Cargando…

To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based

This study aimed to find a better dosimetric parameter in predicting of radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC) individually: ventilation(V), perfusion (Q) or computerized tomography (CT) based. V/Q single-photon emission computerized tomography (SP...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiao, Lin-Lin, Yang, Guoren, Chen, Jinhu, Wang, Xiaohui, Wu, Qingwei, Huo, Zongwei, Yu, Qingxi, Yu, Jinming, Yuan, Shuanghu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5353591/
https://www.ncbi.nlm.nih.gov/pubmed/28294159
http://dx.doi.org/10.1038/srep44646
_version_ 1782515140435902464
author Xiao, Lin-Lin
Yang, Guoren
Chen, Jinhu
Wang, Xiaohui
Wu, Qingwei
Huo, Zongwei
Yu, Qingxi
Yu, Jinming
Yuan, Shuanghu
author_facet Xiao, Lin-Lin
Yang, Guoren
Chen, Jinhu
Wang, Xiaohui
Wu, Qingwei
Huo, Zongwei
Yu, Qingxi
Yu, Jinming
Yuan, Shuanghu
author_sort Xiao, Lin-Lin
collection PubMed
description This study aimed to find a better dosimetric parameter in predicting of radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC) individually: ventilation(V), perfusion (Q) or computerized tomography (CT) based. V/Q single-photon emission computerized tomography (SPECT) was performed within 1 week prior to radiotherapy (RT). All V/Q imaging data was integrated into RT planning system, generating functional parameters based on V/Q SPECT. Fifty-seven NSCLC patients were enrolled in this prospective study. Fifteen (26.3%) patients underwent grade ≥2 RILT, the remaining forty-two (73.7%) patients didn’t. Q-MLD, Q-V20, V-MLD, V-V20 of functional parameters correlated more significantly with the occurrence of RILT compared to V20, MLD of anatomical parameters (r = 0.630; r = 0.644; r = 0.617; r = 0.651 vs. r = 0.424; r = 0.520 p < 0.05, respectively). In patients with chronic obstructive pulmonary diseases (COPD), V functional parameters reflected significant advantage in predicting RILT; while in patients without COPD, Q functional parameters reflected significant advantage. Analogous results were existed in fractimal analysis of global pulmonary function test (PFT). In patients with central-type NSCLC, V parameters were better than Q parameters; while in patients with peripheral-type NSCLC, the results were inverse. Therefore, this study demonstrated that choosing a suitable dosimetric parameter individually can help us predict RILT accurately.
format Online
Article
Text
id pubmed-5353591
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-53535912017-03-20 To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based Xiao, Lin-Lin Yang, Guoren Chen, Jinhu Wang, Xiaohui Wu, Qingwei Huo, Zongwei Yu, Qingxi Yu, Jinming Yuan, Shuanghu Sci Rep Article This study aimed to find a better dosimetric parameter in predicting of radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC) individually: ventilation(V), perfusion (Q) or computerized tomography (CT) based. V/Q single-photon emission computerized tomography (SPECT) was performed within 1 week prior to radiotherapy (RT). All V/Q imaging data was integrated into RT planning system, generating functional parameters based on V/Q SPECT. Fifty-seven NSCLC patients were enrolled in this prospective study. Fifteen (26.3%) patients underwent grade ≥2 RILT, the remaining forty-two (73.7%) patients didn’t. Q-MLD, Q-V20, V-MLD, V-V20 of functional parameters correlated more significantly with the occurrence of RILT compared to V20, MLD of anatomical parameters (r = 0.630; r = 0.644; r = 0.617; r = 0.651 vs. r = 0.424; r = 0.520 p < 0.05, respectively). In patients with chronic obstructive pulmonary diseases (COPD), V functional parameters reflected significant advantage in predicting RILT; while in patients without COPD, Q functional parameters reflected significant advantage. Analogous results were existed in fractimal analysis of global pulmonary function test (PFT). In patients with central-type NSCLC, V parameters were better than Q parameters; while in patients with peripheral-type NSCLC, the results were inverse. Therefore, this study demonstrated that choosing a suitable dosimetric parameter individually can help us predict RILT accurately. Nature Publishing Group 2017-03-15 /pmc/articles/PMC5353591/ /pubmed/28294159 http://dx.doi.org/10.1038/srep44646 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Xiao, Lin-Lin
Yang, Guoren
Chen, Jinhu
Wang, Xiaohui
Wu, Qingwei
Huo, Zongwei
Yu, Qingxi
Yu, Jinming
Yuan, Shuanghu
To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title_full To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title_fullStr To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title_full_unstemmed To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title_short To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based
title_sort to find a better dosimetric parameter in the predicting of radiation-induced lung toxicity individually: ventilation, perfusion or ct based
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5353591/
https://www.ncbi.nlm.nih.gov/pubmed/28294159
http://dx.doi.org/10.1038/srep44646
work_keys_str_mv AT xiaolinlin tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT yangguoren tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT chenjinhu tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT wangxiaohui tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT wuqingwei tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT huozongwei tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT yuqingxi tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT yujinming tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased
AT yuanshuanghu tofindabetterdosimetricparameterinthepredictingofradiationinducedlungtoxicityindividuallyventilationperfusionorctbased