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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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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. |
format | Online Article Text |
id | pubmed-8786722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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