Commercial Planning System Research Articles

Feasibility of contrail avoidance in a commercial flight planning system: an operational analysis

Aircraft condensation trails, also known as contrails, contribute a substantial portion of aviation’s overall climate footprint. Contrail impacts can be reduced through smart flight planning that avoids contrail-forming regions of the atmosphere. While previous studies have explored the operational impacts of contrail avoidance in simulated environments, this paper aims to characterize the feasibility and cost of contrail avoidance precisely within a commercial flight planning system. This study leverages the commercial Flightkeys 5D algorithm, developed by Flightkeys GmbH, with a prototypical contrail forecast model based on the Contrail Cirrus Prediction (CoCiP) model to simulate contrail avoidance on 49 411 flights during the first two weeks of June 2023, and 35 429 flights during the first two weeks of January 2024. The utilization of a commercial flight planning system enables high-accuracy estimates of additional cost and fuel investments by operators to achieve estimated reductions in contrail-energy forcing and overall flight global warming potential. The results show that navigational contrail avoidance will require minimal additional cost (0.08%) and fuel (0.11%) investments to achieve notable reductions in contrail climate forcing (−73.0%). This simulation provides evidence that contrail mitigation entails very low operational risks, even regarding fuel. This study aims to serve as an incentive for operators and air traffic controllers to initiate contrail mitigation testing as soon as possible and begin reducing aviation’s non- CO2 emissions.

Clinical Evaluation of an Automated Iterative Optimization System for Radiation Oncology

Automation of radiotherapy treatment planning improves efficiency and consistency, while reducing planning time and errors. The objective of this study was to validate an Iterative Optimization Engine (IOE) within an existing automated IMRT/VMAT planning framework. The IOE was designed to reduce remaining manual intervention within the automation framework through measuring and codifying common user intervention within a commercial planning system. The IOE was developed for external beam IMRT/VMAT treatment planning on the Monaco Treatment Planning System. The IOE was built on an existing automation framework, utilizing the Application Programming Interface (API) to create completely automated treatment plans. A network of 40 centers in Australia evaluated automated treatment plans for head and neck disease sites where users decided manual intervention was required post automated planning to achieve clinician approval. The modifications to automated plans were recorded, analyzed, and codified into the API to remove the requirement for manual intervention. A subset of the automated plans was then retrospectively processed by the IOE with resulting plans being scored in three categories of 1) superior, 2) equivalent and 3) inferior based on DVH assessment with the original clinician approved plan as the baseline. The automation framework generated 546 head and neck plans from January 1 to February 1, 2023, of which 45% required manual intervention to achieve dosimetric criteria. After being processed by the IOE, 86% of plans showed equivalent or superior coverage and maximum dose, and 95% of plans demonstrated equivalent homogeneity or improved homogeneity. Multi-target plans showed equivalent or improved target dose for 67% of intermediate dose targets and 39% of low dose targets when multiple targets were treated simultaneously. Analysis of organs at risk showed 38% of plans with reduced Parotid mean dose, 92% improved Larynx mean dose, 43% reduced Spinal Cord maximum dose, 57% decreased Brainstem maximum dose, 85% reduced Oral Cavity mean dose and 56% reduced Pharynx mean dose. The addition of an IOE achieved a clinical improvement to target and OAR metrics in the assessed clinical plans. The automation framework will incorporate this work into clinical production to improve the overall effectiveness of the automated planning framework.

Auto Assistant VMAT Planning with HID Automation

To develop a complete, robust, adaptable and fully customizable software interface for assisting treatment planning procedures on FDA approved commercial system. This will standardize treatment planning process and provide opening interface to other third-party clinical software packages, and introduce AI inference to optimize plan without breaking current clinical planning workflow. Based on our clinical planning workflow, Varian Eclipse TPS were used. The general HID interface AUTOFLOW was developed with scripting language AutoIt and includes optical character reorganization (OCR) ability. The AUTOFLOW is fully customizable and adaptable for different VMAT planning process. The planning workflow and objective constraints template defined by Northwell health, CFAM are applied. AUTOFLOW operates automatically 3 standard planning interfaces (contouring, external beam planning and optimization) of Eclipse based on information in action tables. The information in the tables, such as auxiliary structures, field set up and initial optimization parameters, can be preset according to the plan template or from other 3rd party packages. Based on Northwell CFAM clinical planning protocol, the planning starts from post-contour approval. AUTOFLOW operates Eclipse to create auxiliary structures, set up planning fields then initiate plan optimization. During the optimization, the AUTOFLOW fills the constraint parameters and monitor the objective goals achievement by OCR. The updated parameters are introduced with our developing machine learning package. The whole planning process were assisted by AUTOFLOW automatically, while the planner can intercept the planning process as need. The general interface, AUTOFLOW was developed and applied to automatically assist the VMAT procedure in prostate cases. For each prostate case, more than 213 human HID operations on computers were removed from the plan procedure in our CFAM planning protocol. 12 prostate cases without manual interception were tested. The interface succeeds to reducing the VMAT planning time and planner still own the planning control. The AUTOFLOW software interface can be used to perform VMAT planning in current commercial clinical planning system. It can automatically assist planner operation and provide standard interface to 3rd party software packages. The future works will focus on building a cohesive UI, reducing the time further by improving the prediction of optimization parameters and other treatment sites.

Implementation of automated personalised breast radiotherapy planning techniques with scripting in Raystation.

Implement scripted automatic breast planning (AP) for breast techniques within Raystation. Manual plans (MPs) were re-planned and compared with AP plans for whole breast (WB), partial breast (PB), hybrid volumetric modulated arc therapy simultaneous integrated boost (VMAT SIB) and VMAT nodal plans. WB AP plans took 7 min comparing well to MP. One WB AP failed a mandatory dose constraint. Small statistically significant differences showed improved coverage for AP at expense of slightly hotter plans, however absolute differences were small (mean differences < 1% or D 0.5cc<0.2 Gy). PB AP plans took 9 min, showing improved coverage (V 24.7Gy97.6 vs 96.4 %). One PB AP case failed a mandatory constraint. Other dosimetric differences were non-significant. SIB AP plans took 14 min with one case failing a mandatory constraint with minor differences compared with MP except larger V 42.8Gy (3 vs 1.5 %) and more MU. VMAT AP plans took 12 min and were hotter for PTVp_4000 but had higher nodal coverage. Contra_Lung V 2.5Gy was higher (8.8 %) than MP plans (6.5 %). Automatic planning of modern breast techniques has been successfully introduced using a commercial planning system. AP plans are very similar to MP, requiring little manual interaction for most cases with significant timesaving potential. Scripted breast plans produced within minutes for WB, PB, SIB and VMAT. Successfully introduced into large busy department. Plans similar to manual plans, requiring little manual interaction.

Clinical Evaluation of an Automated Treatment Planning Framework for Radiation Oncology

<h3>Purpose/Objective(s)</h3> Automation of radiotherapy treatment planning increases consistency, provides a safety net around error prevention, and reduces planning time. The objective of this study was to validate a scalable framework to automate the creation of VMAT and IMRT treatment plans using commercial planning systems. <h3>Materials/Methods</h3> A total of 35 centers across Australia were used for the study and the disease sites consisted of Urinogenital, Lung, Breast, Head and Neck, Neurological, GI and Gynecological. A scalable framework for external beam treatment planning was implemented for two commercial treatment planning systems (TPS), Eclipse (Varian Medical Systems, Palo Alto, CA) and Monaco (Elekta AB, Stockholm, Sweden). The framework received CT images, target volumes, normal tissue structures, and prescription data from dosimetrists. Information was parsed into the system, validated against configuration settings, the desired treatment protocol template selected, optimization parameters adjusted, and dose calculation completed. The framework controlled the TPS through the Application Programming Interface (API). The dosimetry team evaluated each automated plan by comparison of the plan metrics to the prescription and assessment of the dose distribution. The plans were scored in three areas: 1) clinician approved with no intervention, 2) minimal intervention with minor adjustments, and 3) manual replanning. <h3>Results</h3> Since Aug. 2021, 4972 plans (36% of total plans) have been successfully processed across 35 treatment centers with 111 clinicians. 487 plans were rejected by the framework due to error. The system automated plans for GUI (1822), Lung (629), Breast (745), Head and Neck (65), Neurological (96), GI (568) and Gynecological (163). Out of these plans, 23% were clinician approved with no user intervention, 41% required minimal intervention to achieve clinician approval, and 36% required additional optimization structures and/or cycles of optimization to achieve clinician approval. The average time between clinician target volume delineation and plan approval reduced by 25% from 1.6 to 1.2 days. In Feb. 2022, the framework successfully processed 970 plans (41% of total plans), rejecting 126 (5%) due to error. Evaluation between systems showed 27% of Eclipse plans and 43% of Monaco plans were processed successfully. Of these plans, 19% (Eclipse) and 23% (Monaco) required no intervention while 25% (Eclipse) and 46% (Monaco) required minimal intervention. Analysis of dosimetrist productivity showed an increase of 16% since Aug. 2021 while the average time saved per plan was 85 minutes. Analysis of adverse and near- miss dosimetry related events showed a 6% reduction in reported incidents. <h3>Conclusion</h3> The framework for automated planning achieved a 60% clinician approval rate for plans with minimal or no intervention. Automation can result in more consistent planning and timesaving's for expert operators. A 6% reduction in recorded dosimetry related errors was achieved.

Monte Carlo modeling of the Elekta Versa HD and patient dose calculation with EGSnrc/BEAMnrc.

IntroductionNumerous studies have proven the Monte Carlo method to be an accurate means of dose calculation. Although there are several commercial Monte Carlo treatment planning systems (TPSs), some clinics may not have access to these resources. We present a method for routine, independent patient dose calculations from treatment plans generated in a commercial TPS with our own Monte Carlo model using free, open‐source software.Materials and methodsA model of the Elekta Versa HD linear accelerator was developed using the EGSnrc codes. A MATLAB script was created to take clinical patient plans and convert the DICOM RTP files into a format usable by EGSnrc. Ten patients’ treatment plans were exported from the Monaco TPS to be recalculated using EGSnrc. Treatment simulations were done in BEAMnrc, and doses were calculated using Source 21 in DOSXYZnrc. Results were compared to patient plans calculated in the Monaco TPS and evaluated in Verisoft with a gamma criterion of 3%/2 mm.ResultsOur Monte Carlo model was validated within 1%/1‐mm accuracy of measured percent depth doses and profiles. Gamma passing rates ranged from 82.1% to 99.8%, with 7 out of 10 plans having a gamma pass rate over 95%. Lung and prostate patients showed the best agreement with doses calculated in Monaco. All statistical uncertainties in DOSXYZnrc were less than 3.0%.ConclusionA Monte Carlo model for routine patient dose calculation was successfully developed and tested. This model allows users to directly recalculate DICOM RP files containing patients’ plans that have been exported from a commercial TPS.

Dosimetric Comparison of Various Spot Placement Techniques in Proton Pencil Beam Scanning.

PurposeTo present quantitative dosimetric evaluations of five proton pencil beam spot placement techniques.Materials and MethodsThe spot placement techniques that were investigated include two grid-based (rectilinear grid and hexagonal grid, both commonly available in commercial planning systems) and three boundary-contoured (concentric contours, hybrid, and optimized) techniques. Treatment plans were created for two different target volumes, one spherical and one conical. An optimal set of planning parameters was defined for all treatment plans and the impact of spot placement techniques on the plan quality was evaluated in terms of lateral/distal dose falloff, normal tissue sparing, conformity and homogeneity of dose distributions, as well as total number of spots used.ResultsThe results of this work highlight that for grid-based spot placement techniques, the dose conformity is dependent on target cross-sectional shape perpendicular to beam direction, which changes for each energy layer. This variable conformity problem is mitigated by using boundary contoured spot placement techniques. However, in the case of concentric contours, the conformity is improved but at the cost of decreased homogeneity inside the target. Hybrid and optimized spot placement techniques, which use contoured spots at the boundary and gridlike interior spot patterns, provide more uniform dose distributions inside the target volume while maintaining the improved dose conformity. The optimized spot placement technique improved target coverage, homogeneity of dose, and minimal number of spots. The dependence of these results on spot size is also presented for both target shapes.ConclusionThis work illustrates that boundary-contoured spot placement techniques offer marked improvement in dosimetry metrics when compared to commercially available grid-based techniques for a range of proton scanned beam spot sizes.

Effects of Mechanical Performance on Deliverability and Dose Distribution by Comparing Multi Institutions' Knowledge-based Models for Prostate Cancer in Volumetric Modulated Arc Therapy.

The aim of this study was to evaluate the mechanical performance and the effect on dose distribution and deliverability of volumetric modulated arc therapy (VMAT) plans for prostate cancer created with the commercial knowledge-based planning (KBP) system (RapidPlan™). Three institutions, A, B, and C were enrolled in this study. Each institution established and trained a KBP model with their own cases. CT data and structures for 45 patients at institution B were utilized to validate the dose-volume parameters (D2(%), D95(%), and D98(%) for target, and V50(%), V75(%), and V90(%) for rectum and bladder), and the following mechanical performance parameters and gamma passing rates of each KBP model: leaf sequence variability (LSV), aperture area variability (AAV), total monitor unit (MU), modulation complexity score for VMAT (MCSv), MU/control point (CP), aperture area (AA)/CP, and MU×AA/CP. Significant differences (p<0.01) in dosimetric parameters such as D2 and D98 for target and V50, V75, and V90 for bladder were observed among the three institutions. The means and standard deviations of MCSv were 0.31±0.03, 0.29±0.02, and 0.32±0.03, and the angles of maximum and minimum MU×AA/CP were 269° and 13°, 269° and 13°, and 273° and 153° at institutions A, B, and C, respectively. The mean gamma passing rate (1%/1 mm.) was >95% for all cases in each institution. Dose distribution and mechanical performance significantly differed between the three models. Each KBP model had different dose distributions and mechanical performance but could create an acceptable plan for deliverability regardless of mechanical performance.

A Safe and Practical Cycle for Team-Based Development and Implementation of In-House Clinical Software

PurposeDue to a gap in published guidance, we describe our robust cycle of in-house clinical software development and implementation, which has been used for years to facilitate the safe treatment of all patients in our clinics. Methods and MaterialsOur software development and implementation cycle requires clarity in communication, clearly defined roles, thorough commissioning, and regular feedback. Cycle phases include design requirements and use cases, development, physics evaluation testing, clinical evaluation testing, and full clinical release. Software requirements, release notes, test suites, and a commissioning report are created and independently reviewed before clinical use. Software deemed to be high-risk, such as those that are writable to a database, incorporate the use of a formal, team-based hazard analysis. Incident learning is used to both guide initial development and improvements as well as to monitor the safe use of the software. ResultsOur standard process builds in transparency and establishes high expectations in the development and use of custom software to support patient care. Since moving to a commercial planning system platform in 2013, we have applied our team-based software release process to 16 programs related to scripting in the treatment planning system for the clinic. ConclusionsThe principles and methodology described here can be implemented in a range of practice settings regardless of whether or not dedicated resources are available for software development. In addition to teamwork with defined roles, documentation, and use of incident learning, we strongly recommend having a written policy on the process, using phased testing, and incorporating independent oversight and approval before use for patient care. This rigorous process ensures continuous monitoring for and mitigatation of any high risk hazards.

A detailed analysis of anatomical plausibility of crossed and uncrossed streamline rendition of the dentato-rubro-thalamic tract (DRT(T)) in a commercial stereotactic planning system

BackgroundAn increasing number of neurosurgeons use display of the dentato-rubro-thalamic tract (DRT) based on diffusion weighted imaging (dMRI) as basis for their routine planning of stimulation or lesioning approaches in stereotactic tremor surgery. An evaluation of the anatomical validity of the display of the DRT with respect to modern stereotactic planning systems and across different tracking environments has not been performed.MethodsDistinct dMRI and anatomical magnetic resonance imaging (MRI) data of high and low quality from 9 subjects were used. Six subjects had repeated MRI scans and therefore entered the analysis twice. Standardized DICOM structure templates for volume of interest definition were applied in native space for all investigations. For tracking BrainLab Elements (BrainLab, Munich, Germany), two tensor deterministic tracking (FT2), MRtrix IFOD2 (https://www.mrtrix.org), and a global tracking (GT) approach were used to compare the display of the uncrossed (DRTu) and crossed (DRTx) fiber structure after transformation into MNI space. The resulting streamlines were investigated for congruence, reproducibility, anatomical validity, and penetration of anatomical way point structures.ResultsIn general, the DRTu can be depicted with good quality (as judged by waypoints). FT2 (surgical) and GT (neuroscientific) show high congruence. While GT shows partly reproducible results for DRTx, the crossed pathway cannot be reliably reconstructed with the other (iFOD2 and FT2) algorithms.ConclusionSince a direct anatomical comparison is difficult in the individual subjects, we chose a comparison with two research tracking environments as the best possible “ground truth.” FT2 is useful especially because of its manual editing possibilities of cutting erroneous fibers on the single subject level. An uncertainty of 2 mm as mean displacement of DRTu is expectable and should be respected when using this approach for surgical planning. Tractographic renditions of the DRTx on the single subject level seem to be still illusive.

Dosimetric evaluation of the capabilities of two clinical treatment planning systems for prostate cancer

Treatment planning systems play a key role in radiotherapy. Various commercial planning systems are currently available on the market. These systems usually differ in the algorithms used for radiation dose calculation and vary in the manner of implementation of the same algorithms. They also differ in optimizer algorithms used in search of the best treatment plan required to meet the user specified criteria. In this study, we evaluate two optimization systems available from two commercial treatment planning systems. The two systems used in the study are the Eclipse Planning System (version 10.042, Varian Medical Systems, Palo Alto); and, Monaco Planning System (version 3.01, Elekta CMS Software, St. Louis, MO). Computed tomographic images for ten patients, previously planned using Eclipse, were randomly selected from our patient database. We generated treatment plans for the ten cases utilizing the Monaco system. Monaco utilizes a set of biological and DVH functions in the optimization process, while Eclipse uses only dose volume objectives. Planners would need to understand the difference between the two methodologies for getting better outcomes in radiation treatment planning for cancer patients. All generated plans in the study were evaluated based on dose volume histogram (DVH) and isodose distributions. The overall performance of dose volume optimization was better compared to the biological optimization. Dose volume optimization was more efficient and easier to manipulate for our prostate cases. The biological optimization process provided good quality plans. However, the optimizer requires improvement to become more efficient.

Does commercially available shoulder arthroplasty preoperative planning software agree with surgeon measurements of version, inclination, and subluxation?

Preoperative planning with commercially available imaging software in shoulder arthroplasty may allow for improved decision-making and more accurate placement of the glenoid component. A total of 81 consecutive shoulder computed tomographyscans obtained for preoperative planning purposes for shoulder arthroplasty were analyzed by commercially available software from 4 companies (Blueprint: Wright Medical, Memphis, TN, USA; GPS: Exactech, Gainesville, FL, USA; Materialise: DJO, Vista, CA, USA; and VIP: Arthrex, Naples, FL, USA)and by 5 fellowship-trained sports medicine/shoulder surgeons. Inclination, version, and subluxation of the humerus were measured in a blinded fashion on axial and coronal sequences at the mid-glenoid. Surgeon measurements were analyzed for agreementand were compared with the 4 commercial programs. Surgeon reliability was acceptable for version (intraclass correlation coefficient [ICC]: 0.876), inclination (ICC: 0.84), and subluxation (ICC: 0.523). Significant differences were found between surgeon and commercial software measurements in version (P = .03), inclination (P = .023), and subluxation (P < .001). Software measurements tended to be more superiorly inclined (average -2° to 2° greater), more retroverted (average 2°-5° greater), and more posteriorly subluxed (average 7°-10° greater) than surgeon measurements. In comparing imaging software measurements, only Blueprint was found to producesignificantly different version measurements than surgeon measurements (P = .02). Preoperative planning software for shoulder arthroplasty has limited agreement in measures of version, inclination, and subluxation measurements, whereas surgeons have high inter-reliability. Surgeons should be cautious when using commercial software planning systems and when comparing publications that use different planning systems to determine preoperative glenoid deformity measurements.

Clinical application and evaluation of automatic segmentation model based on deep learning for breast cancer radiotherapy

Objective In this study, the deep learning algorithm and the commercial planning system were integrated to establish and validate an automatic segmentation platform for clinical target volume (CTV) and organs at risk (OARs) in breast cancer patients. Methods A total of 400 patients with left and right breast cancer receiving radiotherapy after breast-conserving surgery in Cancer Hospital CAMS were enrolled in this study. A deep residual convolutional neural network was used to train CTV and OARs segmentation models. An end-to-end deep learning-based automatic segmentation platform (DLAS) was established. The accuracy of the DLAS platform delineation was verified using 42 left breast cancer and 40 right breast cancer patients. The overall Dice Similarity Coefficient (DSC) and the average Hausdorff Distance (AHD) were calculated. The relationship between the relative layer position and the DSC value of each layer (DSC_s) was calculated and analyzed layer-by-layer. Results The mean overall DSC and AHD of global CTV in left/right breast cancer patients were 0.87/0.88 and 9.38/8.71 mm. The average overall DSC and AHD range for all OARs in left/right breast cancer patients were ranged from 0.86 to 0.97 and 0.89 to 9.38 mm. The layer-by-layer analysis of CTV and OARs reached 0.90 or above, indicating that the doctors were only required to make slight or no modification, and the DSC_s ≥ 0.9 of CTV automatic delineation accounted for approximately 44.7% of the layers. The automatic delineation range for OARs was 50.9%-89.6%. For DSC_s< 0.7, the DSC_s values of CTV and the regions of interest other than the spinal cord were significantly decreased in the boundary regions on both sides (layer positions 0-0.2, and 0.8-1.0), and the level of decrease toward the edge was more pronounced. The spinal cord was delineated in a full-scale manner, and no significant decrease in DSC_s was observed in a particular area. Conclusions The end-to-end automatic segmentation platform based on deep learning can integrate the breast cancer segmentation model and achieve excellent automatic segmentation effect. In the boundary areas on both sides of the superior and inferior directions, the consistency of the delineation decreases more obviously, which needs to be further improved. Key words: Automatic segmentation; Deep learning; Breast neoplasm/radiotherapy

Dose-volume Histogram Analysis of Knowledge-based Volumetric-modulated Arc Therapy Planning in Postoperative Breast Cancer Irradiation.

We evaluated the dosimetric profiles of manually generated volumetric-modulated arc therapy (VMAT) plans and performance of a commercial knowledge-based planning system (KBP) in treating breast cancer. We defined the manually generated VMAT plan as the manual plan (MP). Twenty MPs were generated for left-sided breast cancer patients who underwent breast-conserving surgery and used to develop a KBP training set. The other five patients were used for validation. The dosimetric parameters among MPs, tangential irradiation plans (TPs), and KBP-VMAT plans (KBP-Ps) were compared. D95 and homogeneity of the planning target volume (PTV) were significantly higher and greater in MPs and KBP-Ps than in TPs. Lung V20, V40 The Dmean for the left anterior descending artery was lower in MPs and KBP-Ps than in TPs. KBP could save time in generating VMAT plans. MPs and KBP-Ps could ensure higher dose uniformity of PTV than TPs. KBP could faster generate comparable MPs for breast cancer.

Machine learning\u2014aided personalized DTI tractographic planning for deep brain stimulation of the superolateral medial forebrain bundle using HAMLET

BackgroundGrowing interest exists for superolateral medial forebrain bundle (slMFB) deep brain stimulation (DBS) in psychiatric disorders. The surgical approach warrants tractographic rendition. Commercial stereotactic planning systems use deterministic tractography which suffers from inherent limitations, is dependent on manual interaction (ROI definition), and has to be regarded as subjective. We aimed to develop an objective but patient-specific tracking of the slMFB which at the same time allows the use of a commercial surgical planning system in the context of deep brain stimulation.MethodsThe HAMLET (Hierarchical Harmonic Filters for Learning Tracts from Diffusion MRI) machine learning approach was introduced into the standardized workflow of slMFB DBS tractographic planning on the basis of patient-specific dMRI. Rendition of the slMFB with HAMLET serves as an objective comparison for the refinement of the deterministic tracking procedure. Our application focuses on the tractographic planning of DBS (N = 8) for major depression and OCD.ResultsPrevious results have shown that only fibers belonging to the ventral tegmental area to prefrontal/orbitofrontal axis should be targeted. With the proposed technique, the deterministic tracking approach, that serves as the surgical planning data, can be refined, over-sprouting fibers are eliminated, bundle thickness is reduced in the target region, and thereby probably a more accurate targeting is facilitated. The HAMLET-driven method is meant to achieve a more objective surgical fiber display of the slMFB with deterministic tractography.ConclusionsThe approach allows overlying the results of patient-specific planning from two different approaches (manual deterministic and machine learning HAMLET). HAMLET shows the slMFB as a volume and thus serves as an objective tracking corridor. It helps to refine results from deterministic tracking in the surgical workspace without interfering with any part of the standard software solution. We have now included this workflow in our daily clinical experimental work on slMFB DBS for psychiatric indications.

Landeignungsprüfung in prosperierenden Großstädten. Ein GIS-basiertes Entscheidungsunterstützungssystem für Unternehmensimmobilienentwicklungen in der Stadt Düsseldorf

Not only in Germany the attractiveness of large cities leads to a crowding out of corporate real estate in prosperous areas. This affects local communities since the settlement of corporate real estate often entails considerable external (utility) effects. Avoiding this crowding out serves as the origin for developing an innovative methodology for systematic land suitability assessment. Using the current German geodata-initiatives, we can merge for the first time existing geospatial data sets and geographic information systems on the basis of compromise programming into a multidimensional decision-support system for real estate and urban development in Germany. Applied to the city of Düsseldorf, we empirically verify the added value of this new methodology. Not only identifies the multidimensional and GIS-based land suitability assessment new and additional parcels for private investors and developers of corporate real estate. Moreover, the GIS-model visualizes spatial clusters of available industrial land, which might as proactive landscape protection areas prevent the future crowding out of corporate real estate. Thus, the methodology makes an important contribution to an empirically-based commercial planning system by supporting the interdisciplinary exchange between private and public actors in real estate and urban development.

Autonomous Treatment Plan Optimization Strategy Augmented By Using a Knowledge-Guided and Irregularly Downsampled Voxelization Scheme

Current IMRT/VMAT planning is tedious and labor intensive due to its involvement of manual trial-and-error adjustment of model parameters. Despite of intensive research devoted to autonomous treatment planning, a truly efficient and reliable approach in a clinical environment has yet to be developed. A major shortcoming of the existing approaches is their reliance of DVH domain for characterization of a treatment, which is degenerate and does not always provide sufficient guidance to the solution search process. the use of voxel domain, on the other hand, is hampered by the huge dimensionality and thus intractable computational efficiency. The purpose of the work is to mitigate the problem by implementing an autonomous planning strategy in a novel dose-anatomy guided downsampling voxel scheme and showcase the novel approach by planning several clinical head and neck and pancreatic VMAT treatments in a commercial planning system. A sparse voxelization scheme, referred to as the isodose-feature preserving voxelization (IFPV), introduced recently by our group for concise representation of a treatment plan, is used to represent prior knowledge and to facilitate the optimization. Briefly, anatomical and dosimetric information of a treatment plan is characterized by IFPV, which partitions the voxels into subgroups according to their geometric, anatomical and dosimetric features. For a given patient, the IFPV clusters are generated based on prior treatment reference plans with similar anatomy. A plan is then generated using a commercial treatment planning system (TPS) with its planning parameters initialized with the features of the clusters. API script programming is employed to interact with the TPS to implement autonomous plan evaluation and automated optimization parameter update. The procedure proceeds in an iterative fashion until reaching an acceptable tradeoff among target dose coverage/homogeneity and sparing of critical structures. In each iteration, the IFPV clusters are updated based on current dose distributions. Clinical cases with different sites are tested to demonstrate the proposed approach. Compared with the organ DVH-based approach, it is found that the optimization with IFPV voxelization is much easier to be guided toward the desired solution. This especially favors our autonomous planning approach and makes autonomous optimization more efficient. In addition, because of more effective use of both geometric and dose information during plan optimization, the IFPV voxelization-based inverse planning typically yields better treatment plans, as indicated by the testing clinical cases. This work presents the first implementation of IFPV voxelization into a commercial TPS platform for autonomous treatment planning. The algorithm developed here is directly translatable to widespread clinical used, thus the approach has the potential to significantly improve the radiation therapy workflow and patient care.

Development, commissioning, and evaluation of a new intensity modulated minibeam proton therapy system.

To invent, design, construct, and commission an intensity modulated minibeam proton therapy system (IMMPT) without the need for physical collimation and to compare its resulting conformity to a conventional IMPT system. A proton therapy system (Hitachi, Ltd, Hitachi City, Japan; Model: Probeat-V) was specially modified to produce scanned minibeams without collimation. We performed integral depth dose acquisitions and calibrations using a large diameter parallel-plate ionization chamber in a scanning water phantom (PTW, Freiburg, Germany; Models: Bragg Peak ionization chamber, MP3-P). Spot size and shape was measured using radiochromic film (Ashland Advanced Materials, Bridgewater NJ; Type: EBT3), and a synthetic diamond diode type scanned point by point in air (PTW Models: MicroDiamond, MP3-P). The measured data were used as inputs to generate a Monte Carlo-based model for a commercial radiotherapy planning system (TPS) (Varian Medical Systems, Inc., Palo Alto, CA; Model: Eclipse v13.7.15). The regular ProBeat-V system (sigma ~2.5mm) TPS model was available for comparison. A simulated base of skull case with small and medium targets proximal to brainstem was planned for both systems and compared. The spot sigma is determined to be 1.4mm at 221MeV at the isocenter and below 1mm at proximal distances. Integral depth doses were indistinguishable from the standard spot commissioning data. The TPS fit the spot profiles closely, giving a residual error maximum of 2.5% in the spot penumbra tails (below 5% of maximum) from the commissioned energies 69.4 to 221.3MeV. The resulting IMMPT plans were more conformal than the IMPT plans due to a sharper dose gradient (90-10%) 1.5mm smaller for the small target, and 1.3mm for the large target, at a representative central axial water equivalent depth of 7cm. We developed, implemented, and tested a new IMMPT system. The initial results look promising in cases where treatments can benefit from additional dose sparing to neighboring sensitive structures.

Evaluation of multiple institutions\u2019 models for knowledge-based planning of volumetric modulated arc therapy (VMAT) for prostate cancer

BackgroundThe aim of this study was to evaluate the performance of a commercial knowledge-based planning system, in volumetric modulated arc therapy for prostate cancer at multiple radiation therapy departments.MethodsIn each institute, > 20 cases were assessed. For the knowledge-based planning, the estimated dose (ED) based on geometric and dosimetric information of plans was generated in the model. Lower and upper limits of estimated dose were saved as dose volume histograms for each organ at risk. To verify whether the models performed correctly, KBP was compared with manual optimization planning in two cases. The relationships between the EDs in the models and the ratio of the OAR volumes overlapping volume with PTV to the whole organ volume (Voverlap/Vwhole) were investigated.ResultsThere were no significant dosimetric differences in OARs and PTV between manual optimization planning and knowledge-based planning. In knowledge-based planning, the difference in the volume ratio of receiving 90% and 50% of the prescribed dose (V90 and V50) between institutes were more than 5.0% and 10.0%, respectively. The calculated doses with knowledge-based planning were between the upper and lower limits of ED or slightly under the lower limit of ED. The relationships between the lower limit of ED and Voverlap/Vwhole were different among the models. In the V90 and V50 for the rectum, the maximum differences between the lower limit of ED among institutes were 8.2% and 53.5% when Voverlap/Vwhole for the rectum was 10%. In the V90 and V50 for the bladder, the maximum differences of the lower limit of ED among institutes were 15.1% and 33.1% when Voverlap/Vwhole for the bladder was 10%.ConclusionOrgans’ upper and lower limits of ED in the models correlated closely with the Voverlap/Vwhole. It is important to determine whether the models in KBP match a different institute’s plan design before the models can be shared.

Assessment of leakage dose in vivo in patients undergoing radiotherapy for breast cancer.

Background and purposeAccurate quantification of the relatively small radiation doses delivered to untargeted regions during breast irradiation in patients with breast cancer is of increasing clinical interest for the purpose of estimating long-term radiation-related risks. Out-of-field dose calculations from commercial planning systems however may be inaccurate which can impact estimates for long-term risks associated with treatment. This work compares calculated and measured dose out-of-field and explores the application of a correction for leakage radiation.Materials and methodsDose calculations of a Boltzmann transport equation solver, pencil beam-type, and superposition-type algorithms from a commercial treatment planning system (TPS) were compared with in vivo thermoluminescent dosimetry (TLD) measurements conducted out-of-field on the contralateral chest at points corresponding to the thyroid, axilla and contralateral breast of eleven patients undergoing tangential beam radiotherapy for breast cancer.ResultsOverall, the TPS was found to under-estimate doses at points distal to the radiation field edge with a modern linear Boltzmann transport equation solver providing the best estimates. Application of an additive correction for leakage (0.04% of central axis dose) improved correlation between the measured and calculated doses at points greater than 15 cm from the field edge.ConclusionsApplication of a correction for leakage doses within peripheral regions is feasible and could improve accuracy of TPS in estimating out-of-field doses in breast radiotherapy.