SU-GG-I-90: Dose Distribution of Small Fields through MAGIC-F Gel Dosimetry and PENELOPE-Monte Carlo Simulation

Development and Application of MAGIC-f Gel in Cancer Research and Medical Imaging

“…are produced from different accelerators [34]. Alva et al showed the effectiveness of MAGIC-f gel by using small fields in the dosimetric calculation in conformal radiation therapy; this cancer treatment shapes the radiation beam to tally the tumor shape; the effectiveness of MAGIC-f gel is predicted by Monte Carlo simulation, using PENELOPE, and experimentally by irradiating a MAGIC-f gel in phantom of 12 cm diameter and 18 cm height with 9 fields of 6 MV photon beam, each one of 1 × 1 cm2 with a total dose of 16 Gy, and reading the result via MRI [86]. In another study by Alva et al, a comparison of the simulated and experimented dose distributions with the treatment planning system (TPS) gave the mean differences of 2.88% and 3.75%; these low percentages indicate that the response of the MAGIC-f polymeric gel could be suitable to use as a dosimeter in clinical procedures using small fields, especially in radiosurgery.…”

Frontiers in Radiation Oncology

“…The aim of this application is evaluate the response of MAGIC-f dosimeter, after being exposed to a conformal irradiation technique using a small field to compare the results with PENELOPE code through two dimensional dosimetric parameters [46].…”

“…It is instructive to mention that using differential equations and graphic approaches to study various dynamical and kinetic processes of biological systems can provide useful insights, as indicated by many previous studies on a series of important biological topics, such as enzyme-catalyzed reactions [18,40], low-frequency internal motions of biomacromolecules [41][42][43][44][45][46], protein folding kinetics [47,48], analysis of codon usage [49,50], base distribution in the anti-sense strands [51], hepatitis B viral infections [52], HBV virus gene missense mutation [53], GPCR type prediction [54], protein subcellular location prediction [55], and visual analysis of SARS-CoV [56,57].…”