TU-A-BRB-06: Evolving and Optimizing IMRT Treatment Plans with PARETO - a Novel Treatment Planning System Based on a Multi-Objective Genetic Algorithm

2011 ◽  
Vol 38 (6Part27) ◽  
pp. 3740-3740
Author(s):  
J Fiege ◽  
P Potrebko ◽  
H Champion ◽  
A Cull ◽  
B McCurdy
Keyword(s):  
Genetic Algorithm ◽  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Multi Objective ◽  
Novel Treatment ◽  
Multi Objective Genetic Algorithm ◽  
Treatment Plans

scholarly journals Initial Validation of Proton Dose Calculations on SPR Images from DECT in Treatment Planning System

2020 ◽  
Vol 7 (2) ◽  
pp. 51-61
Author(s):  
Sina Mossahebi ◽  
Pouya Sabouri ◽  
Haijian Chen ◽  
Michelle Mundis ◽  
Matthew O'Neil ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Treatment Planning ◽  
Effective Atomic Number ◽  
Dose Calculation ◽  
Target Volume ◽  
Planning System ◽  
Treatment Planning System ◽  
Relative Electron ◽  
Treatment Plans ◽  
Proton Dose

Abstract Purpose To investigate and quantify the potential benefits associated with the use of stopping-power-ratio (SPR) images created from dual-energy computed tomography (DECT) images for proton dose calculation in a clinical proton treatment planning system (TPS). Materials and Methods The DECT and single-energy computed tomography (SECT) scans obtained for 26 plastic tissue surrogate plugs were placed individually in a tissue-equivalent plastic phantom. Relative-electron density (ρe) and effective atomic number (Zeff) images were reconstructed from the DECT scans and used to create an SPR image set for each plug. Next, the SPR for each plug was measured in a clinical proton beam for comparison of the calculated values in the SPR images. The SPR images and SECTs were then imported into a clinical TPS, and treatment plans were developed consisting of a single field delivering a 10 × 10 × 10-cm3 spread-out Bragg peak to a clinical target volume that contained the plugs. To verify the accuracy of the TPS dose calculated from the SPR images and SECTs, treatment plans were delivered to the phantom containing each plug, and comparisons of point-dose measurements and 2-dimensional γ-analysis were performed. Results For all 26 plugs considered in this study, SPR values for each plug from the SPR images were within 2% agreement with measurements. Additionally, treatment plans developed with the SPR images agreed with the measured point dose to within 2%, whereas a 3% agreement was observed for SECT-based plans. γ-Index pass rates were > 90% for all SECT plans and > 97% for all SPR image–based plans. Conclusion Treatment plans created in a TPS with SPR images obtained from DECT scans are accurate to within guidelines set for validation of clinical treatment plans at our center. The calculated doses from the SPR image–based treatment plans showed better agreement to measured doses than identical plans created with standard SECT scans.

Clinical experience using Delta 4 phantom for pretreatment patient-specific quality assurance in modern radiotherapy

2018 ◽  
Vol 18 (02) ◽  
pp. 210-214
Author(s):  
R. P. Srivastava ◽  
C. De Wagter
Keyword(s):  
Quality Assurance ◽  
Treatment Planning ◽  
Volumetric Modulated Arc Therapy ◽  
Planning System ◽  
Treatment Planning System ◽  
Patient Specific ◽  
Dose Distributions ◽  
Gamma Index ◽  
Calculated Dose ◽  
Treatment Plans

AbstractPurposeIn advanced radiotherapy techniques such as intensity-modulated radiation therapy (IMRT), the quality assurance (QA) process is essential. The aim of the study was to assure the treatment planning dose delivered during delivery of complex treatment plans. The QA standard is to perform patient-specific comparisons between planned doses and doses measured in a phantom.Materials and methodThe Delta 4 phantom (Scandidos, Uppsala, Sweden) has been used in this study. This device consists of diode matrices in two orthogonal planes inserted in a cylindrical acrylic phantom. Each diode is sampled per beam pulse so that the dose distribution can be evaluated on segment-by-segment, beam-by-beam, or as a composite plan from a single set of measurements. Ninety-five simple and complex radiotherapy treatment plans for different pathologies, planned using a treatment planning system (TPS) were delivered to the QA device. The planned and measured dose distributions were then compared and analysed. The gamma index was determined for different pathologies.ResultsThe evaluation was performed in terms of dose deviation, distance to agreement and gamma index passing rate. The measurements were in excellent agreement between with the calculated dose of the TPS and the QA device. Overall, good agreement was observed between measured and calculated doses in most cases with gamma values above 1 in >95% of measured points. Plan results for each test met the recommended dose goals.ConclusionThe delivery of IMRT and volumetric-modulated arc therapy (VMAT) plans was verified to correspond well with calculated dose distributions for different pathologies. We found the Delta 4 device is accurate and reproducible. Although Delta4 appears to be a straightforward device for measuring dose and allows measure in real-time dosimetry QA, it is a complex device and careful quality control is required before its use.

scholarly journals Plan Performance Using a Prototype Auto-Planning Workflow within a Novel Treatment Planning System

2019 ◽  
Vol 105 (1) ◽  
pp. E787
Author(s):  
L.E. Henke ◽  
J. Hilliard ◽  
R. Morris ◽  
C.G. Robinson ◽  
J.M. Michalski ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Novel Treatment

Clinical deployment of automatic treatment planning for pancreas SBRT patients.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 219-219
Author(s):  
Joseph A. Moore ◽  
Wuyang Yang ◽  
Kim Evans ◽  
Avani Satish Dholakia ◽  
Albert Koong ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Planning Time ◽  
Plan Optimization ◽  
Treatment Plans ◽  
The Relationship ◽  
Automatic Treatment ◽  
Quality Tool ◽  
Selection Of

219 Background: To clinically utilize an SQL relational database of prior treated patients to generate objectives for future treatment plans. A database approach allows for more rapid planning by starting with a better initial solution and improves safety by providing good known achievable dose values for the initial optimization. The use of a database allows for trending of dose, structure and toxicity data. Methods: A database of fifty-three patients from three institutions is populated with dose and structure data via an automatic script within the treatment planning system. For each new patient, overlap volume histograms (OVHs) are generated to describe the relationship between targets and critical structures. To aid in database consistency, a renaming interface is used which maps known alternative structure names to common names in the database. To ensure all required structures are present, the user is prompted with the names of missing structures. This interface allows selection of machine, energy and commonly used beam sets. The database is queried for all prior patients with the same or closer relationship between the target and each critical structure. The dose objectives reported are the lowest achievable dose from all patients as difficult or harder to plan as determined by OVH. Queried dose objectives are automatically loaded into the treatment planning system and optimized. A protocol quality tool is developed to quickly assess how well plans adhere to specified protocols. Results: Twenty-seven SBRT patients have been planned and clinically approved using the automatic planning tool and future patients continue to be added to the database. OVH computation required approximately 2 minutes, while typical plan optimization required 2.5 minutes. If auto-planned patients require even one fewer optimization to achieve an acceptable plan, total planning time is reduced. Safety is improved by reducing the number of protocol violations from 35% to 6% for one objective. Conclusions: Automatic treatment planning allows for rapid planning while reducing normal tissue dose to known achievable values. The continued addition of patients to the database allows for improvement of the automatically selected planning objectives.

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