The Monte Carlo technique and GafChromic films were employed to verify the accuracy of the dose planning system (Leksell GammaPlan) used in Gamma Knife (type B) radiosurgery when plugged collimator helmets were used. The EGS4 Monte Carlo code was used to calculate the dose distribution along the x, y, and z axes when a single shot was delivered at the center point (unit center point: x = 100, y = 100, z = 100) of a spherical polystyrene phantom, with gamma angle of 90 degrees. Two different sizes of the plugged collimator helmets, 4 and 18 mm, were studied. Two typical plugged patterns, 51 plugs and 99 plugs along the y direction, were examined. The results of our Monte Carlo trials showed good consistency with GammaPlan calculations and GafChromic film measurements. Furthermore, the Monte Carlo results showed that radiation leakage from the plugs was too small to affect the overall isodose curve distribution even when the heavily plugged pattern of up to 99 plugs was employed. The results of this project provide confidence to all Gamma Knife centers using the Leksell GammaPlan treatment planning system.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1118/1.598639 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Highly accurate real-space electron densities with neural networks.
J Chem Phys
January 2025
Microsoft Research AI for Science, 21 Station Road, Cambridge CB1 2FB, United Kingdom.
Variational ab initio methods in quantum chemistry stand out among other methods in providing direct access to the wave function. This allows, in principle, straightforward extraction of any other observable of interest, besides the energy, but, in practice, this extraction is often technically difficult and computationally impractical. Here, we consider the electron density as a central observable in quantum chemistry and introduce a novel method to obtain accurate densities from real-space many-electron wave functions by representing the density with a neural network that captures known asymptotic properties and is trained from the wave function by score matching and noise-contrastive estimation.
View Article and Find Full Text PDFPrecursor sticking coefficient determination from indented deposits fabricated by electron beam induced deposition.
Beilstein J Nanotechnol
January 2025
Physics Institute, Goethe University Frankfurt, Max-von-Laue-Str. 1, 60438 Frankfurt am Main, Germany.
A fast simulation approach for focused electron beam induced deposition (FEBID) numerically solves the diffusion-reaction equation (continuum model) of the precursor surface on the growing nanostructure in conjunction with a Monte Carlo simulation for electron transport in the growing deposit. An important requirement in this regard is to have access to a methodology that can be used to systematically determine the values for the set of precursor parameters needed for this model. In this work we introduce such a method to derive the precursor sticking coefficient as one member of the precursor parameter set.
View Article and Find Full Text PDFNon-linear enhancement of ultrafast X-ray diffraction through transient resonances.
Nat Commun
January 2025
SLAC National Accelerator Laboratory, Stanford PULSE Institute, Menlo Park, CA, USA.
Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI).
View Article and Find Full Text PDFCompetitive Adsorption of Small Molecule Inhibitors and Trimethylaluminum Precursors on the Cu(111) Surface during Area-Selective Atomic Layer Deposition: A GCMC Study.
Langmuir
January 2025
College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.
In area-selective atomic layer deposition (AS-ALD), small molecule inhibitors (SMIs) play a critical role in directing surface selectivity, preventing unwanted deposition on non-growth surfaces, and enabling precise thin-film formation essential for semiconductor and advanced manufacturing processes. This study utilizes grand canonical Monte Carlo (GCMC) simulations to investigate the competitive adsorption characteristics of three SMIs─aniline, 3-hexyne, and propanethiol (PT)─alongside trimethylaluminum (TMA) precursors on a Cu(111) surface. Single-component adsorption analyses reveal that aniline attains the highest coverage among the SMIs, attributed to its strong interaction with the Cu surface; however, this coverage decreases by approximately 42% in the presence of TMA, underscoring its susceptibility to competitive adsorption effects.
View Article and Find Full Text PDFDesiRNA: structure-based design of RNA sequences with a replica exchange Monte Carlo approach.
Nucleic Acids Res
January 2025
Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.
Designing RNA sequences that form a specific structure remains a challenge. Current computational methods often struggle with the complexity of RNA structures, especially when considering pseudoknots or restrictions related to RNA function. We developed DesiRNA, a computational tool for the design of RNA sequences based on the Replica Exchange Monte Carlo approach.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!