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Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study

BACKGROUND: The dosimetric parameters required in lung cancer radiation therapy are taken from a homogeneous water phantom; however, during treatment, the expected results are being affected because of its inhomogeneity. Therefore, it becomes necessary to quantify these deviations. OBJECTIVE: The pr...

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Autores principales: Raj Verma, T., Kumar Painuly, N., Prasad Mishra, S., Yoganathan, S.A., Singh, N., Bhatt, M.L.B., Jamal, N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Journal of Biomedical Physics and Engineering 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6409377/
https://www.ncbi.nlm.nih.gov/pubmed/30881931
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author Raj Verma, T.
Kumar Painuly, N.
Prasad Mishra, S.
Yoganathan, S.A.
Singh, N.
Bhatt, M.L.B.
Jamal, N.
author_facet Raj Verma, T.
Kumar Painuly, N.
Prasad Mishra, S.
Yoganathan, S.A.
Singh, N.
Bhatt, M.L.B.
Jamal, N.
author_sort Raj Verma, T.
collection PubMed
description BACKGROUND: The dosimetric parameters required in lung cancer radiation therapy are taken from a homogeneous water phantom; however, during treatment, the expected results are being affected because of its inhomogeneity. Therefore, it becomes necessary to quantify these deviations. OBJECTIVE: The present study has been undertaken to find out inter- and intra- lung density variations and its dosimetric impact on lung cancer radiotherapy using Monte Carlo code FLUKA and PBC algorithms. MATERIAL AND METHODS: Density of 100 lungs was recorded from their CT images along with age. Then, after PDD calculated by FLUKA MC Code and PBC algorithm for virtual phantom having density 0.2 gm/cm3 and 0.4 gm/cm3 (density range obtained from CT images of 100 lungs) using Co-60 10 x10 cm2 beams were compared. RESULTS: Average left and right lung densities were 0.275±0.387 and 0.270±0.383 respectively. The deviation in PBC calculated PDD were (+)216%, (+91%), (+)45%, (+)26.88%, (+)14%, (-)1%, (+)2%, (-)0.4%, (-)1%, (+)1%, (+)4%, (+)4.5% for 0.4 gm/cm3 and (+)311%, (+)177%, (+)118%, (+)90.95%, (+)72.23%, (+)55.83% ,(+)38.85%, (+)28.80%, (+)21.79%, (+)15.95%, (+)1.67%, (-) 2.13%, (+)1.27%, (+)0.35%, (-)1.79%, (-)2.75% for 0.2 gm/cm3 density mediums at depths of 1mm, 2mm, 3mm, 4mm, 5mm, 6 mm, 7 mm, 8mm, 9mm,10mm, 15mm, 30mm, 40mm, 50mm, 80mm and 100 mm, respectively. CONCLUSION: Large variations in inter- and intra- lung density were recorded. PBC overestimated the dose at air/lung interface as well as inside lung. The results of Monte Carlo simulation can be used to assess the performance of other treatment planning systems used in lung cancer radiotherapy.
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spelling pubmed-64093772019-03-16 Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study Raj Verma, T. Kumar Painuly, N. Prasad Mishra, S. Yoganathan, S.A. Singh, N. Bhatt, M.L.B. Jamal, N. J Biomed Phys Eng Original Article BACKGROUND: The dosimetric parameters required in lung cancer radiation therapy are taken from a homogeneous water phantom; however, during treatment, the expected results are being affected because of its inhomogeneity. Therefore, it becomes necessary to quantify these deviations. OBJECTIVE: The present study has been undertaken to find out inter- and intra- lung density variations and its dosimetric impact on lung cancer radiotherapy using Monte Carlo code FLUKA and PBC algorithms. MATERIAL AND METHODS: Density of 100 lungs was recorded from their CT images along with age. Then, after PDD calculated by FLUKA MC Code and PBC algorithm for virtual phantom having density 0.2 gm/cm3 and 0.4 gm/cm3 (density range obtained from CT images of 100 lungs) using Co-60 10 x10 cm2 beams were compared. RESULTS: Average left and right lung densities were 0.275±0.387 and 0.270±0.383 respectively. The deviation in PBC calculated PDD were (+)216%, (+91%), (+)45%, (+)26.88%, (+)14%, (-)1%, (+)2%, (-)0.4%, (-)1%, (+)1%, (+)4%, (+)4.5% for 0.4 gm/cm3 and (+)311%, (+)177%, (+)118%, (+)90.95%, (+)72.23%, (+)55.83% ,(+)38.85%, (+)28.80%, (+)21.79%, (+)15.95%, (+)1.67%, (-) 2.13%, (+)1.27%, (+)0.35%, (-)1.79%, (-)2.75% for 0.2 gm/cm3 density mediums at depths of 1mm, 2mm, 3mm, 4mm, 5mm, 6 mm, 7 mm, 8mm, 9mm,10mm, 15mm, 30mm, 40mm, 50mm, 80mm and 100 mm, respectively. CONCLUSION: Large variations in inter- and intra- lung density were recorded. PBC overestimated the dose at air/lung interface as well as inside lung. The results of Monte Carlo simulation can be used to assess the performance of other treatment planning systems used in lung cancer radiotherapy. Journal of Biomedical Physics and Engineering 2019-02-01 /pmc/articles/PMC6409377/ /pubmed/30881931 Text en Copyright: © Journal of Biomedical Physics and Engineering http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Raj Verma, T.
Kumar Painuly, N.
Prasad Mishra, S.
Yoganathan, S.A.
Singh, N.
Bhatt, M.L.B.
Jamal, N.
Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title_full Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title_fullStr Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title_full_unstemmed Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title_short Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study
title_sort evaluation of lung density and its dosimetric impact on lung cancer radiotherapy: a simulation study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6409377/
https://www.ncbi.nlm.nih.gov/pubmed/30881931
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