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Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography

BACKGROUND: To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers. METHODS: We analyzed 4D-CT image data sets of 27 conse...

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Autores principales: Ezhil, Muthuveni, Vedam, Sastry, Balter, Peter, Choi, Bum, Mirkovic, Dragan, Starkschall, George, Chang, Joe Y
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2645420/
https://www.ncbi.nlm.nih.gov/pubmed/19173738
http://dx.doi.org/10.1186/1748-717X-4-4
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author Ezhil, Muthuveni
Vedam, Sastry
Balter, Peter
Choi, Bum
Mirkovic, Dragan
Starkschall, George
Chang, Joe Y
author_facet Ezhil, Muthuveni
Vedam, Sastry
Balter, Peter
Choi, Bum
Mirkovic, Dragan
Starkschall, George
Chang, Joe Y
author_sort Ezhil, Muthuveni
collection PubMed
description BACKGROUND: To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers. METHODS: We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV(AllPhases)); (2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV(2Phases)); (3) defining the GTV contour using the maximum intensity projection (MIP) (IGTV(MIP)); and (4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV(MIP-Modified)). Using the IGTV(AllPhases )as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches. RESULTS: The IGTV(MIP )and IGTV(2Phases )were significantly smaller than the IGTV(AllPhases )(p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTV(MIP-Modified )were close to those determined from IGTV(AllPhases )(p = 0.08). IGTV(MIP-Modified )also matched the best with IGTV(AllPhases). CONCLUSION: IGTV(MIP )and IGTV(2Phases )underestimate IGTVs. IGTV(MIP-Modified )is recommended to improve IGTV delineation in lung cancer.
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spelling pubmed-26454202009-02-20 Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography Ezhil, Muthuveni Vedam, Sastry Balter, Peter Choi, Bum Mirkovic, Dragan Starkschall, George Chang, Joe Y Radiat Oncol Research BACKGROUND: To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers. METHODS: We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV(AllPhases)); (2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV(2Phases)); (3) defining the GTV contour using the maximum intensity projection (MIP) (IGTV(MIP)); and (4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV(MIP-Modified)). Using the IGTV(AllPhases )as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches. RESULTS: The IGTV(MIP )and IGTV(2Phases )were significantly smaller than the IGTV(AllPhases )(p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTV(MIP-Modified )were close to those determined from IGTV(AllPhases )(p = 0.08). IGTV(MIP-Modified )also matched the best with IGTV(AllPhases). CONCLUSION: IGTV(MIP )and IGTV(2Phases )underestimate IGTVs. IGTV(MIP-Modified )is recommended to improve IGTV delineation in lung cancer. BioMed Central 2009-01-27 /pmc/articles/PMC2645420/ /pubmed/19173738 http://dx.doi.org/10.1186/1748-717X-4-4 Text en Copyright © 2009 Ezhil et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Ezhil, Muthuveni
Vedam, Sastry
Balter, Peter
Choi, Bum
Mirkovic, Dragan
Starkschall, George
Chang, Joe Y
Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title_full Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title_fullStr Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title_full_unstemmed Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title_short Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
title_sort determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2645420/
https://www.ncbi.nlm.nih.gov/pubmed/19173738
http://dx.doi.org/10.1186/1748-717X-4-4
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