Your browser doesn't support javascript.
loading
A framework for in-field and out-of-field patient specific secondary cancer risk estimates from treatment plans using the TOPAS Monte Carlo system.
Meyer, Isaac; Peters, Nils; Tamborino, Giulia; Lee, Hoyeon; Bertolet, Alejandro; Faddegon, Bruce; Mille, Matthew M; Lee, Choonsik; Schuemann, Jan; Paganetti, Harald.
Afiliación
  • Meyer I; Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.
  • Peters N; Department of Radiation Oncology, Harvard Medical School, Boston, United States of America.
  • Tamborino G; Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.
  • Lee H; Department of Radiation Oncology, Harvard Medical School, Boston, United States of America.
  • Bertolet A; Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.
  • Faddegon B; Department of Radiation Oncology, Harvard Medical School, Boston, United States of America.
  • Mille MM; Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.
  • Lee C; Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.
  • Schuemann J; Department of Radiation Oncology, Harvard Medical School, Boston, United States of America.
  • Paganetti H; Department of Radiation Oncology, University of California San Francisco, San Francisco, United States of America.
Phys Med Biol ; 69(16)2024 Aug 06.
Article en En | MEDLINE | ID: mdl-39019051
ABSTRACT
Objective. To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework.Method. Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection's Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets.Result. The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk.Significance. This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Método de Montecarlo Límite: Humans Idioma: En Revista: Phys Med Biol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Método de Montecarlo Límite: Humans Idioma: En Revista: Phys Med Biol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos