Evidence map›Paper›PMID 41860210›Full record

ArticleTechnology in cancer research & treatment

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 and 1 more

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Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Srinivas ChallapalliDepartment of Radiation Oncology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka India.ORCID 0000-0003-0355-487X
Anupam ChoudharyDepartment of Urology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0002-9868-9269
Jyothi NageshDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0003-4308-8404
Shambhavi CMedical Physics programme, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Shirley LewisDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0001-5306-1649
Umesh VeluDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0001-8202-8995
Jayashree NpDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.
Ankita MehtaDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.
Manoj BelwalWelcomgroup Graduate School of Hotel Administration, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Dilson LoboDepartment of Radiation Oncology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka India.
Sarath S NairDepartment of Radiation Oncology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0002-0012-6020

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionThis 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.MethodsThree 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 240 plans were performed for all three image sets together for both the IMRT and VMAT techniques, and the dose at depth was compared and statistically analyzed via the Kruskal-Walli's test.ResultsThe homogeneity index (HI), conformity index (CI), and V95% target are increased in both IMRT and VMAT, whereas the SU and DVS are reduced.ConclusionHigher statistical uncertainty and grid size significantly reduced dose calculation time, independent of technique or device. surface dose at depth (1-5mm) decreased with increasing grid size and increased with lower statistical uncertainty. IMRT consistently showed higher skin doses than VMAT across all devices, with vac-lock immobilization yielding the highest surface dose in both techniques. These findings show that the surface dose is influenced by beam selection, parameter settings, and the optimization time allocated during treatment planning.

Indexed as

Radiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedAlgorithmsHumansMonte Carlo MethodPhantoms, ImagingRadiotherapy DosageTomography, X-Ray ComputedUncertaintydose voxel sizeintensity modulated radiation therapymonte carlostatistical uncertaintyvolumetric arc therapy (VMAT)

Identifiers

PMID41860210
PMCPMC13010009

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