Evidence map›Paper›PMID 39027884›Full record

ArticleTechnical innovations & patient support in radiation oncology2024

An automation of Monte Carlo workflow for dosimetry study of an Elekta LINAC delivery system in radiotherapy.

Wenchih Tseng, Keith Furutani, Chris Beltran, Bo Lu

Abstract read
In one paragraph

Article in Technical innovations & patient support in radiation oncology, 2024. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Wenchih TsengDepartment of Radiation Oncology, University of Florida, Gainesville, FL 32610, USA.
Keith FurutaniDepartment of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, FL 32224, USA.
Chris BeltranDepartment of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, FL 32224, USA.
Bo LuDepartment of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, FL 32224, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to automate the Monte Carlo (MC) workflow utilized for radiotherapy dosimetry, focusing on an Elekta LINAC delivery system. It addresses the challenge of integrating MC simulations into routine clinical practice, making this accurate yet complex method more accessible and efficient for radiotherapy dosimetry. Methods and Materials: We developed a user-friendly software featuring a graphical user interface (GUI) that integrates EGSnrc for MC simulations. The software streamlines the process from retrieving Digital Imaging and Communications in Medicine (DICOM) data to executing dose calculations and comparing dose distributions. To validate our proposed tool, we compared its computed doses for IMRT and VMAT plans from the Pinnacle TPS for an Elekta Versa HD linear accelerator against MC simulation results. This comparison utilized our in-house software and GUI as the tool, covering various treatment sites and prescriptions. Results: The automated MC workflow demonstrated high accuracy in dose calculations and streamlined integration with clinical workflows. The comparison between the MC-simulated and TPS-calculated doses revealed excellent agreement, highlighting the reliability of MC for independent dose verification in complex treatment scenarios. Conclusions: The automated MC workflow developed represents a substantial improvement in the practicality and efficiency of MC simulations in radiotherapy. This advancement not only simplifies the dosimetry process but also ensures high accuracy, establishing it as a valuable tool for routine patient-specific quality assurance and the development of specialized treatment procedures.

Indexed as

Automated workflowEGSnrcElekta LinacGraphical user interfaceIMRT/VMATMonte Carlo simulation

Identifiers

PMID39027884
PMCPMC11255350

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.