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A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation
BACKGROUND: In this study, we designed a new (Su’S) target area delineation to protect the normal liver during liver regeneration and prospectively evaluate liver regeneration after radiotherapy, as well as to explore the clinical factors of liver regeneration and established a model and nomogram. M...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426619/ https://www.ncbi.nlm.nih.gov/pubmed/34513671 http://dx.doi.org/10.3389/fonc.2021.680303 |
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author | Su, Ting-Shi Li, Li-Qing Liang, Shi-Xiong Xiang, Bang-De Li, Jian-Xu Ye, Jia-Zhou Li, Le-Qun |
author_facet | Su, Ting-Shi Li, Li-Qing Liang, Shi-Xiong Xiang, Bang-De Li, Jian-Xu Ye, Jia-Zhou Li, Le-Qun |
author_sort | Su, Ting-Shi |
collection | PubMed |
description | BACKGROUND: In this study, we designed a new (Su’S) target area delineation to protect the normal liver during liver regeneration and prospectively evaluate liver regeneration after radiotherapy, as well as to explore the clinical factors of liver regeneration and established a model and nomogram. METHODS: Thirty patients treated with preoperative downstaging radiotherapy were prospectively included in the training cohort, and 21 patients treated with postoperative adjuvant radiotherapy were included in the validation cohort. The cut-off points of each optimal predictor were obtained using receiver-operating characteristic analysis. A model and nomogram for liver regeneration after radiotherapy were developed and validated. RESULTS: After radiotherapy, 12 (40%) and 13 (61.9%) patients in the training and validation cohorts experienced liver regeneration, respectively. The risk stratification model based on the cutoffs of standard residual liver volume spared from at least 20 Gy (SVs20 = 303.4 mL/m(2)) and alanine aminotransferase (ALT=43 u/L) was able to effectively discriminate the probability of liver regeneration. The model and nomogram of liver regeneration based on SVs20 and ALT showed good prediction performance (AUC=0.759) in the training cohort and performed well (AUC=0.808) in the validation cohort. CONCLUSIONS: SVs20 and ALT were optimal predictors of liver regeneration. This model may be beneficial to the constraints of the normal liver outside the radiotherapy-targeted areas. |
format | Online Article Text |
id | pubmed-8426619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84266192021-09-10 A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation Su, Ting-Shi Li, Li-Qing Liang, Shi-Xiong Xiang, Bang-De Li, Jian-Xu Ye, Jia-Zhou Li, Le-Qun Front Oncol Oncology BACKGROUND: In this study, we designed a new (Su’S) target area delineation to protect the normal liver during liver regeneration and prospectively evaluate liver regeneration after radiotherapy, as well as to explore the clinical factors of liver regeneration and established a model and nomogram. METHODS: Thirty patients treated with preoperative downstaging radiotherapy were prospectively included in the training cohort, and 21 patients treated with postoperative adjuvant radiotherapy were included in the validation cohort. The cut-off points of each optimal predictor were obtained using receiver-operating characteristic analysis. A model and nomogram for liver regeneration after radiotherapy were developed and validated. RESULTS: After radiotherapy, 12 (40%) and 13 (61.9%) patients in the training and validation cohorts experienced liver regeneration, respectively. The risk stratification model based on the cutoffs of standard residual liver volume spared from at least 20 Gy (SVs20 = 303.4 mL/m(2)) and alanine aminotransferase (ALT=43 u/L) was able to effectively discriminate the probability of liver regeneration. The model and nomogram of liver regeneration based on SVs20 and ALT showed good prediction performance (AUC=0.759) in the training cohort and performed well (AUC=0.808) in the validation cohort. CONCLUSIONS: SVs20 and ALT were optimal predictors of liver regeneration. This model may be beneficial to the constraints of the normal liver outside the radiotherapy-targeted areas. Frontiers Media S.A. 2021-08-26 /pmc/articles/PMC8426619/ /pubmed/34513671 http://dx.doi.org/10.3389/fonc.2021.680303 Text en Copyright © 2021 Su, Li, Liang, Xiang, Li, Ye and Li 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 Su, Ting-Shi Li, Li-Qing Liang, Shi-Xiong Xiang, Bang-De Li, Jian-Xu Ye, Jia-Zhou Li, Le-Qun A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title | A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title_full | A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title_fullStr | A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title_full_unstemmed | A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title_short | A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su’S) Target Area Delineation |
title_sort | prospective study of liver regeneration after radiotherapy based on a new (su’s) target area delineation |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426619/ https://www.ncbi.nlm.nih.gov/pubmed/34513671 http://dx.doi.org/10.3389/fonc.2021.680303 |
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