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Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer

OBJECTIVE: This study intends to construct an error distribution prediction model and analyze its parameters and analyzes the boundary size of CTV extension to PTV, so as to provide a reference for lung cancer patients to control clinical set-up errors and radiotherapy planning. METHODS: The prior S...

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Autores principales: Yang, Fan, Li, Xinxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250426/
https://www.ncbi.nlm.nih.gov/pubmed/35789648
http://dx.doi.org/10.1155/2022/5642529
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author Yang, Fan
Li, Xinxia
author_facet Yang, Fan
Li, Xinxia
author_sort Yang, Fan
collection PubMed
description OBJECTIVE: This study intends to construct an error distribution prediction model and analyze its parameters and analyzes the boundary size of CTV extension to PTV, so as to provide a reference for lung cancer patients to control clinical set-up errors and radiotherapy planning. METHODS: The prior SBRT set-up error data of 50 patients with lung cancer treated by medical linear accelerator were selected, the Gaussian mixture model was adopted to construct the error distribution prediction model, and the model parameters were solved, based on which the emission boundary from CTV to PTV was calculated. RESULTS: According to the analysis of the model parameters, the spatial distribution of set-up errors is mainly concentrated in the direction of four central points (μ(1) ~ μ(4)), and the error is smaller in the Vrt direction (-0.991~2.808 mm) and Lat direction (-0.447~1.337 mm) and larger in the Lng direction (-1.065~4,463 mm). The possibility of offset of set-up errors in μ(2) and μ(3) direction (0.4440, 02198) is greater than that of μ(1) and μ(4) (0.1767, 0.1595). The standard deviation of set-up errors can reach 0.538 mm. The theoretical expansion boundary of CTV to PTV in Vrt, Lng, and Lat can be calculated as 1.7963 mm, 2.3749 mm, and 0.6066 mm. CONCLUSION: The GMM Gaussian mixture model can quantitatively describe and predict the set-up errors distribution of lung cancer patients and can obtain the emission boundary of CTV to PTV, which provides a reference for radiotherapy set-up errors control and tumor planning target expansion of lung cancer patients without SBRT.
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spelling pubmed-92504262022-07-03 Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer Yang, Fan Li, Xinxia Biomed Res Int Research Article OBJECTIVE: This study intends to construct an error distribution prediction model and analyze its parameters and analyzes the boundary size of CTV extension to PTV, so as to provide a reference for lung cancer patients to control clinical set-up errors and radiotherapy planning. METHODS: The prior SBRT set-up error data of 50 patients with lung cancer treated by medical linear accelerator were selected, the Gaussian mixture model was adopted to construct the error distribution prediction model, and the model parameters were solved, based on which the emission boundary from CTV to PTV was calculated. RESULTS: According to the analysis of the model parameters, the spatial distribution of set-up errors is mainly concentrated in the direction of four central points (μ(1) ~ μ(4)), and the error is smaller in the Vrt direction (-0.991~2.808 mm) and Lat direction (-0.447~1.337 mm) and larger in the Lng direction (-1.065~4,463 mm). The possibility of offset of set-up errors in μ(2) and μ(3) direction (0.4440, 02198) is greater than that of μ(1) and μ(4) (0.1767, 0.1595). The standard deviation of set-up errors can reach 0.538 mm. The theoretical expansion boundary of CTV to PTV in Vrt, Lng, and Lat can be calculated as 1.7963 mm, 2.3749 mm, and 0.6066 mm. CONCLUSION: The GMM Gaussian mixture model can quantitatively describe and predict the set-up errors distribution of lung cancer patients and can obtain the emission boundary of CTV to PTV, which provides a reference for radiotherapy set-up errors control and tumor planning target expansion of lung cancer patients without SBRT. Hindawi 2022-06-25 /pmc/articles/PMC9250426/ /pubmed/35789648 http://dx.doi.org/10.1155/2022/5642529 Text en Copyright © 2022 Fan Yang and Xinxia Li. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Fan
Li, Xinxia
Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title_full Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title_fullStr Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title_full_unstemmed Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title_short Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer
title_sort construction of prediction model of radiotherapy set-up errors in patients with lung cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250426/
https://www.ncbi.nlm.nih.gov/pubmed/35789648
http://dx.doi.org/10.1155/2022/5642529
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