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Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury

PURPOSE: To study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements. METHODS AND MATERIALS: The brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose d...

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Autores principales: Du, Qing-Hua, Li, Jian, Gan, Yi-Xiu, Zhu, Hui-Jun, Yue, Hai-Ying, Li, Xiang-De, Ou, Xue, Zhong, Qiu-Lu, Luo, Dan-Jing, Xie, Yi-Ting, Liang, Qian-Fu, Wang, Ren-Sheng, Liu, Wen-Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786722/
https://www.ncbi.nlm.nih.gov/pubmed/35087743
http://dx.doi.org/10.3389/fonc.2021.743941
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author Du, Qing-Hua
Li, Jian
Gan, Yi-Xiu
Zhu, Hui-Jun
Yue, Hai-Ying
Li, Xiang-De
Ou, Xue
Zhong, Qiu-Lu
Luo, Dan-Jing
Xie, Yi-Ting
Liang, Qian-Fu
Wang, Ren-Sheng
Liu, Wen-Qi
author_facet Du, Qing-Hua
Li, Jian
Gan, Yi-Xiu
Zhu, Hui-Jun
Yue, Hai-Ying
Li, Xiang-De
Ou, Xue
Zhong, Qiu-Lu
Luo, Dan-Jing
Xie, Yi-Ting
Liang, Qian-Fu
Wang, Ren-Sheng
Liu, Wen-Qi
author_sort Du, Qing-Hua
collection PubMed
description PURPOSE: To study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements. METHODS AND MATERIALS: The brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; V (D) with different D for different distributions). Predictive ability of EUD(V) (D) (EUD of V (D) ) for radiation-induced brain injury was assessed by receiver operating characteristics curve (ROC) and area under the curve (AUC). The optimal volume-effect parameter a of EUD was selected when AUC was maximal (mAUC). Correlations between mAUC, a and D were analyzed by Pearson correlation analysis. Both mAUC and a in brain and half-brain were compared by using paired samples t-tests. The optimal D (V) and V (D) points were selected for a simple comparison. RESULTS: The mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal a value was 21.5/22. When D increased, mAUC of EUD(V) (D) increased, while a decreased. The mAUC reached the maximum value when D was 50–55 Gy, and a was always 1 when D ≥55 Gy. The difference of mAUC/a between brain and half-brain was not significant. If a was in range of 1 to 22, AUC of brain/half-brain EUD(V55 Gy) (0.857–0.830/0.845–0.830) was always larger than that of brain/half-brain EUD (0.681–0.819/0.691–0.821). The AUCs of optimal dose/volume points were 0.801 (brain D(2.5 cc)), 0.823 (brain V(70 Gy)), 0.818 (half-brain D(1 cc)), and 0.827 (half-brain V(69 Gy)), respectively. Mean dose (equal to EUD(V) (D) with a = 1) of high-dose volume (V(50 Gy)–V(60 Gy)) was superior to traditional EUD and dose/volume points. CONCLUSION: Volume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability.
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spelling pubmed-87867222022-01-26 Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury Du, Qing-Hua Li, Jian Gan, Yi-Xiu Zhu, Hui-Jun Yue, Hai-Ying Li, Xiang-De Ou, Xue Zhong, Qiu-Lu Luo, Dan-Jing Xie, Yi-Ting Liang, Qian-Fu Wang, Ren-Sheng Liu, Wen-Qi Front Oncol Oncology PURPOSE: To study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements. METHODS AND MATERIALS: The brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; V (D) with different D for different distributions). Predictive ability of EUD(V) (D) (EUD of V (D) ) for radiation-induced brain injury was assessed by receiver operating characteristics curve (ROC) and area under the curve (AUC). The optimal volume-effect parameter a of EUD was selected when AUC was maximal (mAUC). Correlations between mAUC, a and D were analyzed by Pearson correlation analysis. Both mAUC and a in brain and half-brain were compared by using paired samples t-tests. The optimal D (V) and V (D) points were selected for a simple comparison. RESULTS: The mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal a value was 21.5/22. When D increased, mAUC of EUD(V) (D) increased, while a decreased. The mAUC reached the maximum value when D was 50–55 Gy, and a was always 1 when D ≥55 Gy. The difference of mAUC/a between brain and half-brain was not significant. If a was in range of 1 to 22, AUC of brain/half-brain EUD(V55 Gy) (0.857–0.830/0.845–0.830) was always larger than that of brain/half-brain EUD (0.681–0.819/0.691–0.821). The AUCs of optimal dose/volume points were 0.801 (brain D(2.5 cc)), 0.823 (brain V(70 Gy)), 0.818 (half-brain D(1 cc)), and 0.827 (half-brain V(69 Gy)), respectively. Mean dose (equal to EUD(V) (D) with a = 1) of high-dose volume (V(50 Gy)–V(60 Gy)) was superior to traditional EUD and dose/volume points. CONCLUSION: Volume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability. Frontiers Media S.A. 2022-01-11 /pmc/articles/PMC8786722/ /pubmed/35087743 http://dx.doi.org/10.3389/fonc.2021.743941 Text en Copyright © 2022 Du, Li, Gan, Zhu, Yue, Li, Ou, Zhong, Luo, Xie, Liang, Wang and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Du, Qing-Hua
Li, Jian
Gan, Yi-Xiu
Zhu, Hui-Jun
Yue, Hai-Ying
Li, Xiang-De
Ou, Xue
Zhong, Qiu-Lu
Luo, Dan-Jing
Xie, Yi-Ting
Liang, Qian-Fu
Wang, Ren-Sheng
Liu, Wen-Qi
Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title_full Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title_fullStr Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title_full_unstemmed Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title_short Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury
title_sort potential defects and improvements of equivalent uniform dose prediction model based on the analysis of radiation-induced brain injury
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786722/
https://www.ncbi.nlm.nih.gov/pubmed/35087743
http://dx.doi.org/10.3389/fonc.2021.743941
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