass rate was improved by 5% using this approach., Conclusions: Laryngeal motion management using surface imaging is feasible and efficacious. Uncontrolled movement of the larynx was not uncommon during treatment, with gating reducing potential for unplanned dose deviations. Additional research is needed to determine the clinical benefit with this system., (Copyright © 2020 Elsevier B.V. All rights reserved.)

We developed a fluence map prediction method that directly generates fluence maps for a given desired dose distribution without optimization for volumetric modulated arc therapy (VMAT) planning. The prediction consists of two steps. First, projections of the desired dose are calculated and then inversely mapped to fluence maps in the phantom geometry by a deep neural network. Second, a plan scaling technique is applied to scale fluence maps from phantom to patient geometry. We evaluated the performance of the proposed fluence map prediction method for 102 head and neck (H&N) and 14 prostate cancer VMAT plans by comparing the patient doses calculated from the predicted fluence maps with the given desired dose distributions. The mean dose differences were 1.42% ± 0.37%, 1.53% ± 0.44% and 1.25% ± 0.44% for the planning target volume (PTV), the region from the PTV boundary to the 50% isodose line, and the region from the 50% to the 20% isodose line, respectively. The gamma passing rate was 98.06% ± 2.64% with the 3 mm/3% criterion. The prediction time for a single VMAT plan was less than one second. In conclusion, we developed an inverse mapping-based method that predicts fluence maps for desired dose distributions with high accuracy. Our method is effectively an optimization-free inverse planning approach, which was orders of magnitude faster than fluence map optimization. Combining the proposed method with leaf sequencing has the potential to dramatically speed up VMAT treatment planning., (© 2020 Institute of Physics and Engineering in Medicine.)

Purpose: GammaPod, a stereotactic partial breast irradiator allowing highly conformal radiation dose delivery, has its unique mechanical design and treatment planning system (TPS). However, the uniqueness of the system poses challenges regarding initial GammaPod system commissioning and routine quality assurance (QA). In this study, we report POD-DOSI, a dedicated dosimetry system for accurate and efficient commissioning and QA of GammaPod., Materials and Methods: The POD-DOSI system consists of two subsystems, POD-Scanner and POD-Calculator. The POD-Scanner is an automatic ion-chamber positioning system driven by two translational stepper motors for anterior-posterior, longitudinal, and lateral beam scanning. The stepper motors are controlled by a microcomputer through an in-house-developed graphical user interface, which can be remotely accessed by a laptop via wireless connection. The POD-Calculator is a commissioned GPU-based Monte Carlo dose calculation engine, which calculates dose by transporting particles from phase space constructed for GammaPod. In our institution, the POD-DOSI system was used for GammaPod TPS commissioning and dose verification. The POD-Calculator was further developed as a secondary dose calculation tool performing patient-specific plan QA before each treatment., Results: The POD-DOSI system has been fully evaluated and tested, both mechanically and dosimetrically, and applied successfully to drive the commissioning of our GammaPod system. The POD-Scanner achieved 0.1 mm accuracy in ion-chamber positioning tests. The POD-Calculator generated dose profiles matched well with water phantom measurements and TPS calculations to <0.5 mm accuracy. For end-to-end test on 56 different treatment plans, in-water point dose measurements by POD-Scanner were within ±2.20% of the doses calculated by POD-Calculator (range: -2.01% to 2.20%, mean: 0.04%, std&#95;dev: 1.10%). Correspondingly, when switching the calculation medium from water to breast tissue, the point doses calculated by the POD-Calculator were within ±1.60% of the point doses calculated by the GammaPOD TPS (range: -1.59% to 1.51%, mean: -0.02%, std&#95;dev: 0.73%). The average three-dimensional gamma passing rate between the GammaPod TPS doses and the POD-Calculator doses was 97.10% under the 2%/1 mm gamma criteria. The POD-DOSI system substantially shortened the GammaPod dosimetry commissioning time from weeks to days., Conclusion: The developed POD-DOSI system resolves the challenges and streamlines the process of GammaPod commissioning and QA. It improves the efficiency and accuracy for both GammaPod commissioning and routine patient-specific QA., (© 2020 American Association of Physicists in Medicine.)

Introduction: Stereotactic body radiation therapy (SBRT) was found effective in treating laryngeal cancer with only five treatment fractions by a recent clinical trial (NCT01984502, ClinicalTrials.gov). Nevertheless, this trial used the Cyberknife system, which is not widely accessible enough to benefit all patients affected by laryngeal cancer. Our study investigates the feasibility of larynx SBRT treatment planning on a conventional gantry-based LINAC and compares its plan quality with that from the Cyberknife., Materials & Methods: Ten larynx SBRT cases were originally treated by Cyberknife using fixed cones in our institution, with plans created and optimized using the Monte-Carlo algorithm in the MultiPlan treatment planning system. These cases were retrospectively planned in the Eclipse planning system for a LINAC with the same prescription dose. We used volumetric modulated arc therapy (VMAT) for larynx SBRT planning in Eclipse and incorporated non-coplanar arcs to approach the Cyberknife's large solid angle delivery space. We used both anisotropic analytical algorithm (AAA) and Acuros XB (AXB) algorithm for dose calculation and compared their accuracy by measurements on an in-house larynx phantom. We compared the LINAC VMAT plans (VMAT-AAA and VMAT-AXB) with the original Cyberknife plans using dosimetric endpoints such as the conformity index, gradient indices (R50, R20), OAR maximum/mean doses, and the monitor units., Results: Phantom measurement showed that both the AAA and the AXB algorithms provided adequate dose calculation accuracy (94.7% gamma pass rate on 2%/2 mm criteria for AAA vs. 97.3% for AXB), though AXB provided better accuracy in the air cavity. The LINAC-based VMAT plans achieved similar dosimetric endpoints as the Cyberknife planning, and all plans met the larynx SBRT dosimetric constraints. Cyberknife plans achieved an average conformity index of 1.13, compared to 1.20 of VMAT-AXB and 1.19 of VMAT-AAA. The VMAT plans spared the thyroid gland better with average Dmean of 2.4 Gy (VMAT-AXB) and 2.7 Gy (VMAT-AAA), as compared to 4.3 Gy for Cyberknife plans. The VMAT-AAA plans had a slightly lower contralateral arytenoid Dmax (average: 15.2 Gy) than Cyberknife plans (average: 17.9 Gy) with statistical significance, while the contralateral arytenoid Dmax was similar between VMAT-AXB and Cyberknife plans with no statistically significant difference. Cyberknife plans offered slightly better R50 (average: 5.0) than VMAT-AXB (5.9) and VMAT-AAA (5.7) plans. The VMAT plans substantially reduced the plan MUs to less than 1/3 of the Cyberknife plans, and the differences were statistically significant. The other metrics were similar between VMAT and Cyberknife plans with no statistically significant differences., Conclusions: Gantry-based LINACs can achieve similar plan quality to Cyberknife systems. Treatment outcome with both methods remains to be investigated.

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate this issue by guiding clinical plan optimization to save time and maintain high quality plans. We have modified a convolutional deep network model, U-net (originally designed for segmentation purposes), for predicting dose from patient image contours of the planning target volume (PTV) and organs at risk (OAR). We show that, as an example, we are able to accurately predict the dose of intensity-modulated radiation therapy (IMRT) for prostate cancer patients, where the average Dice similarity coefficient is 0.91 when comparing the predicted vs. true isodose volumes between 0% and 100% of the prescription dose. The average value of the absolute differences in [max, mean] dose is found to be under 5% of the prescription dose, specifically for each structure is [1.80%, 1.03%](PTV), [1.94%, 4.22%](Bladder), [1.80%, 0.48%](Body), [3.87%, 1.79%](L Femoral Head), [5.07%, 2.55%](R Femoral Head), and [1.26%, 1.62%](Rectum) of the prescription dose. We thus managed to map a desired radiation dose distribution from a patient's PTV and OAR contours. As an additional advantage, relatively little data was used in the techniques and models described in this paper.

Purpose: The flattening filter (FF) has traditionally been used to flatten beams or create uniform fields in conformal and intensity-modulated radiation therapy (IMRT) but reduces the dose rate. Many studies have confirmed improvement in delivery efficiency by removing the FF, also known as flattening filter free (FFF), especially for small field stereotactic body radiation therapy (SBRT); but it is unclear if large treatment fields still favor the FFF beam. We propose a novel, unified approach to quantify delivery efficiency of the FFF and flattened beams., Methods: We modeled the FF effect by inverse conical filters and systematically studied delivery efficiency (beam-on time, BOT) by varying the filter thickness, including the FF and FFF mode. We formulated the BOT of different beams for any arbitrary fluence map in linear programming to solve the optimal inverse conical filter that minimizes the BOT. One-dimensional optimal filters of minimum BOT were also derived in closed form for conical fluence to gain insight for arbitrary clinical fluence maps. We evaluated the BOT of the FFF beam and flattened beam for conformal treatment fields of various dimensions ranging from 5 cm × 5 cm to 25 cm × 25 cm. We also analyzed the BOT for 698 clinical IMRT prostate fluence maps of field size 10 cm × 10 cm, 17 head-and-neck fluence maps of field size 15 cm × 15 cm, and additional realistic test data from 90° rotation and up to 40 cm × 40 cm enlargement of these clinical fluence maps, which were all initially generated with flattened beams., Results: The FFF beam minimized the BOT for A field size less than 20 cm in single leaf pair cases and for conformal fields of dimension less than 20 cm × 20 cm. The FFF beam also minimized the BOT for all tested prostate and head-and-neck cases. The median BOT ratios of the FFF beam to the flattened beam were 0.56 and 0.61 for prostate and head-and-neck cases, respectively. The FFF beam minimized the BOT for field size up to 30 cm × 30 cm and had similar BOTs to those of the flattened beam for field size greater than 30 cm × 30 cm in those clinically realistic test data., Conclusion: The filter modeling and BOT calculation enable us to quantify delivery efficiency of the FFF beam and flattened beam in a unified approach. The FFF beam minimized the BOT both theoretically and in simulations for all clinically relevant field sizes and fluence maps in IMRT. The results for conformal fields imply that the FFF beam requires less BOT than the flattened beam for volumetric modulated arc therapy (VMAT) treatments. The delivery efficiency consideration favors the FFF beam in intensity-modulated treatments and may eventually lead to removal of the FF in all future linear accelerator head designs., (© 2018 American Association of Physicists in Medicine.)

Background: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction., Methods: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including 12 with Grade ≥ 2 rectum toxicity and 30 patients with Grade 0-1 toxicity (non-toxicity patients). The cumulative equivalent 2-Gy rectal surface dose was deformably summed using the deformation vector fields obtained through a recent developed local topology preserved non-rigid point matching algorithm. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectum surface dose map (RSDM). The dose volume parameters (DVPs) were calculated from the 3D rectum surface, while the texture features and the dose geometric parameters (DGPs) were extracted from the 2D RSDM. Representative features further computed from DVPs, textures and DGPs by principle component analysis (PCA) and statistical analysis were respectively fed into a support vector machine equipped with a sequential feature selection procedure. The predictive powers of the representative features were compared with the GEC-ESTRO dosimetric parameters D 0.1/1/2cm 3 ., Results: Satisfactory predictive accuracy of sensitivity 74.75 and 84.75%, specificity 72.67 and 79.87%, and area under the receiver operating characteristic curve (AUC) 0.82 and 0.91 were respectively achieved by the PCA features and statistical significant features, which were superior to the D 0.1/1/2cm 3 (AUC 0.71). The relative area in dose levels of 64Gy, 67Gy, 68Gy, 87Gy, 88Gy and 89Gy, perimeters in dose levels of 89Gy, as well as two texture features were ranked as the important factors that were closely correlated with rectal toxicity., Conclusions: Our extensive experimental results have demonstrated the feasibility of the proposed scheme. A future large patient cohort study is still needed for model validation.

Purpose: To assess whether the optimal gating window for each beam during lung radiation therapy with respiratory gating will be dependent on a variety of patient-specific factors, such as tumor size and location and the extent of relative tumor and organ motion., Methods and Materials: To create optimal gating treatment plans, we started from an optimized clinical plan, created a plan per respiratory phase using the same beam arrangements, and used an inverse planning optimization approach to determine the optimal gating window for each beam and optimal beam weights (ie, monitor units). Two pieces of information were used for optimization: (1) the state of the anatomy at each phase, extracted from 4-dimensional computed tomography scans; and (2) the time spent in each state, estimated from a 2-minute monitoring of the patient's breathing motion. We retrospectively studied 15 lung cancer patients clinically treated by hypofractionated conformal radiation therapy, for whom 45 to 60 Gy was administered over 3 to 15 fractions using 7 to 13 beams. Mean gross tumor volume and respiratory-induced tumor motion were 82.5 cm 3 and 1.0 cm, respectively., Results: Although patients spent most of their respiratory cycle in end-exhalation (EE), our optimal gating plans used EE for only 34% of the beams. Using optimal gating, maximum and mean doses to the esophagus, heart, and spinal cord were reduced by an average of 15% to 26%, and the beam-on times were reduced by an average of 23% compared with equivalent single-phase EE gated plans (P<.034, paired 2-tailed t test)., Conclusions: We introduce a personalized respiratory-gating technique in which inverse planning optimization is used to determine patient- and beam-specific gating phases toward enhancing dosimetric quality of radiation therapy treatment plans., (Copyright © 2017 Elsevier Inc. All rights reserved.)

In intensity modulated radiotherapy (IMRT), the optimal plan for each patient is specific due to unique patient anatomy. To achieve such a plan, patient-specific dosimetric goals reflecting each patient's unique anatomy should be defined and adopted in the treatment planning procedure for plan quality control. This study is to develop such a personalized treatment plan quality control tool by predicting patient-specific dosimetric endpoints (DEs). The incorporation of patient specific DEs is realized by a multi-OAR geometry-dosimetry model, capable of predicting optimal DEs based on the individual patient's geometry. The overall quality of a treatment plan is then judged with a numerical treatment plan quality indicator and characterized as optimal or suboptimal. Taking advantage of clinically available prostate volumetric modulated arc therapy (VMAT) treatment plans, we built and evaluated our proposed plan quality control tool. Using our developed tool, six of twenty evaluated plans were identified as sub-optimal plans. After plan re-optimization, these suboptimal plans achieved better OAR dose sparing without sacrificing the PTV coverage, and the dosimetric endpoints of the re-optimized plans agreed well with the model predicted values, which validate the predictability of the proposed tool. In conclusion, the developed tool is able to accurately predict optimally achievable DEs of multiple OARs, identify suboptimal plans, and guide plan optimization. It is a useful tool for achieving patient-specific treatment plan quality control.

We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose-volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25-55 s.

The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 x 5 mm(2) beamlet size and 2.5 x 2.5 x 2.5 mm(3) voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.

Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.