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SU‐E‐T‐750: Three Dimensional in Silico Study of Brachytherapy Application with In‐Situ Dose‐Painting Administered Via Gold‐Nanoparticle Eluters
Author(s) -
Sinha N,
Cifter G,
Ngwa W
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4925114
Subject(s) - brachytherapy , materials science , nanoparticle , finite element method , dosimetry , colloidal gold , biomedical engineering , multiphysics , nuclear medicine , radiation therapy , nanotechnology , radiology , medicine , physics , thermodynamics
Purpose: Brachytherapy Application with in‐situ Dose‐painting Administered via Gold‐Nanoparticle Eluters (BANDAGE) has been proposed as a new therapeutic strategy for radiation boosting of high‐risk prostate tumor subvolume while minimizing dose to neighboring organs‐at‐risk. In a previous study the one‐dimensional dose‐painting with gold nanoparticles (GNP) released from GNP‐loaded brachytherapy spacers was investigated. The current study investigates BANDAGE in three‐dimensions. Methods: To simulate GNPs transport in prostrate tumors, a three dimensional, cylindrically symmetric transport model was generated using a finite element method (FEM). A mathematical model of Gold nanoparticle (GNPs) transport provides a useful strategy to optimize potential treatment planning for BANDAGE. Here, treatment of tumors with a radius of 2.5 cm was simulated in 3‐D. This simulation phase considered one gold based cylindrical spacer (GBS of size 5mm × 0.8 mm) introduced at the center of the spherical tumor with initial concentration of 100 mg/g or 508 mol/m3 of GNP. Finite element mesh is used to stimulate the GNP transport. Gold concentrations within the tumor were obtained using a 3‐D FEM solution implemented by COMSOL. Results: The analysis shows the spread of the GNPs through‐out the tumor with the increase of concentration towards the periphery with time. The analysis also shows the concentration profiles and corresponding dose enhancement factors (dose boost factor) as a function of GNP size. Conclusion: This study demonstrates the use of computational modeling and optimal parameter estimation to predict local GNPs from central implant as a function of x, y and z axis . Such a study provides a useful reference for ongoing translational studies for the BANDAGE approach