Beam Angle Optimization Research Articles

RIS-assisted optical receiver model and reflected angle optimization for visible light communication in mobile environments

Reconfigurable intelligent surfaces (RIS) supply high-speed and in-depth coverage wireless networks for visible light communication (VLC) systems, improving the system adaptability to mobile scenarios. But the angle-related efficiency loss caused by the diffraction effect of RIS as well as the angular response of the lens-enhanced optical receiver severely affects the practical performance of the RIS-assisted VLC system, which have not draw the attention of researchers. By the influences of these adverse properties, the beam angle configuration method should be further explored. In this paper, a RIS-assisted optical receiver model that jointly considering the angle-related characteristics of both the RIS reflector and the receiver is proposed. Based on the model, the receiver property is characterized, and the beam angle optimization to achieve the maximum optical power is presented. The results of simulations verify the validity of the obtained optimal reflected angle, and test the practical detecting range of the optimally configured RIS-assisted receiver.

On polling directions for randomized direct-search approaches: application to beam angle optimization in intensity-modulated proton therapy

AbstractDeterministic direct-search methods have been successfully used to address real-world challenging optimization problems, including the beam angle optimization (BAO) problem in radiation therapy treatment planning. BAO is a highly non-convex optimization problem typically treated as the optimization of an expensive multi-modal black-box function which results in a computationally time consuming procedure. For the recently available modalities of radiation therapy with protons (instead of photons) further efficiency in terms of computational time is required despite the success of the different strategies developed to accelerate BAO approaches. Introducing randomization into otherwise deterministic direct-search approaches has been shown to lead to excellent computational performance, particularly when considering a reduced number (as low as two) of random poll directions at each iteration. In this study several randomized direct-search strategies are tested considering different sets of polling directions. Results obtained using a prostate and a head-and-neck cancer cases confirmed the high-quality results obtained by deterministic direct-search methods. Randomized strategies using a reduced number of polling directions showed difficulties for the higher dimensional search space (head-and-neck) and, despite the excellent mean results for the prostate cancer case, outliers were observed, a result that is often ignored in the literature. While, for general global optimization problems, mean results (or obtaining the global optimum once) might be enough for assessing the performance of the randomized method, in real-world problems one should not disregard the worst-case scenario and beware of the possibility of poor results since, many times, it is only possible to run the optimization problem once. This is even more important in healthcare applications where the mean patient does not exist and the best treatment possible must be assured for every patient.

A multiobjective beam angle optimization framework for intensity-modulated radiation therapy

Radiation therapy treatment planning is inherently a multiobjective problem, aiming to obtain the best tradeoffs between irradiating the tumor with the prescribed dose and sparing as much as possible the surrounding healthy organs. Many different multiobjective approaches have been proposed for the optimization of radiation intensities for fixed beam irradiation directions. However, multiobjective beam angle optimization is seldom considered. The purpose of this paper is to introduce a new multiobjective optimization framework that explicitly and simultaneously considers the optimization of intensities and also beam directions. Whilst multiobjective optimization of radiation intensities considering a fixed set of beam directions gives rise to a single Pareto front, beam angle optimization gives rise to the appearance of multiple Pareto fronts, each one associated with a given beam angle set. Our framework proposes a beam angle set choice based on the evaluation of non-dominated solutions belonging to different Pareto fronts, using a tree-based approach and a performance indicator to assess the quality of each Pareto front. The proposed approach, illustrated by head-and-neck cancer cases, allows for more flexibility in the calculation of solutions and a better understanding of the existing compromises between different objectives.

Stereotactic Optimized Automated Radiotherapy (SOAR): a novel automated planning solution for multi-metastatic SRS compared to HyperArc™

Objective. Automated Stereotactic Radiosurgery (SRS) planning solutions improve clinical efficiency and reduce treatment plan variability. Available commercial solutions employ a template-based strategy that may not be optimal for all SRS patients. This study compares a novel beam angle optimized Volumetric Modulated Arc Therapy (VMAT) planning solution for multi-metastatic SRS to the commercial solution HyperArc. Approach. Stereotactic Optimized Automated Radiotherapy (SOAR) performs automated plan creation by combining collision prediction, beam angle optimization, and dose optimization to produce individualized high-quality SRS plans using Eclipse Scripting. In this retrospective study 50 patients were planned using SOAR and HyperArc. Assessed dose metrics included the Conformity Index (CI), Gradient Index (GI), and doses to organs-at-risk. Complexity metrics evaluated the modulation, gantry speed, and dose rate complexity. Plan dosimetric quality, and complexity were compared using double-sided Wilcoxon signed rank tests (α = 0.05) adjusted for multiple comparisons. Main Results. The median target CI was 0.82 with SOAR and 0.79 with HyperArc (p < .001). Median GI was 1.85 for SOAR and 1.68 for HyperArc (p < .001). The median V12Gy normal brain volume for SOAR and HyperArc were 7.76 cm3 and 7.47 cm3 respectively. Median doses to the eyes, lens, optic nerves, and optic chiasm were statistically significant favoring SOAR. The SOAR algorithm scored lower for all complexity metrics assessed. Significance. In-house developed automated planning solutions are a viable alternative to commercial solutions. SOAR designs high-quality patient-specific SRS plans with a greater degree of versatility than template-based methods.

Dosimetrically motivated beam-angle optimization for non-coplanar arc radiotherapy with and without dynamic collimator rotation.

Non-coplanar techniques have shown to improve the achievable dose distribution compared to standard coplanar techniques for multiple treatment sites but finding optimal beam directions is challenging. Dynamic collimator trajectory radiotherapy (colli-DTRT) is a new intensity modulated radiotherapy technique that uses non-coplanar partial arcs and dynamic collimator rotation. To solve the beam angle optimization (BAO) problem for colli-DTRT and non-coplanar VMAT (NC-VMAT) by determining the table-angle and the gantry-angle ranges of the partial arcs through iterative 4π fluence map optimization (FMO) and beam direction elimination. BAO considers all available beam directions sampled on a gantry-table map with the collimator angle aligned to the superior-inferior axis (colli-DTRT) or static (NC-VMAT). First, FMO is performed, and beam directions are scored based on their contributions to the objective function. The map is thresholded to remove the least contributing beam directions, and arc candidates are formed by adjacent beam directions with the same table angle. Next, FMO and arc candidate trimming, based on objective function penalty score, is performed iteratively until a desired total gantry angle range is reached. Direct aperture optimization on the final set of colli-DTRT or NC-VMAT arcs generates deliverable plans. colli-DTRT and NC-VMAT plans were created for seven clinically-motivated cases with targets in the head and neck (two cases), brain, esophagus, lung, breast, and prostate. colli-DTRT and NC-VMAT were compared to coplanar VMAT plans as well as to class-solution non-coplanar VMAT plans for the brain and head and neck cases. Dosimetric validation was performed for one colli-DTRT (head and neck) and one NC-VMAT (breast) plan using film measurements. Target coverage and conformity was similar for all techniques. colli-DTRT and NC-VMAT plans had improved dosimetric performance compared to coplanar VMAT for all treatment sites except prostate where all techniques were equivalent. For the head and neck and brain cases, mean dose reduction-in percentage of the prescription dose-to parallel organs was on average 0.7% (colli-DTRT), 0.8% (NC-VMAT) and 0.4% (class-solution) compared to VMAT. The reduction in D2% for the serial organs was on average 1.7% (colli-DTRT), 2.0% (NC-VMAT) and 0.9% (class-solution). For the esophagus, lung, and breast cases, mean dose reduction to parallel organs was on average 0.2% (colli-DTRT) and 0.3% (NC-VMAT) compared to VMAT. The reduction in D2% for the serial organs was on average 1.3% (colli-DTRT) and 0.9% (NC-VMAT). Estimated delivery times for colli-DTRT and NC-VMAT were below 4 min for a full gantry angle range of 720°, including transitions between arcs, except for the brain case where multiple arcs covered the whole table angle range. These times are in the same order as the class-solution for the head and neck and brain cases. Total optimization times were 25%-107% longer for colli-DTRT, including BAO, compared to VMAT. We successfully developed dosimetrically motivated BAO for colli-DTRT and NC-VMAT treatment planning. colli-DTRT and NC-VMAT are applicable to multiple treatment sites, including body sites, with beneficial or equivalent dosimetric performances compared to coplanar VMAT and reasonable delivery times.

Implementation and evaluation of an iterative-based algorithm for automatic beam angle optimization in breast cancer treatment planning

IntroductionA beam angle optimization (BAO) algorithm was developed to evaluate its clinical feasibility and investigate the impact of varying BAO constraints on breast cancer treatment plans. Materials and MethodsA two-part study was designed. In part 1, we retrospectively selected 20 patients treated with radiotherapy after breast-conserving surgery. For each patient, BAO plans were designed using beam angles optimized by the BAO algorithm and the same optimization constraints as manual plans. Dosimetric indices were compared between BAO and manual plans. In part 2, fifteen patients with left breast cancer were included. For each patient, three distinct cardiac constraints (mean heart dose < 5 Gy, 3 Gy or 1 Gy) were established during the BAO process to obtain three optimized beam sets which were marked as BAO_H1, BAO_H3, BAO_H5, respectively. These sets of beams were then utilized under identical IMRT constraints for planning. Comparative analysis was conducted among the three groups of plans. ResultsFor part 1, no significant differences were observed between BAO plans and manual plans in all dosimetric indices, except for ipsilateral lung V5, where BAO plans performed slightly better than manual plans (35.5% ± 5.6% vs 36.9% ± 4.3%, p = 0.034). For part 2, Stricter BAO heart constraints resulted in more perpendicular beams. However, there was no significant difference between BAO_H1, BAO_H3 and BAO_H5 with the same IMRT constraint in the heart dose. Meanwhile, the left lung dose was increased while the right breast and lung doses were decreased with stricter heart constraints in BAO. When mean heart dose < 5 Gy in IMRT constraint, the mean dose to the right lung was decreased from 0.46 Gy for BAO_H5 to 0.33 Gy for BAO_H1 (p = 0.027). ConclusionsThe BAO algorithm can achieve quality plans comparable to manual plans. IMRT constraints dominate the final plan dose, while varying BAO constraints alter the trade-off among structures, providing an additional degree of freedom in planning design.

Per-fraction planning to enhance optimization degrees of freedom compared to the conventional single-plan approach.

&#xD;In conventional radiotherapy, a single treatment plan is generated pre-treatment, and delivered in daily fractions. In this study, we propose to generate different treatment plans for all fractions ('Per-fraction' planning) to reduce cumulative OAR doses. Per-fraction planning was compared to the 'Conventional' single-plan approach for non-coplanar 4x9.5 Gy prostate SBRT.&#xD;&#xD;Approach:&#xD;An in-house application for fully automated, non-coplanar multi-criterial treatment planning with integrated beam angle and fluence optimization was used for plan generations. For the Conventional approach, a single 12-beam non-coplanar IMRT plan with individualized beam angles was generated for each of the 20 included patients. In Per-fraction planning, four fraction plans were generated for each patient. For each fraction, a different set of patient-specific 12-beam configurations could be automatically selected. Per-fraction plans were sequentially generated by adding dose to already generated fraction plan(s). For each fraction, the cumulative- and fraction dose were simultaneously optimized, allowing some minor constraint violations in fraction doses, but not in cumulative.&#xD;&#xD;Main results:&#xD;In the Per-fraction approach, on average 32.9 ± 3.1 [29;39] unique beams per patient were used. PTV doses in the separate Per-fraction plans were acceptable and highly similar to those in Conventional plans, while also fulfilling all OAR hard constraints. When comparing total cumulative doses, Per-fraction planning showed improved bladder sparing for all patients with reductions in Dmean of 22.6% (p=0.0001) and in D1cc of 2.0% (p=0.0001), reductions in patient volumes receiving 30% and 50% of the prescribed dose of 54.7% and 6.3%, respectively, and a 3.1% lower rectum Dmean (p=0.007). Rectum D1cc was 4.1 % higher (p=0.0001) and Urethra dose was similar. &#xD;&#xD;Significance:&#xD;In this proof-of-concept paper, Per-fraction planning resulted in several dose improvements in healthy tissues compared to the Conventional single-plan approach, for similar PTV dose. By keeping the number of beams per fraction the same as in Conventional planning, reported dosimetric improvements could be obtained without increase in fraction durations. Further research is needed to explore the full potential of the Per-fraction planning approach.&#xD.

Feasibility Study of Beam Angle Optimization Based on Scripts in Automated-planning for Liver Cancer

To study the feasibility and potential benefits of beam angle optimization (BAO) to automated planning in liver cancer. An approach of beam angle sampling is proposed to implement BAO along with the module Auto-planning in treatment planning system (TPS) Pinnacle. An in-house developed plan quality metric (PQM) is taken as the preferred evaluating method during the sampling. The process is driven automatically by in-house made Pinnacle scripts both in sampling and scoring. In addition, dosimetry analysis and physician's opinion are also performed as the supplementary and compared with the result of PQM. It is revealed by the numerical analysis of PQM scores that only 15% patients whose superior trials evaluated by PQM are also the initial trials. Gantry optimization can bring benefit to plan quality along with auto-planning in liver cancer. Similar results are provided by both dose comparison and physician's opinion. It is possible to introduce a full automated approach of beam angle optimization to automated planning process. The advantages of this procedure can be observed both in numerical analysis and physician's opinion.

Beam angle optimization for proton therapy via group-sparsity based angle generation method.

In treatment planning, beam angle optimization (BAO) refers to the selection of a subset with a given number of beam angles from all available angles that provides the best plan quality. BAO is a NP-hard combinatorial problem. Although exhaustive search (ES) can exactly solve BAO by exploring all possible combinations, ES is very time-consuming and practically infeasible. To the best of our knowledge, (1) no optimization method has been demonstrated that can provide the exact solution to BAO, and (2) no study has validated an optimization method for solving BAO by benchmarking with the optimal BAO solution (e.g., via ES), both of which will be addressed by this work. This work considers BAO for proton therapy, for example, the selection of 2-4 beam angles for IMPT. The optimal BAO solution is obtained via ES and serves as the ground truth. A new BAO algorithm, namely angle generation (AG) method, is proposed, and demonstrated to provide nearly-exact solutions for BAO in reference to the ES solution. AG iteratively optimizes the angular set via group-sparsity (GS) regularization, until the planning objective does not decrease further. Since GS alone can also solve BAO, AG was validated and compared with GS for 2-angle brain, 3-angle lung, and 4-angle brain cases, in reference to the optimal BAO solutions obtained by ES: the AG solution had the rank (1/276, 1/2024, 4/10626), while the GS solution had the rank (42/276, 279/2024, 4328/10626). A new BAO algorithm called AG is proposed and shown to provide substantially improved accuracy for BAO from current methods with nearly-exact solutions to BAO, in reference to the ground truth of optimal BAO solution via ES.

Fully automated segmentally boosted VMAT.

Treatment planning for volumetric modulated arc therapy (VMAT) typically involves the use of multiple arcs to achieve sufficient intensity modulation. Alternatively, we can perform segment boosting to achieve similar intensity modulation while also reducing the number of control points used. Here, we propose the MetaPlanner Boosted VMAT (MPBV) approach, which generates boosted VMAT plans through a fully automated framework. The proposed MPBV approach is an open-source framework that consists of three main stages: meta-optimization of treatment plan hyperparameters, fast beam angle optimization on a coarse dose grid to select desirable segments for boosting, and final plan generation (i.e., constructing the boosted VMAT arc and performing optimization). Performance for the MPBV approach is evaluated on 21 prostate cases and 6 head and neck cases using clinically relevant plan quality metrics (i.e., target coverage, dose conformity, dose homogeneity, and OAR sparing). As compared to two baseline methods with multiple arcs, MPBV maintains or improves dosimetric performance for the evaluated metrics while substantially reducing average estimated delivery times (from 2.6 to 2.1 min). Our proposed MPBV approach provides an automated framework for producing high-quality VMAT plans that uses fewer control points and reduces delivery time as compared to traditional approaches with multiple arcs. MPBV applies automated treatment planning to segmentally boosted VMAT to address the beam utilization inefficiencies of traditional VMAT approaches that use multiple full arcs.

Effect of Topical Pilocarpine Instilled Before Laser Peripheral Iridotomy on Regional Iris Thickness in Primary Angle Closure Disease: A Swept-Source Anterior Segment Optical Coherence Tomography Pilot Study

ABSTRACT Purpose To determine whether the temporal-superior or the nasal-superior iris area becomes thinner (more optimal) for laser peripheral iridotomy (LPI) after pilocarpine instillation in primary angle closure disease (PACD); and to identify an angle for optimal penetration of the laser beam. Patients and Methods Iris thickness at 2 mm from the iris root in the preset scanning axes was measured using swept-source anterior segment optical coherence tomography before and 60 minutes after the instillation of pilocarpine 2% in one eye of 30 consecutive Japanese PACD patients with thick, dark brown iris. Iris thickness at 1:30 and 10:30 clock hour positions were evaluated in sagittal and oblique directions, resulting sagittal iris thickness (SIT) and minimum iris thickness (MIT) parameters, respectively. Results Compared to the baseline values, iris thickness decreased significantly (P < .001) in both locations after pilocarpine instillation. Both before and after pilocarpine instillation the temporal-superior iris thickness was significantly smaller than the nasal-superior thickness (P ≤ .001). After pilocarpine instillation, the temporal-superior iris was significantly thinner in an approximately 13° angle direction temporal to the sagittal direction than in the sagittal direction (MIT: 0.322 mm; SIT: 0.346 mm, P < .001). Conclusions After pilocarpine instillation, the temporal-superior iris and an approximately 13° angle temporal to the sagittal direction may provide an optimal location and laser beam angle for LPI in PACD eyes.

Operations research contribution to totally automated radiotherapy treatment planning: A noncoplanar beam angle and fluence map optimization engine based on optimization models and algorithms

The planning of radiotherapy treatments is based on the use of mathematical optimization models and algorithms. A treatment plan will correspond to an admissible solution to a problem that is defined by the medical prescription. The medical prescription defines the constraints that have to be satisfied, and that are patient dependent. To find a treatment plan complying with all the defined constraints, an objective function is built, having a set of parameters that can be tuned. In the clinical practice, the objective function parameters are tuned through a trial-and-error procedure. One common way of defining this objective function is to consider as parameters weights that are related with the importance of the corresponding structures of interest (volumes to treat and organs to spare), as well as upper and lower bounds that are related with the constraints defined by the medical prescription. Some treatment options, like the set of irradiation directions (beam angles), are usually defined beforehand by the planner, considering previous experiences with similar cases. This trial-and-error process is lengthy, since it can take up to several hours to calculate an admissible treatment plan for a single patient. There have been some research efforts to automate the treatment planning procedure, releasing the planner for other important tasks in the radiotherapy treatment workflow and guaranteeing the consistent calculation of high-quality plans. In this work derivative-free optimization algorithms are integrated with fuzzy inference systems that automatically tune the objective function parameters so that an admissible solution is found. This fully automated approach was tested and assessed considering six head-and-neck cancer cases already treated at the Portuguese Institute of Oncology at Coimbra (IPOC). For the clinical cases tested, comparisons between different treatment plans clearly favor the proposed approach. For a similar tumor coverage, it was possible to improve the sparing of the spinal cord, brainstem and parotids. Automating radiotherapy treatment planning can contribute to improved treatment plans in a consistent way.

Applying mixed-integer linear programming to the non-coplanar beam angle optimization of intensity-modulated radiotherapy for liver cancer.

Currently, intensity-modulated radiation therapy (IMRT) is commonly used in radiotherapy clinics. However, designing a treatment plan with multiple beam angles depends on the experience of human planners, and is mostly achieved using a trial-and-error approach. It is preferrable but challenging to solve this issue automatically and mathematically using an optimization approach. The goal of this study is to develop a mixed-integer linear programming (MILP) approach for the beam angle optimization (BAO) of non-coplanar IMRT for liver cancer. MILP models for the BAO of both coplanar and non-coplanar IMRT treatment plans were developed. The beam angles of the IMRT plans were first selected by the MILP model built using mathematical optimization software. Next, the IMRT plans with the selected beam angles was created in a commercial treatment planning system. Finally, the fluence map and dose distribution of the IMRT plans were generated under pre-defined dose-volume constraints. The IMRT plans of 10 liver cancer patients previously treated at our institute were used to assessed the proposed MILP models. For each patient, both coplanar and non-coplanar IMRT plans with beam angles optimized by the MILP models were compared with the IMRT plan clinically approved by physicians. The MILP model-guided IMRT plans showed reduced doses for most of the organs at risk (OARs). Compared with the IMRT plans clinically approved by physicians, the doses for the spinal cord (28.5 vs. 36.1, P=0.001<0.05) and liver (27.6 vs. 29.1, P=0.005<0.05) decreased significantly in the IMRT plans with non-coplanar beams selected by the MILP models. The MILP model is an effective tool for the BAO in coplanar and non-coplanar IMRT treatment planning. It facilitates the automation of IMRT treatment planning for current high-precision radiotherapy.

DOSIMETRIC COMPARISON OF PRE-SELECTED BEAM ORIENTATION AND BEAM ANGLE OPTIMIZATION IN INTENSITY MODULATED RADIATION THERAPY PLANS FOR NASOPHARYNGEAL CARCINOMA.

Purpose: This study is intended to verify and analyze the dosimetric impact of Pre selected beam orientation (PSBO) and Beam angle optimization (BAO) in IMRT for Nasopharyngeal Carcinoma. Twenty patients of Nasopharyngeal carcinom Materials and Methods: a treated with IMRT Plans were recruited for this retrospective study. Varian Medical systems treatment planning systems (TPS), Eclipse of version 13.6 were used for planning. All twenty patients were treated with IMRT plan created by PSBO while choosing beam angle. Another plan using BAO used for choosing beam angles followed by PRO optimization for inverse planning were created. Objectives of PTV and OARs are maintained constant in both the plans. Statistical analyses of both the plans were performed using parameters; Paddick conformity index (PCI), Homogeneity index (HI), Dose delivered to OAR and Delivered MU. The statistical data were analyzed by Student t test. In this study, out of twenty patients, Result: seventeen patients BAO were valid for inverse planning optimization. For three patients beam angles chosen by BAO were invalid. And the dosimetric comparison of seventeen patients between BAO and PSBO was showing similar results except for MU. The p value obtained for all the parameters except MU, were &gt;0.05. On taking into consideration of delivered MU, PSBO has lesser MU than BAO and are statistically signicant. Conclusion: On reviewing the results, it is concluded that both BAO and PSBO are clinically acceptable. But on concerning the delivered MU, PSBO seems to be better method than BAO. Also, it should be taken into account that three of the plans have been failed to optimize in BAO, since the beam angles suggested in this BAO method does not account the limitations of machine. It shows the advantage of PSBO over BAO. Hence, we can conclude that PSBO is a better method in selection of beam angles in Nasopharyngeal Carcinoma cases.

Phantom Study of the Optimum Irradiation Angle for Proton Beam Therapy in Hepatocellular Carcinoma

<h3>Purpose/Objective(s)</h3> Passive proton beam therapy (PPBT) for hepatocellular carcinoma (HCC) has a higher local control rate than surgery or photon beam therapy. Moreover, it is attracting attention as one of the new treatment options. In the PPBT planning, the selection of the beam angle is determined according to the subjective judgment of the planner. Therefore, there are differences in the dose distribution depending on the planner. It has not yet been clarified which the irradiation angle can be selected to reduce unnecessary dose on the organ-at-risks and maintain the target coverage. The purpose of this study was to determining the optimal beam angle for liver S8 lesions. <h3>Materials/Methods</h3> The subjects were fifty-four treatment plans for HCC located in S8 irradiated using PPBT during the period of 2012.6-2021.3 at the National Cancer Center Hospital East. Tumor sizes were aggregated from the subjects. Clinical Target Volume (CTV) of the subject's liver ranged from 4 cm3 to 1370 cm3. Tumor sizes ranged from 132 cm to 655 cm3. From these results, the average CTV were represented on a virtual phantom, the dose distribution using PPBT was optimized using two irradiation angles. For the calculation of the optimum irradiation angle, the combination of the two beams rotated every 10 degrees and the best dose distribution was considered to be the optimum angle. The Conformity Index (CI) and Homogeneity Index (HI) of the CTV and the V30 (%) of the liver were calculated using the Dose volume histogram (DVH). <h3>Results</h3> The combination of beam angles showing 1 in the Conformity Index was 360 ° and 250 °, 350 ° and 230 °, 260 ° and 190 ° for small tumor volumes. Homogeneity Index and V30 averaged 1.06 and 28.0%, respectively. At the time of large tumor volume, it was 350 ° and 270 °, 350 ° and 250 °, 250 ° and 170 °. Homogeneity Index and V30 averaged 1.07 and 47.6%, respectively. The treatment schemes beam-arranged with a 70 ° difference in angle between the two beams were the most homogeneous with respect to the target. A significant difference was found in Conformity Index when compared to the most heterogeneous 190 ° difference (p <0.05). <h3>Conclusion</h3> Based on our findings, we recommend using a 2-beam configuration with a beam tilted by approximately 70 ° between the two beams for passive irradiation of hepatocellular carcinoma located in S8. This has the potential to achieve a uniform dose distribution within the target and at the same time reduce the hepatic dose. However, it should be noted that there is a difference in dose increase / decrease depending on the positional relationship of organs and tumors. Further treatment planning studies on aspects of respiration and organ movement need to be conducted.

Robustly optimized hybrid intensity-modulated proton therapy for craniospinal irradiation.

The aim of the study was to investigate the hybrid robust optimization planning approach in intensity-modulated proton therapy (IMPT) of craniospinal irradiation (CSI). Five IMPT-based adult CSI plans in supine position were created using Raystation treatment planning system (TPS) modelled for Proteus plus proton therapy system. A hybrid planning strategy was implemented, where clinical target volume was robustly optimized (RB) for set up uncertainties and planning target volume was optimized for target coverage using minimax algorithm in the TPS. Beam angle selection, optimization, and dose calculation approach were carefully performed to ensure optimum organ at risk (OAR) sparing, even with potential setup and range errors. The complementary dose gradients in junctions were generated using spot assignment and RB technique. Dosimetric outcomes in both nominal plan and the 16 error scenarios (±3 mm setup and 3.5% range) were analyzed using standard dose volume histogram. This planning approach resulted in a homogeneous dose distribution in the target volume of CSI, including the junction regions, by explicitly reducing number of robust optimization scenarios. The proposed technique was also able to achieve excellent coverage to cribriform plate with lower lens doses and minimal dose to other OARs. Target and OAR doses in the nominal plans as well as in the worst case scenarios with setup and range errors were able to meet the predefined clinical goal. This proposed planning technique is efficient, robust against the uncertainties. It could be adopted in other proton therapy centers.

Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma

PurposeComplexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of non-coplanar treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated beam angle optimization was used to define non-coplanar VMAT class solutions (CSs), each consisting of a coplanar arc and additional 1 or 2 fixed, non-coplanar partial arcs. MethodsAutomated planning was used to generate a coplanar VMAT plan with 5 complementary computer-optimized non-coplanar IMRT beams (VMAT+5) for each of the 20 included patients. Subsequently, the frequency distribution of the 100 patient-specific non-coplanar IMRT beam directions was used to select non-coplanar arcs for supplementing coplanar VMAT. A second investigated CS with only one non-coplanar arc consisted of coplanar VMAT plus a partial arc at 90° couch angle (VMATCS90). Plans generated with the two VMATCSs were compared to coplanar VMAT. ResultsVMAT+5 analysis resulted in VMATCS60: two partial non-coplanar arcs at couch angles 60° and −60° to complement coplanar VMAT. Compared to coplanar VMAT, the non-coplanar VMATCS60 and VMATCS90 yielded substantial average dose reductions in OARs associated with xerostomia and dysphagia, i.e., parotids, submandibular glands, oral cavity and swallowing muscles (p < 0.05) for the same PTV coverage and without violating hard constraints. Impact of non-coplanar treatment and superiority of either VMACS60 and VMATCS90 was highly patient dependent. ConclusionsCompared to coplanar VMAT, dose to OARs was substantially reduced with a CS with one or two non-coplanar arcs. Preferences for coplanar or one or two additional arcs are highly patient-specific, balancing plan quality and treatment time.

Toward automatic beam angle selection for pencil‐beam scanning proton liver treatments: A deep learning–based approach

Dose deposition characteristics of proton radiation can be advantageous over photons. Proton treatment planning, however, poses additional challenges for the planners. Proton therapy is usually delivered with only a small number of beam angles, and the quality of a proton treatment plan is largely determined by the beam angles employed. Finding the optimal beam angles for a proton treatment plan requires time and experience, motivating the investigation of automatic beam angle selection methods. A deep learning-based approach to automatic beam angle selection is proposed for the proton pencil-beam scanning treatment planning of liver lesions. We cast beam-angle selection as a multi-label classification problem. To account for angular boundary discontinuity, the underlying convolution neural network is trained with the proposed Circular Earth Mover's Distance-based regularization and multi-label circular-smooth label technique. Furthermore, an analytical algorithm emulating proton treatment planners' clinical practice is employed in post-processing to improve the output of the model. Forty-nine patients that received proton liver treatments between 2017 and 2020 were randomly divided into training (n=31), validation (n=7), and test sets (n=11). AI-selected beam angles were compared with those angles selected by human planners, and the dosimetric outcome was investigated by creating plans using knowledge-based treatment planning. For 7 of the 11 cases in the test set, AI-selected beam angles agreed with those chosen by human planners to within 20° (median angle difference=10°; mean=18.6°). Moreover, out of the total 22 beam angles predicted by the model, 15 (68%) were within 10° of the human-selected angles. The high correlation in beam angles resulted in comparable dosimetric statistics between proton treatment plans generated using AI- and human-selected angles. For the cases with beam angle differences exceeding 20°, the dosimetric analysis showed similar plan quality although with different emphases on organ-at-risk sparing. This pilot study demonstrated the feasibility of a novel deep learning-based beam angle selection technique. Testing on liver cancer patients showed that the resulting plans were clinically viable with comparable dosimetric quality to those using human-selected beam angles. In tandem with auto-contouring and knowledge-based treatment planning tools, the proposed model could represent a pathway for nearly fully automated treatment planning in proton therapy.

PD-0731 Integrated beam angle optimization in IMRT autoplanning for lung cancer

PD-0731 Integrated beam angle optimization in IMRT autoplanning for lung cancer

Caudal foot placement superior to toe elevation for navicular palmaroproximal-palmarodistal-oblique image quality.

Palmaroproximal-palmarodistal oblique (PaPr-PaDiO) radiographs are regularly obtained for a full evaluation of the navicular bone (NB). Despite their routine use, different acquisition techniques are described. To determine optimal foot placement and beam angle for obtaining PaPr-PaDiO views. In vitro experiment. A convenience sample of 26 disarticulated forelimbs were placed in six different positions using a leg press to mimic the weight-bearing position. In each position, navicular PaPr-PaDiO images were obtained with eight different beam angles. The resulting 1248 radiographs were graded for their diagnostic quality and the compacta spongiosa demarcation of the NB. Diagnostic quality and compacta-spongiosa demarcation was graded higher for feet positioned caudally and angle between 40° and 45°. Elevation of the toe significantly decreased the NB palmar border angle (elevated mean: 40.66, SD: 4.46, non-elevated mean: 42.06, SD: 4.70) (P<.01), but seemed to have no obvious positive influence on radiographs. Using disarticulated legs could only mimic positions but, using a press, weight-bearing positions were replicated as closely as possible. The use of a convenience sample makes the results of the study exploratory only. Caudal foot placement seems to improve the image quality of the navicular PaPr-PaDiO view. The widely used standard beam angle of 45° appears to be the favourable angle for acquisition with a varied range of -5°. Elevation of the toe, standard in most commercially available navicular skyline cassette holders, does not influence the obtained image quality.