3 research outputs found
Planificaci贸n radioter谩pica de intensidad modulada basada en un modelo de simulaci贸n expl铆cita del transporte de part铆culas mediante optimizaci贸n por im谩gen m茅dica
Falta resumen y palabras claveIntroducci贸n: La planificaci贸n radioter谩pica m谩s precisa es la basada en un c谩lculo del transporte expl铆cito del haz de part铆culas, desde su generaci贸n en la cabeza del acelerador lineal, y en su interacci贸n con los modificadores y colimadores, hasta la deposici贸n de su energ铆a en los tejidos del paciente con densidades heterog茅neas. No obstante, este c谩lculo exige un tiempo de computaci贸n inviable para la pr谩ctica cl铆nica diaria. En este trabajo se presenta un modelo de optimizaci贸n de abertura directa que est谩 exclusivamente basado en los datos de la imagen del paciente, y que se implementa en un sistema propio de planificaci贸n de tratamientos Monte Carlo (MCTPS), con objeto de resolver tratamientos de radioterapia complejos con resultados 贸ptimos y en tiempos eficientes para ser adaptado a la pr谩ctica cl铆nica.
M茅todo: El sistema de planificaci贸n es un sistema full Monte Carlo (fMC), controlado mediante una interfaz de Matlab庐, que est谩 basado en la generaci贸n de matrices, que conforman un mapa denominado biof铆sico, el cual es generado a partir de los datos de la imagen del paciente para conseguir un juego de segmentos realizable 贸ptimo. En orden a reducir los tiempos de computaci贸n necesarios, el mapa de fluencia convencional ha sido sustituido por el conjunto de mapas biof铆sicos, el cual es secuenciado para proporcionar las aberturas que posteriormente ser谩n pesadas mediante un algoritmo de optimizaci贸n basado en un modelo de programaci贸n lineal, que permite optimizar la distribuci贸n de dosis al nivel del v贸xel. Un algoritmo de ray-casting extrae del CT del paciente la informaci贸n de las estructuras de inter茅s, el espesor atravesado, as铆 como los valores PET, si los hay. Los datos son guardados para generar los mapas biof铆sicos en cada incidencia. Estos mapas son los ficheros inputs de un secuenciador propio desarrollado para este fin. Se simularon espacios de fase para distintos aceleradores (Primus de Siemens y Axesse de Elekta) para varias energ铆as (6, 9, 12, 15 MeVy 6 MV). Los espacios de fase fueron simulados con el c贸digo EGSnrc/BEAMnrc. El c谩lculo de dosis en el paciente fue simulado con el c贸digo BEAMDOSE. Este c贸digo es una versi贸n modificada de EGSnrc/DOSXYZnrc capaz de calcular la dosis sobre cada v贸xel debido a cada segmento, y as铆 estar en disposici贸n de combinarlos con diferentes pesos durante el proceso de optimizaci贸n.
Resultados: Se han estudiado casos complejos con distintas caracter铆sticas, para chequear el algoritmo de planificaci贸n en situaciones en las que el c谩lculo MC ofrece un valor a帽adido: Un caso de cabeza y cuello (Caso I) con tres blancos delineados a partir de la imagen PET/CT y con un escalado de dosis exigente; un caso de mama parcial (Caso II) para ser resuelto con haces de electrones modulados (IMRT+MERT); y un caso de lecho prost谩tico (Caso III) con una geometr铆a c贸ncava acusada. En estos tres casos, las dosis de prescripci贸n y l铆mites en los 贸rganos de riesgo fueron satisfactorias en un tiempo lo suficientemente corto como para permitir implementarlo en la rutina cl铆nica. Estas soluciones te贸ricas fueron verificadas experimentalmente con 茅xito.
Conclusiones: Se ha desarrollado un modelo de planificaci贸n de tratamiento Monte Carlo basado exclusivamente en mapas dise帽ados a partir de la imagen del paciente. La secuenciaci贸n de estos mapas permite obtener aberturas realizables las cuales son moduladas mediante una formulaci贸n de programaci贸n lineal, permitiendo una optimizaci贸n de la dosis al nivel del v贸xel. El modelo es capaz de resolver casos complejos de radioterapia con una gran precisi贸n y empleando tiempos de computaci贸n asumibles para la aplicaci贸n cl铆nica
Accurate,robust and harmonized implementation of morpho-functional imaging in treatment planning for personalized radiotherapy
In this work we present a methodology able to use harmonized PET/CT imaging in dose painting by number (DPBN) approach by means of a robust and accurate treatment planning system. Image processing and treatment planning were performed by using a Matlab-based platform, called CARMEN, in which a full Monte Carlo simulation is included. Linear programming formulation was developed for a voxel-by-voxel robust optimization and a specific direct aperture optimization was designed for an efficient adaptive radiotherapy implementation. DPBN approach with our methodology was tested to reduce the uncertainties associated with both, the absolute value and the relative value of the information in the functional image. For the same H&N case, a single robust treatment was planned for dose prescription maps corresponding to standardized uptake value distributions from two different image reconstruction protocols: One to fulfill EARL accreditation for harmonization of [18F]FDG PET/CT image, and the other one to use the highest available spatial resolution. Also, a robust treatment was planned to fulfill dose prescription maps corresponding to both approaches, the dose painting by contour based on volumes and our voxel-by-voxel DPBN. Adaptive planning was also carried out to check the suitability of our proposal.
Different plans showed robustness to cover a range of scenarios for implementation of harmonizing strategies by using the highest available resolution. Also, robustness associated to discretization level of dose prescription according to the use of contours or numbers was achieved. All plans showed excellent quality index histogram and quality factors below 2%. Efficient solution for adaptive radiotherapy based directly on changes in functional image was obtained. We proved that by using voxel-by-voxel DPBN approach it is possible to overcome typical drawbacks linked to PET/CT images, providing to the clinical specialist confidence enough for routinely implementation of functional imaging for personalized radiotherapy.Junta de Andaluc铆a (FISEVI, reference project CTS 2482)European Regional Development Fund (FEDER
3D VMAT Verification Based on Monte Carlo Log File Simulation with Experimental Feedback from Film Dosimetry.
A model based on a specific phantom, called QuAArC, has been designed for the evaluation
of planning and verification systems of complex radiotherapy treatments, such as volumetric
modulated arc therapy (VMAT). This model uses the high accuracy provided by the Monte
Carlo (MC) simulation of log files and allows the experimental feedback from the high spatial
resolution of films hosted in QuAArC. This cylindrical phantom was specifically designed to
host films rolled at different radial distances able to take into account the entrance fluence
and the 3D dose distribution. Ionization chamber measurements are also included in the
feedback process for absolute dose considerations. In this way, automated MC simulation
of treatment log files is implemented to calculate the actual delivery geometries, while the
monitor units are experimentally adjusted to reconstruct the dose-volume histogram (DVH)
on the patient CT. Prostate and head and neck clinical cases, previously planned with
Monaco and Pinnacle treatment planning systems and verified with two different commercial
systems (Delta4 and COMPASS), were selected in order to test operational feasibility of the
proposed model. The proper operation of the feedback procedure was proved through the
achieved high agreement between reconstructed dose distributions and the film measure-
ments (global gamma passing rates > 90% for the 2%/2 mm criteria). The necessary discre-
tization level of the log file for dose calculation and the potential mismatching between
calculated control points and detection grid in the verification process were discussed.
Besides the effect of dose calculation accuracy of the analytic algorithm implemented in
treatment planning systems for a dynamic technique, it was discussed the importance of the
detection density level and its location in VMAT specific phantom to obtain a more reliable
DVH in the patient CT. The proposed model also showed enough robustness and efficiency
to be considered as a pre-treatment VMAT verification system.Ministerio de Ciencia y Tecnolog铆a SAF2011- 27116; IPT-2011-1480-900000