Impact of Voxel Grid Size and Statistical Uncertainty on Surface Depth Dose Via Various Planning Techniques and Immobilization Devices Using Monte Carlo Algorithm
Srinivas Challapalli, Anupam Choudhary, Jyothi Nagesh, Shambhavi C, Shirley Lewis, Umesh Velu, Jayashree NP, Ankita Mehta, Manoj Belwal, Dilson Lobo, Sarath S. Nair

TL;DR
This study examines how changes in voxel grid size and statistical uncertainty affect surface dose depth in radiotherapy planning using Monte Carlo simulations.
Contribution
The study introduces a detailed analysis of surface dose variations based on grid size and uncertainty in different immobilization devices and planning techniques.
Findings
Higher statistical uncertainty and grid size significantly reduced dose calculation time.
Surface dose at depth decreased with increasing grid size and increased with lower statistical uncertainty.
IMRT consistently showed higher skin doses than VMAT, with vac-lock immobilization yielding the highest surface dose.
Abstract
This study aims to analyze the impact of the surface dose at depth (1-5mm) in different planning techniques and immobilization devices by varying the dose-voxel size (DVS) and statistical uncertainty (SU) using Monte Carlo (MC) algorithm. Three Sets of computed tomography (CT) images were taken from an in-house developed chest phantom, which included an open phantom, a vaclok and a thermoplastic mask. The image sets were pushed to the Monaco planning station for registration and contouring. Six beams of 6 MV photon energy are used to plan an Intensity modulated radiotherapy (IMRT) technique, and a half arc beam is used for Volumetric Modulated arc therapy (VMAT). In each plan, recalculation is performed by changing only the grid size from 1 mm to 8 mm and the statistical uncertainty from 1% to 5% from the parameter control window, keeping the other dose constraints the same. A total of…
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Taxonomy
TopicsAdvanced Radiotherapy Techniques · Advanced X-ray and CT Imaging · Radiation Dose and Imaging
