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Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance

PURPOSE: To incorporate four‐dimensional computed tomography (4DCT)‐based ventilation imaging into intensity‐modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. METHODS AND MATERIALS: Nineteen locally advanced lung cancer patients are retrospectively studied. 4D...

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Autores principales: Iqbal, Gazi Md Daud, Zhang, Hao, D'Souza, Wareen, Ha, Lidan, Rosenberger, Jay M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243320/
https://www.ncbi.nlm.nih.gov/pubmed/36727606
http://dx.doi.org/10.1002/acm2.13920
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author Iqbal, Gazi Md Daud
Zhang, Hao
D'Souza, Wareen
Ha, Lidan
Rosenberger, Jay M.
author_facet Iqbal, Gazi Md Daud
Zhang, Hao
D'Souza, Wareen
Ha, Lidan
Rosenberger, Jay M.
author_sort Iqbal, Gazi Md Daud
collection PubMed
description PURPOSE: To incorporate four‐dimensional computed tomography (4DCT)‐based ventilation imaging into intensity‐modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. METHODS AND MATERIALS: Nineteen locally advanced lung cancer patients are retrospectively studied. 4DCT images are employed to create ventilation maps for each patient via a density‐change‐based algorithm with mass correction. The regional ventilation is directly incorporated into the mathematical formulation of a direct aperture optimization model in IMRT treatment planning to achieve functional avoidance and a voxel‐based treatment plan. The proposed functional avoidance planning and voxel‐based planning are compared to the conventional treatment planning approach purely based on the anatomy of patients. Paired sample t‐tests are conducted to see whether dosimetric differences among the three approaches are significant. RESULTS: Similar planning target volume (PTV) coverage is achieved by anatomical, functional avoidance, and voxel‐based approaches. The voxel‐based treatment planning performs better than both functional avoidance and anatomical planning to the lung. For a total lung, the average volume reductions in a functional avoidance plan from an anatomical plan, a voxel‐based plan from an anatomical plan, and a voxel‐based plan from a functional avoidance plan are 7.0%, 16.8%, and 10.6%, respectively for V(40); and 0.4%, 6.4%, and 6.0%, respectively for mean Lung Dose (MLD). For a functional lung, the reductions are 8.8%, 17.2%, and 9.2%, respectively, for fV(40); and 1.1%, 6.2%, and 5.2%, respectively, for functional mean lung dose (fMLD). These reductions are obtained without significantly increasing doses to other organs‐at‐risk. All the pairwise treatment planning comparisons for both total lung and functional lung are statistically significant (p‐value [Formula: see text]) except for the functional avoidance plan with the anatomical plan pair in which the p‐value [Formula: see text]. From these results, we can conclude that voxel‐based treatment planning outperforms both anatomical and functional‐avoidance planning. CONCLUSIONS: We propose a treatment planning framework that directly utilizes functional images and compares voxel‐based treatment planning with functional avoidance and anatomical treatment planning.
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spelling pubmed-102433202023-06-07 Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance Iqbal, Gazi Md Daud Zhang, Hao D'Souza, Wareen Ha, Lidan Rosenberger, Jay M. J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: To incorporate four‐dimensional computed tomography (4DCT)‐based ventilation imaging into intensity‐modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. METHODS AND MATERIALS: Nineteen locally advanced lung cancer patients are retrospectively studied. 4DCT images are employed to create ventilation maps for each patient via a density‐change‐based algorithm with mass correction. The regional ventilation is directly incorporated into the mathematical formulation of a direct aperture optimization model in IMRT treatment planning to achieve functional avoidance and a voxel‐based treatment plan. The proposed functional avoidance planning and voxel‐based planning are compared to the conventional treatment planning approach purely based on the anatomy of patients. Paired sample t‐tests are conducted to see whether dosimetric differences among the three approaches are significant. RESULTS: Similar planning target volume (PTV) coverage is achieved by anatomical, functional avoidance, and voxel‐based approaches. The voxel‐based treatment planning performs better than both functional avoidance and anatomical planning to the lung. For a total lung, the average volume reductions in a functional avoidance plan from an anatomical plan, a voxel‐based plan from an anatomical plan, and a voxel‐based plan from a functional avoidance plan are 7.0%, 16.8%, and 10.6%, respectively for V(40); and 0.4%, 6.4%, and 6.0%, respectively for mean Lung Dose (MLD). For a functional lung, the reductions are 8.8%, 17.2%, and 9.2%, respectively, for fV(40); and 1.1%, 6.2%, and 5.2%, respectively, for functional mean lung dose (fMLD). These reductions are obtained without significantly increasing doses to other organs‐at‐risk. All the pairwise treatment planning comparisons for both total lung and functional lung are statistically significant (p‐value [Formula: see text]) except for the functional avoidance plan with the anatomical plan pair in which the p‐value [Formula: see text]. From these results, we can conclude that voxel‐based treatment planning outperforms both anatomical and functional‐avoidance planning. CONCLUSIONS: We propose a treatment planning framework that directly utilizes functional images and compares voxel‐based treatment planning with functional avoidance and anatomical treatment planning. John Wiley and Sons Inc. 2023-02-02 /pmc/articles/PMC10243320/ /pubmed/36727606 http://dx.doi.org/10.1002/acm2.13920 Text en © 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Iqbal, Gazi Md Daud
Zhang, Hao
D'Souza, Wareen
Ha, Lidan
Rosenberger, Jay M.
Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title_full Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title_fullStr Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title_full_unstemmed Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title_short Four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
title_sort four‐dimensional computed tomography‐based ventilation imaging in intensity‐modulated radiation therapy treatment planning for pulmonary functional avoidance
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243320/
https://www.ncbi.nlm.nih.gov/pubmed/36727606
http://dx.doi.org/10.1002/acm2.13920
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