Re-planning Strategies Research Articles

Optimal Timing of Organs-at-Risk-Sparing Adaptive Radiation Therapy for Head-and-Neck Cancer under Re-planning Resource Constraints.

Prior work on adaptive organ-at-risk (OAR)-sparing radiation therapy has typically reported outcomes based on fixed-number or fixed-interval re-planning, which represent one-size-fits-all approaches and do not account for the variable progression of individual patients' toxicities. The purpose of this study was to determine the personalized optimal timing for re-planning in adaptive OAR-sparing radiation therapy, considering limited re-planning resources, for patients with head and neck cancer (HNC). A novel Markov decision process (MDP) model was developed to determine optimal timing of re-planning based on the patient's expected toxicity, characterized by normal tissue complication probability (NTCP), for four toxicities. The MDP parameters were derived from a dataset comprising 52 HNC patients treated at the University of Texas MD Anderson Cancer Center between 2007 and 2013. Kernel density estimation was used to smooth the sample distributions. Optimal re-planning strategies were obtained when the permissible number of re-plans throughout the treatment was limited to 1, 2, and 3, respectively. The MDP (optimal) solution recommended re-planning when the difference between planned and actual NTCPs (ΔNTCP) was greater than or equal to 1%, 2%, 2%, and 4% at treatment fractions 10, 15, 20, and 25, respectively, exhibiting a temporally increasing pattern. The ΔNTCP thresholds remained constant across the number of re-planning allowances (1, 2, and 3). In limited-resource settings that impeded high-frequency adaptations, ΔNTCP thresholds obtained from an MDP model could derive optimal timing of re-planning to minimize the likelihood of treatment toxicities.

Automated component delivery management under uncertainty for prefabricated buildings to minimize cost and harmful emissions

Effectively coordinating and managing onsite construction, offsite prefabrication, and component delivery activities in an ever-changing environment is crucial for prefabricated or modular construction. This study develops an automated component delivery management system to identify the optimal supplier portfolio and delivery strategy, balancing the trade-offs among time, costs, and carbon emissions before construction. The system incorporates onsite activity rescheduling and delivery re-planning strategies to manage progress uncertainty, thereby minimizing crash and overstock costs. It automatically extracts project design data from building information model (BIM) digital files, schedule data from scheduling programs, and logistic data from the Web Map Service. The outcomes generated are then fed back into BIM platforms for enhanced visualization. An illustrative example showcases the system's effectiveness, demonstrating its ability to support lean construction practices while offering economic and environmental advantages to stakeholders.

Technical note: Optimization functions for re-irradiation treatment planning.

Although re-irradiation is increasingly used in clinical practice, almost no dedicated planning software exists. Standard dose-based optimization functions were adjusted for re-irradiation planning using accumulated equivalent dose in 2-Gy fractions (EQD2) with rigid or deformable dose mapping, tissue-specific α/β, treatment-specific recovery coefficients, and voxelwise adjusted EQD2 penalization levels based on the estimated previously delivered EQD2 (EQD2deliv ). To demonstrate proof-of-concept, 35Gy in 5 fractions was planned to a fictitious spherical relapse planning target volume (PTV) in three separate locations following previous prostate treatment on a virtual human phantom. The PTV locations represented one repeated irradiation scenario and two re-irradiation scenarios. For each scenario, three re-planning strategies with identical PTV dose-functions but various organ at risk (OAR) EQD2-functions was used: 1) reRTregular : Regular functions with fixed EQD2 penalization levels larger than EQD2deliv for all OAR voxels. 2) reRTreduce : As reRTregular , but with lower fixed EQD2 penalization levels aiming to reduce OAR EQD2. 3) reRTvoxelwise : As reRTregular and reRTreduce , but with voxelwise adjusted EQD2 penalization levels based on EQD2deliv . PTV near-minimum and near-maximum dose (D98% /D2% ), homogeneity index (HI), conformity index (CI) and accumulated OAR EQD2 (α/β=3Gy) were evaluated. For the repeated irradiation scenario, all strategies resulted in similar dose distributions. For the re-irradiation scenarios, reRTreduce and reRTvoxelwise reduced accumulated average and near-maximum EQD2 by ˜1-10 Gy for all relevant OARs compared to reRTregular . The reduced OAR doses for reRTreduce came at the cost of distorted dose distributions with D98% = 92.3%, HI = 12.0%, CI = 73.7% and normal tissue hot spots ≥150% for the most complex scenario, while reRTregular (D98% = 98.1%, HI = 3.2%, CI = 94.2%) and reRTvoxelwise (D98% = 96.9%, HI = 6.1%, CI = 93.7%) fulfilled PTV coverage without hot spots. The proposed re-irradiation-specific EQD2-based optimization functions introduce novel planning possibilities with flexible options to guide the trade-off between target coverage and OAR sparing with voxelwise adapted penalization levels based on EQD2deliv .

Convex optimization for post-fault ascent trajectory replanning using auxiliary phases

For ascent trajectory replanning after non-fatal dynamic faults, the terminal orbital constraints and optimization indexes under different replanning strategies usually have very strong nonconvexity, which brings significant challenges to real-time guidance. This paper introduces auxiliary phases to convexify the terminal constraints and objective functions losslessly, significantly improving the convergence and injection accuracy. After lossless and successive convexification, the original problems are converted into a series of convex subproblems. The replanning algorithm is then presented, including the fault detection module, the residual carrying capacity determination module, and the task degradation module. Two typical launch missions are simulated to verify the proposed method's pmethoderformance. Numerical results show that the method can always converge efficiently and reliably in different scenarios and has great potential for real-time onboard applications.

Dosimetric impact of adaptive proton therapy in head and neck cancer - A review.

Intensity Modulated Proton Therapy (IMPT) in head and neck cancer (HNC) is susceptible to anatomical changes and patient set-up inaccuracies during the radiotherapy course, which can cause discrepancies between planned and delivered dose. The discrepancies can be counteracted by adaptive replanning strategies. This article reviews the observed dosimetric impact of adaptive proton therapy (APT) and the timing to perform a plan adaptation in IMPT in HNC. A literature search of articles published in PubMed/MEDLINE, EMBASE and Web of Science from January 2010 to March 2022 was performed. Among a total of 59 records assessed for possible eligibility, ten articles were included in this review. Included studies reported on target coverage deterioration in IMPT plans during the RT course, which was recovered with the application of an APT approach. All APT plans showed an average improved target coverage for the high- and low-dose targets as compared to the accumulated dose on the planned plans. Dose improvements up to 2.5 Gy (3.5 %) and up to 4.0 Gy (7.1 %) in the D98 of the high- and low dose targets were observed with APT. Doses to the organs at risk (OARs) remained equal or decreased slightly after APT was applied. In the included studies, APT was largely performed once, which resulted in the largest target coverage improvement, but eventual additional APT improved the target coverage further. There is no data showing what is the most appropriate timing for APT. APT during IMPT for HNC patients improves target coverage. The largest improvement in target coverage was found with a single adaptive intervention, and an eventual second or more frequent APT application improved the target coverage further. Doses to the OARs remained equal or decreased slightly after applying APT. The most optimal timing for APT is yet to be determined.

A Real-Time Decision Support Approach for Managing Disruptions in Line-Haul Freight Transport Networks

Unexpected disruptions in road freight transport caused by poor weather conditions, traffic accidents, etc., are quite frequent and have negative effects on the whole supply chain. Therefore, an intelligent disruption management system is necessary to revise the transport plan directly after disruptions have occurred. The literature presents several approaches for managing disruptions in road freight transport. However, most of them focus on urban freight distributions where disruptions are often handled by vehicle rerouting. The current work, in contrast, addresses disruption management in a line-haul freight transport network that connects urban distribution systems. We present a novel hybrid approach combining a simulation model, optimization algorithms, and a cost-effectiveness analysis. When a disruption occurs, the proposed approach can be used to analyze the impacts of the disruption, identify the affected trips, and revise their plan quickly in real time. Six re-planning strategies are proposed to handle the disruptions and are evaluated in terms of cost, reliability (expressed in time delays), and CO2 emissions. Cost-effectiveness analyses are conducted to rank the obtained solutions and identify the best strategy. Moreover, we suggest a decision support system architecture, based on the proposed approach, to enable disruption management in real-time settings. Real data is used to evaluate the proposed approach in different disruption scenarios. The results provide transport planners with useful insights into possible re-planning strategies and how to identify the best cost-effective strategy to minimize the disruptions’ effects and be more economically sustainable. This work also supports carriers in the transition towards intelligent disruption management.

Using nature-based solutions to support urban regeneration: A conceptual study

Abstract Nature-based solutions use a holistic viewpoint to address social challenges while providing environmental, social and economic benefits simultaneously. The Victoria Quay is a historical space with complex social and environmental issues. This study uses an investigation-oriented method to explore the re-planning strategies. The environmental problems are addressed by extending the green infrastructure into the site to recover the ecological corridor and alleviate flooding risks. The originally single land-use type is changed, and several historical buildings are transformed into landmarks to improve the connection with city center by linking the ‘golden route’. All the proposed measures tried to reactivate the various relationships rather than merely renew the Victoria Quay.

Use of knowledge based DVH predictions to enhance automated re-planning strategies in head and neck adaptive radiotherapy

This study aimed to investigate if a commercial, knowledge-based tool for radiotherapy planning could be used to estimate the amount of sparing in organs at risk (OARs) in the re-planning strategy for adaptive radiotherapy (ART). Eighty head and neck (HN) VMAT Pareto plans from our institute’s database were used to train a knowledge-based planning (KBP) model. An evaluation set of another 20 HN patients was randomly selected. For each patient in the evaluation set, the planning computed tomography (CT) and 2 sets of on-board cone-beam CT, corresponding to the middle and second half of the radiotherapy treatment course, were extracted. The original plan was re-calculated on a daily deformed CT (delivered dose‐volume histogram (DVH)) and compared with the KBP DVH predictions and with the final KBP DVH after optimisation of the plan, which was performed on the same image sets. To evaluate the feasibility of this method, the range of KBP DVH uncertainties was compared with the gains obtained from re-planning. DVH differences and receiver operating characteristic (ROC) curve analysis were used for this purpose. On average, final KBP uncertainties were smaller than the gain in re-planning. Statistical tests confirmed significant differences between the two groups. ROC analysis showed KBP performance in terms of area under the curve values higher than 0.7, which confirmed a good accuracy in predicted values. Overall, for 48% of cases, KBP predicted a desirable outcome from re-planning, and the final dose confirmed an effective gain in 47% of cases. We have established a systematic workflow to identify effective OAR sparing in re-planning based on KBP predictions that can be implemented in an on-line, ART process.

Parotid sparing adaptive radiotherapy in head and neck cancer patients: A study evaluating resource intensiveness and impact on quality of life.

e24037 Background: Anatomical changes during the course of parotid sparing IMRT for head and neck cancer can lead to an increase in the actual dose absorbed by the parotid glands, which may be controlled with the use of interval adaptive replanning. In this prospective assessment of adaptive replanning for parotid dose changes, we explored the feasibility of carrying out adaptive replanning based on predefined objective dosimetric criteria at specified time points. We sought to assess the impact of this measure using a clinically meaningful endpoint of patient reported quality of life outcomes. Methods: 90 patients with head and neck radiotherapy indicated for definitive management or adjuvant therapy who had at least one parotid gland receiving a mean dose (MD) of between 25-30Gy were accrued in the study. The index parotid was delineated on the images acquired on 14th and 19th day and the MD was determined by overlaying the verification image on the planned CT. If the MD had increased by 2% of the initial intended dose, an adaptive plan was attempted with an aim to reduce MD by 2% without compromising PTV coverage; this plan was then used to deliver the remaining treatment. Patients were invited to complete QoL questionnaires: EORTC-QLQC30 with HN35 module, and XeQoL score at baseline, at 3 and 9 months after completion of treatment. Results: 46 out of 90 patients met the threshold for adaptive replanning and were switched to the new plan during treatment. Adaptive replanning was triggered at D14 for 31 patients and D19 for the remaining 15. Need for adaptive replanning was associated with receipt of concurrent chemotherapy and weight loss in the first two weeks of RT. QoL was evaluable for 50 patients at 3 months post treatment. In patients who required adaptive replanning per protocol, Mean XeQoL scores at 3 months showed significantly worse scores for overall scores (1.1 vs 2.3, p 0.001) and for the component individual physical, pain, psychological, and social domains. EORTC QLQ-C30 and HN35 questionnaires at 3 months also demonstrated significantly worse mean symptom scores of the relevant domains of mouth dryness (39 vs 60), stickiness (32 vs 54) and swallowing (39 vs 60) in patients who required adaptive replanning versus those who did not. No significant QoL trends were observable in the 31 patients who were evaluable at 9 months post treatment. The average time required for each step in the planning process was comparable for both the initial planning workflow and adaptive replanning process. Conclusions: The trigger criteria for replanning identified a population of patients who have significantly worsened quality of life due to radiation induced xerostomia. The benefits of adaptive replanning strategies based on weekly evaluation, binary thresholds and standard planning procedures is doubtful Clinical trial information: CTRI/2017/11/010683.

Projection-Based Collision Detection Algorithm for Stereoelectroencephalography Electrode Risk Assessment and Re-Planning

Surgical planning is crucial to Stereoelectroencephalography (SEEG), a minimally invasive procedure that requires clinicians to operate with no direct view of the brain. Decisions making involves different clinical specialties and requires analysis of multiple multimodal datasets. We present a DepthMap tool designed to localize, measure, and visualize surgical risk, and an AlternativeFinder tool, designed to search for alternative trajectories maintaining adherence to the initial trajectory with three different re-planning strategies: similar entry, similar target, or parallel trajectory. The two tools transform the 3D problem into the 2D domain using projective geometry and distance mapping. Both use the graphics processing unit (GPU) to create a 2D depth image used by DepthMap for measurement and visualization, and by AlternativeFinder to find alternative trajectories. Tools were tested with 12 SEEG cases using digital subtraction angiography. DepthMap was used to measure vessel distance. AlternativeFinder was then used to search for alternatives. Computation time and displacements of the entry and target points for each trajectory and adherence strategy were recorded. The DepthMap tool found vessels in 118 initial trajectories (out of 145). Ninety alternative trajectories were found to meet the required avascular constraints (average 820K alternatives evaluated per initial trajectory). The average computation time was 449 ms per initial trajectory (77 ms when alternatives were found). The tools presented helped clinicians examine and re-plan SEEG trajectories to avoid vascular risks using three adherence strategies. Quantitative measurement of the adherence shows the potential of this tool for clinical use.

Controlling Draft Interactions Between Quadcopter Unmanned Aerial Vehicles with Physics-aware Modeling

In this paper, we address the problem of multiple quadcopter control, where the quadcopters maneuver in close proximity resulting in interference due to air-drafts. We use sparse experimental data to estimate the interference area between palm sized quadcopters and to derive physics-infused models that describe how the air-draft generated by two quadcopters (flying one above the other) affect each other. The observed significant altitude deviations due to airdraft interactions, mainly in the lower quadcopter, is adequately captured by our physics infused machine learning model. We use two strategies to mitigate these effects. First, we propose non-invasive, online and offline trajectory re-planning strategies that allow avoiding the interference zone while reducing the deviations from desired minimum snap trajectories. Second, we propose invasive strategies that re-design control algorithms by incorporating the interference model. We demonstrate how to modify the standard quadcopter PID controller, and how to formulate a model predictive control approach when considering the interference model. Both invasive and non-invasive strategies show significant reduction in tracking error and control signal energy as compared to the case where the interference area is ignored.

Mobile Robot Path Planning in Dynamic Environments Through Globally Guided Reinforcement Learning

Path planning for mobile robots in large dynamic environments is a challenging problem, as the robots are required to efficiently reach their given goals while simultaneously avoiding potential conflicts with other robots or dynamic objects. In the presence of dynamic obstacles, traditional solutions usually employ re-planning strategies, which re-call a planning algorithm to search for an alternative path whenever the robot encounters a conflict. However, such re-planning strategies often cause unnecessary detours. To address this issue, we propose a learning-based technique that exploits environmental spatio-temporal information. Different from existing learning-based methods, we introduce a globally guided reinforcement learning approach ( G2RL ), which incorporates a novel reward structure that generalizes to arbitrary environments. We apply G2RL to solve the multi-robot path planning problem in a fully distributed reactive manner. We evaluate our method across different map types, obstacle densities, and the number of robots. Experimental results show that G2RL generalizes well, outperforming existing distributed methods, and performing very similarly to fully centralized state-of-the-art benchmarks.

The Effect of Self-Regulation of Shame on Teenagers’ Aggression

Studies have found that shame and aggression are closely connected, and self-blaming and re-planning strategies can regulate an individual’s shame. This study conducted two experiments to investigate the effects of self-regulation of shame on explicit and implicit aggressiveness of adolescents. Shame was induced in both experiments by audio recordings describing different shameful situations that adolescents may experience in daily life. The participants of 7th Grade were required to self-regulate their shame by self-blaming strategy, re-planning strategy, or non-regulation, and rated their explicit aggressiveness in study 1 and did implicit association test (IAT) in study 2, respectively. The current studies found that the regulation of shame with self-blaming strategy enhanced explicit aggression, but could not affect the bias of implicit aggression.

Dosimetric Impact of Interfractional Variations in Prostate Cancer Radiotherapy-Implications for Imaging Frequency and Treatment Adaptation.

Background and purpose: To analyze deviations of the applied from the planned doses on a voxel-by-voxel basis for definitive prostate cancer radiotherapy depending on anatomic variations and imaging frequency.Materials and methods: Daily in-room CT imaging was performed in treatment position for 10 patients with prostate cancer undergoing intensity-modulated radiotherapy (340 fraction CTs). Applied fraction doses were recalculated on daily images, and voxel-wise dose accumulation was performed using a deformable registration algorithm. For weekly imaging, weekly position correction vectors were derived and used to rigidly register daily scans of that week to the planning CT scan prior to dose accumulation. Applied and prescribed doses were compared in dependence of the imaging frequency, and derived TCP and NTCP values were calculated.Results: Daily CT-based repositioning resulted in non-significant deviations of all analyzed dose-volume, conformity and uniformity parameters to the CTV, bladder and rectum irrespective of anatomic changes. Derived average TCP values were comparable, and NTCP values for the applied doses to the bladder and rectum did not significantly deviate from the planned values. For weekly imaging, the applied D2 to the CTV, rectum and bladder significantly varied from the planned doses, and the CTV conformity index and D98 decreased. While TCP values were comparable, the NTCP for the bladder erroneously appeared reduced for weekly repositioning.Conclusions: Based on daily diagnostic quality CT imaging and voxel-wise dose accumulation, we demonstrated for the first time that daily, but not weekly imaging resulted in only negligible deviations of the applied from the planned doses for prostate intensity-modulated radiotherapy. Therefore, weekly imaging may not be adequately reliable for adaptive treatment delivery techniques for prostate. This work will contribute to devising adaptive re-planning strategies for prostate radiotherapy.

Learning Replanning Policies With Direct Policy Search

Direct policy search has been successful in learning challenging real-world robotic motor skills by learning open-loop movement primitives with high sample efficiency. These primitives can be generalized to different contexts with varying initial configurations and goals. Current state-of-the-art contextual policy search algorithms can however not adapt to changing, noisy context measurements. Yet, these are common characteristics of real-world robotic tasks. Planning a trajectory ahead based on an inaccurate context that may change during the motion often results in poor accuracy, especially with highly dynamical tasks. To adapt to updated contexts, it is sensible to learn trajectory replanning strategies. We propose a framework to learn trajectory replanning policies via contextual policy search and demonstrate that they are safe for the robot, can be learned efficiently, and outperform non-replanning policies for problems with partially observable or perturbed context.

Hypofractionated Radiation Therapy Using Fiducial Markers: Assessment of Residual Error and Variation of Prostate Volume during Treatment

With the incorporation of fiducial markers as a surrogate for the prostate itself, the systematic and random positioning error can be removed from the treatment. However, geometric uncertainties remain with respect to the prostate’s position. In this study, two topics have been investigated: the residual error in the patient positioning associated to the rigid marker-based registration and the variation of the prostate volume during the treatment. A total of 375 pre-treatment CBCT images from 15 prostate cancer patients treated with a hypofractioned RT (2.7 Gy/session in 25 fractions) are included in the study. Two weeks before the treatment, all patients underwent the implantation of three gold seeds by ultrasound-guided insertion (one at the apex, S1, and two at each side of the prostate base, S2 left, S3 right). The positioning protocol consists of a daily CBCT acquisition followed by a rigid marker-based registration with the planning CT. The position coordinates of the markers and the isocenter are obtained from each study. In each treatment session, the prostate may undergo deformations that can lead to relative displacements between markers different from those of the CT simulation. This fact, together with the subjective alignment of the images, lead to an error associated to the registration. In order to quantify this potential error, the difference between the markers center of mass in the CBCT relative to the treatment isocenter and the center of mass in the CT relative to the planning isocenter was calculated. The residual errors from the combination of systematic and random errors were determined by quadratic addition. Additionally, markers distance variation per treatment session has been analyzed by deducing the separation distance two by two (D12, D13, D23) from markers coordinates. The results obtained for the residual error in the patient positioning are (mm): 0.7 lateral, 1.1 longitudinal, 1.3 vertical. The higher errors detected in the longitudinal and vertical directions could be explained by the prostate rotations on the left-right axis that are not completely compensated by the translational shifts. The distances between markers show a decrease during the treatment course. This fact is associated with a potential reduction in prostate volume. On average, it is observed that in session 12-13 the three distances begin to decrease in magnitude, with D23 showing a smaller reduction at the end of the treatment (about 1 mm). D12 and D13 decrease to 1.6 and 1.8 mm in the last session. The alignment of prostate cancer patients based on CBCT with fiducial markers entails a negligible residual error compared to the margins generally considered. The prostate shows a tendency to reduce its volume during treatment. This fact can have a relevant impact on treatment margins and on treatment re-planning strategies.

Re-planning strategies for space station on-orbit activities executed in emergencies

In this paper, we develop strategies for the problem of space station on-orbit activity re-planning. Considering the effects of emergencies, a preprocessed strategy is firstly proposed to reconstruct conflicting missions. Furthermore, a greedy algorithm with interval-based strategies is used to re-plan the activities of the reconstructed missions by utilizing mission priority and preplanned activity schedule intervals. Taking into account the propagation of complicated constraints, a time backtrack iteration strategy is adopted to solve constraint conflicts. We demonstrate the proposed approach with a notional operation scenario of the Chinese future space station. The results indicate that our method can successfully re-plan space station on-orbit activities when emergencies occur, all constraint conflicts can be solved, and mission accomplishment rate is increased, in comparison with a method that does not include re-planning strategies.

Multicomponent Assessment of the Geometrical Uncertainty and Consequent Margins in Prostate Cancer Radiotherapy Treatment Using Fiducial Markers

The aim is to compute all sources of geometrical uncertainty in prostate radiotherapy using fiducial markers and determine the safety treatment margins. Based on the markers position, correlations between prostate rotation/deformation and rectal and bladder fillings as well as changes in prostate volume during the treatment course are analyzed. The study includes 375 pre-treatment CBCT images from 15 prostate cancer patients treated with hypofractionated radiotherapy. The position coordinates of the markers were obtained from each image acquisition. In addition, rectum and bladder were outlined on CBCTs. The intrafractional error was estimated by an additional post-treatment CBCT acquired on alternate days. Tau-Kendall analysis was performed to correlate organ fillings with prostate rotation/deformation. Delineation uncertainty was assessed from contours of 10 patients performed by two radiation oncologists and repeated twice. The CT contouring was assisted by a multiparametric MR approach combining a T2-weighted with diffusion-weighted imaging, and a gradient recalled echo for fiducial marker identification. Uncertainty associated to treatment unit was estimated from phantom measurements. The obtained clinical margins were 4.4, 7.3, 5.1 mm in the Left-Right, Superior-Inferior, and Anterior-Posterior directions, respectively, being the contouring the most important contribution. The mechanical limitations of the beam delivery system and the associated imaging device entailed errors of the same order as prostate motion, rotation or deformation. Weak correlations between variation of the rectal volume and the presence of rotations/deformations were found (correlation coefficient 0.182, p = 0.001 for rotations around lateral axis; correlation coefficients 0.1, p < 0.05 for deformations). The distance between markers decreased with session number, becoming more pronounced from fraction 13 and reaching 1 - 1.8 mm at the end of the treatment. In summary we have determined the optimal treatment margins based on geometrical uncertainty assessment using van Herk formalism. An appropriate preparation of rectum and bladder involves minimizing the effect of prostate rotations/deformations. The prostate tends to decrease in size during the treatment which could influence treatment re-planning strategies.

Online dose reconstruction for tracked volumetric arc therapy: Real-time implementation and offline quality assurance for prostate SBRT.

Firstly, this study provides a real-time implementation of online dose reconstruction for tracked volumetric arc therapy (VMAT). Secondly, this study describes a novel offline quality assurance tool, based on commercial dose calculation algorithms. Online dose reconstruction for VMAT is a computationally challenging task in terms of computer memory usage and calculation speed. To potentially reduce the amount of memory used, we analyzed the impact of beam angle sampling for dose calculation on the accuracy of the dose distribution. To establish the performance of the method, we planned two single-arc VMAT prostate stereotactic body radiation therapy cases for delivery with dynamic MLC tracking. For quality assurance of our online dose reconstruction method we have also developed a stand-alone offline dose reconstruction tool, which utilizes the RayStation treatment planning system to calculate dose. For the online reconstructed dose distributions of the tracked deliveries, we could establish strong resemblance for 72 and 36 beam co-planar equidistant beam samples with less than 1.2% deviation for the assessed dose-volume indicators (clinical target volume D98 and D2, and rectum D2). We could achieve average runtimes of 28-31ms per reported MLC aperture for both dose computation and accumulation, meeting our real-time requirement. To cross-validate the offline tool, we have compared the planned dose to the offline reconstructed dose for static deliveries and found excellent agreement (3%/3mm global gamma passing rates of 99.8%-100%). Being able to reconstruct dose during delivery enables online quality assurance and online replanning strategies for VMAT. The offline quality assurance tool provides the means to validate novel online dose reconstruction applications using a commercial dose calculation engine.

Fast online replanning for interfraction rotation correction in prostate radiotherapy.

To enable fast online replanning for prostate radiotherapy with the inclusion of interfraction rotations and translations and investigate the possibility for margin reduction via this regime. Online daily replanning for a 35-fraction treatment for five prostate cases is simulated while accounting for anatomical transformations derived from fiducial marker data available in our clinic. Two online replanning strategies were simulated, compensating for: (a) rotation-only in combination with a couch shift and (b) both translation and rotation without a couch shift. They were compared against our current clinical protocol consisting of a single offline plan used over all fractions with daily couch repositioning (translations only). For every patient, the above methods were generated for several planning margins (0-8 mm with 2 mm increments) in order to assess the performance of online replanning in terms of target coverage and investigate the possible dosimetric benefit for the organs at risk. The daily DVHs for each treatment strategy were used for evaluation and the non tumor integral dose (NTID) for the different margins was calculated in order to quantify the overall reduction of the delivered energy to the patient. Our system is able to generate a daily automated prostate plan in less than 2 min. For every patient, the daily treatment plans produce similar dose distributions to the original approved plan (average CTV D99 relative difference: 0.2%). The inclusion of both shifts and rotations can be effectively compensated via replanning among all planning margins (average CTV D99 difference: 0.01 Gy between the two replanning regimes). Online replanning is able to maintain target coverage among all margins, while - as expected - the conventional treatment plan is increasingly affected by the interfraction rotations as the margins shrink (average CTV D99 decrease: 0.2 Gy at 8 mm to 2.9 Gy at 0 mm margin). The possible gain in total delivered energy to the patient was quantified by the decreased NTID ranging from 12.6% at 6 mm to 32.9% at 0 mm. We demonstrate that fast daily replanning can be utilized to account for daily rotations and translations based on the daily positioning protocol. A daily plan can be generated from scratch in less than 2 min making it suitable for online application. Given the large magnitude of prostate rotation around the LR axis, online correction for daily rotations can be beneficial even for the clinical 8 mm margin and could be utilized for treatments with small margin reduction mainly limited then by anatomical deformations and intrafraction motion. Our online replanning pipeline can be used in future treatments with online MR guidance that can lead to further safe reduction of the planning margins.