Scripting a planning avoidance structure to perform simultaneous integrated boost breast on Halcyon linear accelerators.

When planning a simultaneous integrated boost in breast treatment with sliding window intensity-modulated radiotherapy, the use of an oblique anterior field can be advantageous. To limit the irradiation to the tumor bed on the oblique anterior field, we use the "fixed jaw" option during optimization in Eclipse (v15.6, Varian Medical System). However, this option is not available for Halcyon (Varian Medical System) linear accelerators because the beam-defining collimator is only composed of a dual-layer multileaf collimator (MLC) without any jaw collimator. Hence, the optimizer opens the leaves on all target volumes, and leaves facing the heart or medullary canal may be opened on the oblique anterior field. To avoid this unacceptable behavior, we created an avoidance structure using the Eclipse Scripting Application Programming Interface (ESAPI) to force the optimizer to close the leaves when facing critical organs at risk. The avoidance structure was the whole body of the patient subtracted from every beam path used: the tangential fields collimated to the breast planning target volume (PTV) and the oblique anterior field collimated to the tumor bed PTV. The ESAPI has a built-in method that returns a table of points, drawing the outline of a structure at the isocenter plane of a beam. We used this method to build the avoidance structure. We planned 6 breast cancer patients using this structure, and we were able to meet all dosimetric constraints. All MLC leaves were fully closed outside the tumor bed PTV for the oblique anterior field.

Automated contouring, treatment planning, and quality assurance for VMAT craniospinal irradiation (VMAT-CSI).

Purpose: Create a comprehensive automated solution for pediatric and adult VMAT-CSI including contouring, planning, and plan check to reduce planning time and improve plan quality. Methods: Seventy-seven previously treated CSI patients (age, 2-67 years) were used for creation of an auto-contouring model to segment 25 organs at risk (OARs). The auto-contoured OARs were evaluated using the Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD95), and a qualitative ranking by one physician and one physicist (scale: 1-acceptable, 2-minor edits, 3-major edits). The auto-planning script was developed using the Varian Eclipse Scripting API and tested with 20 patients previously treated with either low-dose VMAT-CSI (12 Gy) or high-dose VMAT-CSI (36 Gy + 18 Gy boost). Clinically relevant metrics, planning time, and blinded physician review were used to evaluate significance of differences between the auto and manual plans. Finally, the plan preparation for treatment and plan check processes were automated to improve efficiency and safety of VMAT-CSI. Results: The auto-contours achieved an average DSC of 0.71 ± 0.15, HD95 of 4.81 ± 4.68, and reviewers' ranking of 1.22 ± 0.39, indicating close to "acceptable-as-is" contours. Compared to the manual CSI plans, the auto-plans for both dose regimens achieved statistically significant reductions in body V50% and Dmean for parotids, submandibular, and thyroid glands. The variance in the dosimetric parameters decreased for the auto-plans as compared to the manual plans indicating better plan consistency. From the blinded review, the auto-plans were marked as equivalent or superior to the manual-plans 88.3% of the time. The required time for the auto-contouring and planning was consistently between 1-2 hours compared to an estimated 5-6 hours for manual contouring and planning. Conclusions: Reductions in contouring and planning time without sacrificing plan quality were obtained using the developed auto-planning process. The auto-planning scripts and documentation will be made freely available to other institutions and clinics.

Eclipse web service application programming interface.

Objective.Low-coupling seamless integration of multiple systems is the core foundation of smart radiotherapy. Following Service-Oriented Architecture style, a set of named operations (Eclipse Web Service API, EWSAPI) was developed for realizing network call of Eclipse.Approach.Under the guidance of Vertical Slice Architecture, EWSAPI was implemented in the C# language and based on ASP .Net Core 6.0. Each operation consists of three components: Request, Endpoint and Response. Depending on the function, the exchanged data for each operation, as input or output parameters, is the empty or a predefined JSON data. These operations were realized and enriched gradually, layer by layer, with reference to the clinical business classification. The business logic of each operation was developed and maintained independently. In situations where Eclipse Scripting API(ESAPI) was required, constraints of ESAPI were followed.Main results.Selected features of Eclipse TPS were encapsulated as standard web services, which can be invocated by other software through network. Several processes for data quality control and planning were encapsulated into interfaces, thereby extending the functionality of Eclipse. Currently, EWSAPI already covers testing of service interface, quality control of radiotherapy data, automation tasks for plan designing and DICOM RT files' transmission. All the interfaces support asynchronous invocation. A separate Eclipse context will be created for each invocation, and is released in the end.Significance.EWSAPI which is a set of standard web services for calling Eclipse features through network is flexible and extensible. It is an efficient way to integration of Eclipse and other systems and will be gradually enriched with the deepening of clinical applications.

Vulnerable JavaScript functions detection using stacking of convolutional neural networks.

System security for web-based applications is paramount, and for the avoidance of possible cyberattacks it is important to detect vulnerable JavaScript functions. Developers and security analysts have long relied upon static analysis to investigate vulnerabilities and faults within programs. Static analysis tools are used for analyzing a program's source code and identifying sections of code that need to be further examined by a human analyst. This article suggests a new approach for identifying vulnerable code in JavaScript programs by using ensemble of convolutional neural networks (CNNs) models. These models use vulnerable information and code features to detect related vulnerable code. For identifying different vulnerabilities in JavaScript functions, an approach has been tested which involves the stacking of CNNs with misbalancing, random under sampler, and random over sampler. Our approach uses these CNNs to detect vulnerable code and improve upon current techniques' limitations. Previous research has introduced several approaches to identify vulnerable code in JavaScript programs, but often have their own limitations such as low accuracy rates and high false-positive or false-negative results. Our approach addresses this by using the power of convolutional neural networks and is proven to be highly effective in the detection of vulnerable functions that could be used by cybercriminals. The stacked CNN approach has an approximately 98% accuracy, proving its robustness and usability in real-world scenarios. To evaluate its efficacy, the proposed method is trained using publicly available JavaScript blocks, and the results are assessed using various performance metrics. The research offers a valuable insight into better ways to protect web-based applications and systems from potential threats, leading to a safer online environment for all.

A Model generation method and iteration algorithm for optimising fire protection thickness.

With temperatures rising above 1000 °C within 5 min, hydrocarbon fire causes rapid strength degradation of structural steel members. It is among the most dangerous hazards, such as boiling liquid expanding vapour explosion (BLEVE) in the oil and gas industry. Intumescent coating as passive protection is widely adopted to prevent the steel structure from material property reduction. However, when optimising fire protection with heat transfer simulation, repetitive modelling work and lacking recalculation principle hinder productivity improvement. This method is developed to generate steel beam models and provides an effective algorithm to optimise coating thickness considering the temperature of a specific region. The main functions of the method include: •Providing section dimensions, initial insulation thickness, target temperature and heating time, temperature allowance and mesh size as variables.•Automatically generating the Abaqus steel beam model under 3-side heating conditions.•Effective iteration algorithm to modify fire protection thickness: test containing 38 Universal beam sections with a 5 °C allowance below target shows that 55.2% were completed within five iterations and 76.3% were completed within eight iterations.

A script-enabled interactive checklist document for efficient management of electronic devices in a busy multimodality radiotherapy clinic.

PURPOSE: Develop an efficient, interactive, and instructive checklist document for the management of implanted electronic medical devices in a multimodality radiotherapy clinic. METHODS: The built-in scripting and interactivity of a popular commercial word processor was used to develop an interactive document that changes the information presented to the user based on drop-down selections. The interactivity and scripting were compatible with the radiation oncology information system (ROIS) which allows the document to be accessible by all team members and serve as a permanent record in a patient's electronic chart. RESULTS: The final interactive document, which was clinically deployed after beta testing with a group consisting of nurses and medical physicists, presents information and action plans to the user based on multiple departmental medical device decision trees that are specific to the combination of device, treatment modality, rhythm-pacing dependence for cardiac devices, and distance from the device to the treatment volume. CONCLUSION: A script-enabled interactive document was developed for a busy multimodality clinic, condensing multiple comprehensive departmental guidelines spanning multiple device types and treatment modalities into a single interactive checklist accessible within the ROIS. Given the wide accessibility of the commercial word processor, this approach could be adopted by other clinics to streamline their own respective workflows.

What does it mean to be 'porn literate': perspectives of young people, parents and teachers in Aotearoa New Zealand.

Porn literacy education is a pedagogical strategy responding to youth engagement with pornography through digital media. The approach is intended to increase young people's knowledge and awareness regarding the portrayal of sexuality in Internet pornography. However, what being 'porn literate' entails, and what a porn literacy education curricula should therefore include, is not a settled matter. Recognising the importance of end-user perspectives, 24 semi-structured interviews were conducted with parents, teachers and young people in Aotearoa (New Zealand) and analysed via critical, constructionist thematic analysis. Participants drew on a developmentalist discourse and a discourse of harm to construct porn literacy education as a way to inoculate young people against harmful effects, distortions of reality, and unhealthy messages. In addition to this dominant construction of porn literacy education, we identified talk that to some extent resisted these dominant discourses. Building on these instances of resistance, and asset-based constructions of youth based on their agency and capability, we point to an ethical sexual citizenship pedagogy as an alternative approach to porn literacy education.

Treatment planning of scanned proton beams in RayStation.

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Enhancing Security of Web-Based IoT Services via XSS Vulnerability Detection.

The Internet of Things (IoT) technology is experiencing significant growth and integration into various aspects of daily life. With the rising number of connected devices, diverse security challenges are emerging as substantial threats to IoT. Cross-Site Scripting (XSS) is one of the major security risks in web services and so is within the application layer of IoT. Many existing web applications remain susceptible to XSS vulnerabilities. In this paper, we propose an XSS detection scheme aimed at enhancing the security of IoT, particularly concerning web application services. To achieve this, we developed a framework for combining symbolic execution and dynamic taint analysis to provide a comprehensive security assessment. Our objective is to increase the ratio of vulnerability detection while avoiding false alarms and keeping the required analysis time as minimal. To realize our idea, we have defined an instrumentation scheme for taint analysis and concolic executions and automated the process of vulnerability detection for a web application. Our framework is capable of pinpointing the precise locations of security vulnerabilities and the exact input datasets at risk of XSS threats. Subsequently, the detected flaws can be easily removed. The experimental results demonstrate the validity of the proposed scheme. We achieved a detection rate of XSS threats of 90.62% using a test set of SecuriBench Micro and 69.11% using OWASP while showing 0% false positives.

Automated evaluation for rapid implementation of knowledge-based radiotherapy planning models.

PURPOSE: Knowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models. METHODS: RapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics. RESULTS: RapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity. CONCLUSION: Automated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.

Assessing multi-hazard susceptibility to cryospheric hazards: Lesson learnt from an Alaskan example.

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions. However, global warming is radically changing this situation and will change it even more in the future. For this reason, understanding the spatial and temporal dynamics of geomorphological processes in peri-arctic environments can be crucial to make informed decisions in such unstable environments and shed light on what changes may follow at lower latitudes. For this reason, here we explored the use of data-driven models capable of recognizing locations prone to develop retrogressive thaw slumps (RTSs) and/or active layer detachments (ALDs). These are cryospheric hazards induced by permafrost degradation, and their development can negatively affect human settlements or infrastructure, change the sediment budget and release greenhouse gases. Specifically, we test a binomial Generalized Additive Modeling structure to estimate the probability of RST and ALD occurrences in the North sector of the Alaskan territory. The results we obtain show that our binary classifiers can accurately recognize locations prone to RTS and ALD, in a number of goodness-of-fit (AUCRTS = 0.83; AUCALD = 0.86), random cross-validation (mean AUCRTS = 0.82; mean AUCALD = 0.86), and spatial cross-validation (mean AUCRTS = 0.74; mean AUCALD = 0.80) routines. Overall, our analytical protocol has been implemented to build an open-source tool scripted in Python where all the operational steps are automatized for anyone to replicate the same experiment. Our protocol allows one to access cloud-stored information, pre-process it, and download it locally to be integrated for spatial predictive purposes.

Improved planning efficiency in multiple brain lesion SRS VMAT cases using Eclipse scripting.

Though dosimetry has a multitude of treatment modalities, software, and workflows to aid in the treatment planning process, treatment planners are still responsible for several tedious and monotonous tasks that could decrease their planning efficiency. The purpose of this study was to determine if scripting could improve treatment planning efficiency for multiple brain lesion stereotactic radiosurgery (SRS) volumetric arc therapy cases by reducing planning time commitment. A script was developed for multiple brain lesion SRS cases using Eclipse scripting application programming interface with the intention of improving treatment planning efficiency by creating optimization structures and importing prescription and suggested OS dose metrics to the optimizer. Nine treatment planners were each provided with 3 different multiple brain lesion, single-isocenter SRS cases. Each planner created 2 plans for each case. One of these 2 plans used the SRS script, and the other did not. There were 54 treatment plans developed, totaling 27 plan comparisons. Each of the 54 treatment plans were considered clinically acceptable based on the participating institution's plan quality guidelines. Statistical analyses of planning time commitment with and without the SRS script were performed using RStudio. The mean and median planning times with and without the SRS script were compared using a paired T-test and Wilcoxon Signed Rank test, respectively, and effect size was evaluated using Cohen's classification. Using the SRS script resulted in statistically significant reduction in total contouring time (11.3 vs 2.8 minutes, p < 0.001), optimizer preparation time (7.7 vs 2.1 minutes, p < 0.001), and overall planning time (105.1 vs 77.9 minutes, p < 0.001). This study concluded that scripts developed using Eclipse scripting application programming interface offer an opportunity to improve treatment planning efficiency by reducing the planning time commitment for treatment planners.

AmberMDrun: A Scripting Tool for Running Amber MD in an Easy Way.

MD simulations have been widely applied and become a powerful tool in the field of biomacromolecule simulations and computer-aided drug design, etc., which can estimate binding free energy between receptor and ligand. However, the inputs and force field preparation for performing Amber MD is somewhat complicated, and challenging for beginners. To address this issue, we have developed a script for automatically preparing Amber MD input files, balancing the system, performing Amber MD for production, and predicting receptor-ligand binding free energy. This script is open-source, extensible and can support customization. The core code is written in C++ and has a Python interface, providing both efficient performance and convenience.

A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system.

PURPOSE: To develop an automated planning approach in Raystation and evaluate its feasibility in multiple clinical application scenarios. METHODS: An automated planning approach (Ruiplan) was developed by using the scripting platform of Raystation. Radiotherapy plans were re-generated both automatically by using Ruiplan and manually. 60 patients, including 20 patients with nasopharyngeal carcinoma (NPC), 20 patients with esophageal carcinoma (ESCA), and 20 patients with rectal cancer (RECA) were retrospectively enrolled in this study. Dosimetric and planning efficiency parameters of the automated plans (APs) and manual plans (MPs) were statistically compared. RESULTS: For target coverage, APs yielded superior dose homogeneity in NPC and RECA, while maintaining similar dose conformity for all studied anatomical sites. For OARs sparing, APs led to significant improvement in most OARs sparing. The average planning time required for APs was reduced by more than 43% compared with MPs. Despite the increased monitor units (MUs) for NPC and RECA in APs, the beam-on time of APs and MPs had no statistical difference. Both the MUs and beam-on time of APs were significantly lower than that of MPs in ESCA. CONCLUSIONS: This study developed a new automated planning approach, Ruiplan, it is feasible for multi-treatment techniques and multi-anatomical sites cancer treatment planning. The dose distributions of targets and OARs in the APs were similar or better than those in the MPs, and the planning time of APs showed a sharp reduction compared with the MPs. Thus, Ruiplan provides a promising approach for realizing automated treatment planning in the future.

Reduction of patient specific quality assurance through plan complexity metrics for VMAT plans with an open-source TPS script.

PURPOSE: Volumetric modulated arc therapy (VMAT) is a widespread technique for the delivery of normo-fractionated radiation therapy (NFRT) and stereotactic body radiation therapy (SBRT). It is associated with a significant hardware burden requiring dose rate modulation, collimator movement and gantry rotation synchronisation. Patient specific quality assurance (PSQA) guarantees that the linacs can precisely and accurately deliver the planned dose. However, PSQA requires a significant time allocation and class solutions to reduce this while guaranteeing the deliverability of the plans should be investigated. METHODS: In this study, an in-house developed Eclipse Scripting API (ESAPI) script was used to extract five independent plan complexity metrics from N = 667 VMAT treatment fields. The correlation between metrics and portal dosimetry measurements was investigated with Pearson correlation, box plot analysis and receiver operating characteristic curves, which were used to defined the best performing metric and its threshold. RESULTS: The incidence of fields failing the clinical PSQA criteria of 3%/2mm (NFRT) and 3%/1.5mm (SBRT) was low (N = 1). The mean MLC opening was the metric with the highest correlation with the portal dosimetry data and among the best in discriminating the requirement of PSQA. The thresholds of 16.12 mm (NFRT) and 7.96 mm (SBRT) corresponded to true positive rates higher than 90%. CONCLUSIONS: This work presents a quantitative approach to reduce the time allocation for PSQA by identifying the most complex plans demanding a dedicated measurement. The proposed method requires PSQA for approximately 10% of the plans. The ESAPI script is distributed open-source to ease the investigation and implementation at other institutions.

Development of automated tip preparation for atom probe tomography by using script-controlled FIB-SEM.

Atom probe tomography (APT) has become a popular technique for microstructural analysis of a wide range of alloys and devices over the past two decades owing to the employment of laser-assisted field evaporation and the development of site-specific tip preparation using a focused ion beam (FIB) with a scanning electron microscopy (SEM) system. In laser-assisted field evaporation, laser irradiation conditions largely influence mass resolution; therefore, recent commercial APT instruments allow strict control of the analysis conditions. However, the mass resolution is affected not only by the laser condition but also by the thermal conductivity of the material and the tip shape. In addition, it is also important to keep the tip shape constant in order to obtain tomography data with good reproducibility since the analytical volume highly depends on the tip shape. In this study, we have developed a method to fabricate the tip with the desired shape automatically by using a script-controlled FIB-SEM system, which has traditionally depended on the skill of the FIB-SEM operator. The tip shape was then intentionally changed by using this method, and its effect on the APT data is also discussed.

Development of independent dose verification plugin using Eclipse scripting API for brachytherapy.

In this study, an independent dose verification plugin (DVP) using the Eclipse Scripting Application Programming Interface (ESAPI) for brachytherapy was developed. The DVP was based on the general 2D formalism reported in AAPM-TG43U1. The coordinate and orientation of each source position were extracted from the translation matrix acquired from the treatment planning system (TPS), and the distance between the source and verification point (r) was calculated. Moreover, the angles subtended by the center-tip and tip-tip of the hypothetical line source with respect to the verification point (θ and ß) were calculated. With r, θ, ß and the active length of the source acquired from the TPS, the geometry function was calculated. As the TPS calculated the radial dose function, g(r), and 2D anisotropy function, F(r,θ), by interpolating and extrapolating the corresponding table stored in the TPS, the DVP calculated g(r) and F(r,θ) independently from equations fitted with the Monte Carlo data. The relative deviation of the fitted g(r) and F(r,θ) for the GammaMed Plus HDR 192Ir source was 0.5% and 0.9%, respectively. The acceptance range of the relative dose difference was set to ±1.03% based on the relative deviation between the fitted functions and Monte Carlo data, and the linear error propagation law. For 64 verification points from sixteen plans, the mean of absolute values of the relative dose difference was 0.19%. The standard deviation (SD) of the relative dose difference was 0.17%. The DVP maximizes efficiency and minimizes human error for the brachytherapy plan check.

Uncertainty in Determination of Meteorological Drought Zones Based on Standardized Precipitation Index in the Territory of Poland.

The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990-2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem.

Clinical implementation and validation of an automated adaptive workflow for proton therapy.

Background and purpose: Treatment quality of proton therapy can be monitored by repeat-computed tomography scans (reCTs). However, manual re-delineation of target contours can be time-consuming. To improve the workflow, we implemented an automated reCT evaluation, and assessed if automatic target contour propagation would lead to the same clinical decision for plan adaptation as the manual workflow. Materials and methods: This study included 79 consecutive patients with a total of 250 reCTs which had been manually evaluated. To assess the feasibility of automated reCT evaluation, we propagated the clinical target volumes (CTVs) deformably from the planning-CT to the reCTs in a commercial treatment planning system. The dose-volume-histogram parameters were extracted for manually re-delineated (CTVmanual) and deformably mapped target contours (CTVauto). It was compared if CTVmanual and CTVauto both satisfied/failed the clinical constraints. Duration of the reCT workflows was also recorded. Results: In 92% (N = 229) of the reCTs correct flagging was obtained. Only 4% (N = 9) of the reCTs presented with false negatives (i.e., at least one clinical constraint failed for CTVmanual, but all constraints were satisfied for CTVauto), while 5% (N = 12) of the reCTs led to a false positive. Only for one false negative reCT a plan adaption was made in clinical practice, i.e., only one adaptation would have been missed, suggesting that automated reCT evaluation was possible. Clinical introduction hereof led to a time reduction of 49 h (from 65 to 16 h). Conclusion: Deformable target contour propagation was clinically acceptable. A script-based automatic reCT evaluation workflow has been introduced in routine clinical practice.