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29 poster VIRTUAL PLANNING FOR IEORT: RADIANCE MAIN FEATURES AND RECENT IMPROVEMENTS
S ATURDAY, M AY 7, 2011
P OSTER DISCUSSION
S 15
29SRVWHU
30SRVWHU
VIRTUAL PLANNING FOR IEORT: RADIANCE MAIN FEATURES AND RECENT IMPROVEMENTS J. Pascau1 2 , J. A. Santos Miranda3 , C. González-San Segundo3 , F. Carlos4 , A. Ramos5 , R. M. Meirino6 , F. Calvo3 , M. Desco1 1 H OSPITAL G ENERAL U NIVERSITARIO G REGORIO M ARAÑÓN, Unidad de Medicina y Cirugía Experimental, Madrid, Spain 2 U NIVERSIDAD C ARLOS III DE M ADRID, Departamento de Ingeniería Biomédica y Aeroespacial, Madrid, Spain 3 H OSPITAL G ENERAL U NIVERSITARIO G REGORIO M ARAÑÓN, Oncología, Madrid, Spain 4 C ONSORCIO H OSPITALARIO P ROVINCIAL DE C ASTELLÓN, Oncología , Castelló de la Plana, Spain 5 H OSPITAL U NIVERSITARIO R AMÓN Y C AJAL, Oncología, Madrid, Spain 6 C LINICA L A L UZ, Oncología, Madrid, Spain
AN INTRA-OPERATIVE RADIOTHERAPY ACCELERATOR COMMISSIONING TOOL BASED ON MONTE CARLO SIMULATION G. Iaccarino1 , M. D’Andrea1 , M. Grusio2 , L. Bellesi1 , A. Soriani1 , G. Felici2 , A. Ciccotelli2 , M. Benassi1 , L. Strigari1 1 N ATIONAL C ANCER I NSTITUTE R EGINA E LENA, Laboratory of Medical Physics and Expert Systems, Rome, Italy 2 S ORDINA S. P.A., Saonara (PD), Italy
Purpose: The RADIANCE (GMV, Spain) treatment planning system allows IOERT patient-specific virtual surgical simulation and electron beam interaction. The current state of the project, including details on its clinical use, is presented in this work. Materials: Development of the system started as an industrial and academic initiative in 2007 (GMV, Hospital General Universitario "Gregorio Mara and Hospital Provincial de Castellpain). The tool allows planning IOERT interventions from CT studies of a patient. Other modalities can also be used as complementary information. The planning process is as follows: 1) segmentation, user can select several regions to be considered organs at risk, structures to be removed during surgery, high relapse risk areas, bolus or protections; 2) simulation of patient positioning during surgery, accomplished by rotating the CT image, allowing virtual definition of the surgical frame; 3) selection of applicator parameters (diameter and bevel angle), and position; 4) selection of treatment energy with calculation of Dose Volume Histograms (DVHs) for the different regions. The DVHs are generated from dose distributions measured on a water phantom, but can also be estimated by means of a specific implementation of the Pencil Beam (PB) algorithm. This allows estimating the real interaction between radiation beam and patient anatomy or other objects. The pre-planning process includes interaction with the surgeons, who can indicate the expected surgical access and high risk areas in order to incorporate this information. Results: 41 patients have been evaluated, 33 retrospective and 8 prospective. The tumor types were: rectal and colon cancer (19), recurrences (6), sarcomas (8), breast cancer (5), pancreatic cancer (2) and chordoma (1). Clinical testing has proved feasibility of a) pre-tailoring IOERT target definition in agreement with surgical and radiotherapeutical individualized criteria; b) intra-surgically guided selection and optimization of pre-planning estimated parameters; c) post-planning definitive registration of the actual performed procedure for documentation and record. The system has proved the ability to integrate both radiotherapists and surgeons in the simulation and planning process. The stability of the current development has allowed the installation and clinical use of radiance systems in four hospitals in Spain (Hospital General Universitario "Gregorio Mara, Clca La Luz, Hospital Provincial de Castellospital Ramajal). These centers are now collaborating in establishing new protocols for IOERT that involve simulation and planning with the presented tool.
Purpose: The commissioning of a IORT accelerator requires measurements of depth dose, off-axis dose profiles and output factors for each energy and applicator type. In particular the most recent model of the Light Intraoperative ACcelerator (LIAC, SORDINA, Italy) has 4 energies (6, 8, 10 and 12 MeV) and a set of 28 applicators: 7 different diameters (3, 4, 5, 6, 7, 8 and 10 cm) X 4 different beveling angles (0◦ , 15◦ , 30◦ and 45◦ ). This means that the LIAC commissioning needs more than one hundred measurements. Aim of this work is to develop a tool that helps the medical physicist in the commissioning of a IORT accelerator generating all the necessary data from a minimal set of basic measurements. Materials: The tool has been developed in MatlabTM . It allows to store the experimental percentage depth doses (PDDs) and off-axis profiles (OAPs) of two mandatory irradiation setups: LIAC with the flat 10 cm applicator and without any applicator. Starting from these data the tool calculates the dose distributions in water for all the other applicators (both flat and bevelled). This is done using a database that had been previously created, which contains the pre-calculated simulated dose distributions of all the applicators for monoenergetic energies ranging from 3.5 to 15.0 MeV with a step of 0.1 MeV. The Monte Carlo codes BEAMnrc and EGSnrc were used to simulate the particle transport in the LIAC geometry and to calculate the dose in water, respectively. The simulated annealing optimization algorithm was used to find the weights of the monoenergetic PDDs that minimize the objective function given by the sum of the squared differences between calculated and measured PDDs at each depth. The weights obtained from the optimization are used as input to calculate the 3D distributions and the output factors of the other flat/beveled applicators. Results: The figure shows a step of the optimization process to find the spectrum for a nominal energy of 12 MeV. The software has been tested in the commissioning of 3 LIACs. For all energies and applicators, the differences between calculated and experimental depth doses are almost everywhere less than 2% (about 3% only around the depth of practical range). Likewise, the distance to agreement between the calculated and experimental off-axis profiles are almost everywhere less than 1 mm. The differences between calculated and experimental output factors are less than 2%, with the exception of the smallest applicator (3 cm diameter) for which the difference is between 3 and 4%.
Conclusions: The software is easy to use and useful to check the experimental data from various LIAC, supporting the medical physicist in the commissioning phase reducing the workload and improving accuracy. Noteworthy the dose distribution generated by this tool can be used as input (i.e. look-up table) for a treatment planning system.
Conclusions: This virtual pre-intra-post planning system reproduces the real radiosurgical process involved in IOERT, and includes now real dose modeling. Predictability of IOERT treatment decision process (including surgical and radiation treatment outcomes) is possible with this version of radiance. The multi-site collaboration will result in new guidelines for IOERT planning with this new approach. Project funded by Spanish Ministry of Science and Innovation (PI09/90568, PSE-300000-2009-5, IPT-300000-2010-3, Comunidad de Madrid ARTEMIS S2009/DPI-1802 and FEDER founds).
P OSTER DISCUSSION
S 15
29SRVWHU
30SRVWHU
VIRTUAL PLANNING FOR IEORT: RADIANCE MAIN FEATURES AND RECENT IMPROVEMENTS J. Pascau1 2 , J. A. Santos Miranda3 , C. González-San Segundo3 , F. Carlos4 , A. Ramos5 , R. M. Meirino6 , F. Calvo3 , M. Desco1 1 H OSPITAL G ENERAL U NIVERSITARIO G REGORIO M ARAÑÓN, Unidad de Medicina y Cirugía Experimental, Madrid, Spain 2 U NIVERSIDAD C ARLOS III DE M ADRID, Departamento de Ingeniería Biomédica y Aeroespacial, Madrid, Spain 3 H OSPITAL G ENERAL U NIVERSITARIO G REGORIO M ARAÑÓN, Oncología, Madrid, Spain 4 C ONSORCIO H OSPITALARIO P ROVINCIAL DE C ASTELLÓN, Oncología , Castelló de la Plana, Spain 5 H OSPITAL U NIVERSITARIO R AMÓN Y C AJAL, Oncología, Madrid, Spain 6 C LINICA L A L UZ, Oncología, Madrid, Spain
AN INTRA-OPERATIVE RADIOTHERAPY ACCELERATOR COMMISSIONING TOOL BASED ON MONTE CARLO SIMULATION G. Iaccarino1 , M. D’Andrea1 , M. Grusio2 , L. Bellesi1 , A. Soriani1 , G. Felici2 , A. Ciccotelli2 , M. Benassi1 , L. Strigari1 1 N ATIONAL C ANCER I NSTITUTE R EGINA E LENA, Laboratory of Medical Physics and Expert Systems, Rome, Italy 2 S ORDINA S. P.A., Saonara (PD), Italy
Purpose: The RADIANCE (GMV, Spain) treatment planning system allows IOERT patient-specific virtual surgical simulation and electron beam interaction. The current state of the project, including details on its clinical use, is presented in this work. Materials: Development of the system started as an industrial and academic initiative in 2007 (GMV, Hospital General Universitario "Gregorio Mara and Hospital Provincial de Castellpain). The tool allows planning IOERT interventions from CT studies of a patient. Other modalities can also be used as complementary information. The planning process is as follows: 1) segmentation, user can select several regions to be considered organs at risk, structures to be removed during surgery, high relapse risk areas, bolus or protections; 2) simulation of patient positioning during surgery, accomplished by rotating the CT image, allowing virtual definition of the surgical frame; 3) selection of applicator parameters (diameter and bevel angle), and position; 4) selection of treatment energy with calculation of Dose Volume Histograms (DVHs) for the different regions. The DVHs are generated from dose distributions measured on a water phantom, but can also be estimated by means of a specific implementation of the Pencil Beam (PB) algorithm. This allows estimating the real interaction between radiation beam and patient anatomy or other objects. The pre-planning process includes interaction with the surgeons, who can indicate the expected surgical access and high risk areas in order to incorporate this information. Results: 41 patients have been evaluated, 33 retrospective and 8 prospective. The tumor types were: rectal and colon cancer (19), recurrences (6), sarcomas (8), breast cancer (5), pancreatic cancer (2) and chordoma (1). Clinical testing has proved feasibility of a) pre-tailoring IOERT target definition in agreement with surgical and radiotherapeutical individualized criteria; b) intra-surgically guided selection and optimization of pre-planning estimated parameters; c) post-planning definitive registration of the actual performed procedure for documentation and record. The system has proved the ability to integrate both radiotherapists and surgeons in the simulation and planning process. The stability of the current development has allowed the installation and clinical use of radiance systems in four hospitals in Spain (Hospital General Universitario "Gregorio Mara, Clca La Luz, Hospital Provincial de Castellospital Ramajal). These centers are now collaborating in establishing new protocols for IOERT that involve simulation and planning with the presented tool.
Purpose: The commissioning of a IORT accelerator requires measurements of depth dose, off-axis dose profiles and output factors for each energy and applicator type. In particular the most recent model of the Light Intraoperative ACcelerator (LIAC, SORDINA, Italy) has 4 energies (6, 8, 10 and 12 MeV) and a set of 28 applicators: 7 different diameters (3, 4, 5, 6, 7, 8 and 10 cm) X 4 different beveling angles (0◦ , 15◦ , 30◦ and 45◦ ). This means that the LIAC commissioning needs more than one hundred measurements. Aim of this work is to develop a tool that helps the medical physicist in the commissioning of a IORT accelerator generating all the necessary data from a minimal set of basic measurements. Materials: The tool has been developed in MatlabTM . It allows to store the experimental percentage depth doses (PDDs) and off-axis profiles (OAPs) of two mandatory irradiation setups: LIAC with the flat 10 cm applicator and without any applicator. Starting from these data the tool calculates the dose distributions in water for all the other applicators (both flat and bevelled). This is done using a database that had been previously created, which contains the pre-calculated simulated dose distributions of all the applicators for monoenergetic energies ranging from 3.5 to 15.0 MeV with a step of 0.1 MeV. The Monte Carlo codes BEAMnrc and EGSnrc were used to simulate the particle transport in the LIAC geometry and to calculate the dose in water, respectively. The simulated annealing optimization algorithm was used to find the weights of the monoenergetic PDDs that minimize the objective function given by the sum of the squared differences between calculated and measured PDDs at each depth. The weights obtained from the optimization are used as input to calculate the 3D distributions and the output factors of the other flat/beveled applicators. Results: The figure shows a step of the optimization process to find the spectrum for a nominal energy of 12 MeV. The software has been tested in the commissioning of 3 LIACs. For all energies and applicators, the differences between calculated and experimental depth doses are almost everywhere less than 2% (about 3% only around the depth of practical range). Likewise, the distance to agreement between the calculated and experimental off-axis profiles are almost everywhere less than 1 mm. The differences between calculated and experimental output factors are less than 2%, with the exception of the smallest applicator (3 cm diameter) for which the difference is between 3 and 4%.
Conclusions: The software is easy to use and useful to check the experimental data from various LIAC, supporting the medical physicist in the commissioning phase reducing the workload and improving accuracy. Noteworthy the dose distribution generated by this tool can be used as input (i.e. look-up table) for a treatment planning system.
Conclusions: This virtual pre-intra-post planning system reproduces the real radiosurgical process involved in IOERT, and includes now real dose modeling. Predictability of IOERT treatment decision process (including surgical and radiation treatment outcomes) is possible with this version of radiance. The multi-site collaboration will result in new guidelines for IOERT planning with this new approach. Project funded by Spanish Ministry of Science and Innovation (PI09/90568, PSE-300000-2009-5, IPT-300000-2010-3, Comunidad de Madrid ARTEMIS S2009/DPI-1802 and FEDER founds).