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Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI
Chemoradiation therapy (CRT) of locally advanced esophageal cancer (LAEC), although improving outcomes of patients, still results in 50% of local failure. An early prediction could identify patients at high risk of poor response for individualized adaptive treatment. We aimed to investigate physiolo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8645758/ https://www.ncbi.nlm.nih.gov/pubmed/34618997 http://dx.doi.org/10.1111/cas.15156 |
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author | Wang, Peiliang Wang, Xin Xu, Liang Yu, Jinming Teng, Feifei |
author_facet | Wang, Peiliang Wang, Xin Xu, Liang Yu, Jinming Teng, Feifei |
author_sort | Wang, Peiliang |
collection | PubMed |
description | Chemoradiation therapy (CRT) of locally advanced esophageal cancer (LAEC), although improving outcomes of patients, still results in 50% of local failure. An early prediction could identify patients at high risk of poor response for individualized adaptive treatment. We aimed to investigate physiological changes in LAEC using diffusion and perfusion magnetic resonance imaging (MRI) for early prediction of treatment response. In the study, 115 LAEC patients treated with CRT were enrolled (67 in the discovery cohort and 48 in the validation cohort). MRI scans were performed before radiotherapy (pre‐RT) and at week 3 during RT (mid‐RT). Gross tumor volume (GTV) of primary tumor was delineated on T2‐weighted images. Within the GTV, the hypercellularity volume (V(HC)) and high blood volume (V(HBV)) were defined based on the analysis of ADC and fractional plasma volume (Vp) histogram distributions within the tumors in the discovery cohort. The median GTVs were 28 cc ± 2.2 cc at pre‐RT and 16.7 cc ± 1.5 cc at mid‐RT. Respectively, V(HC) and V(HBV) decreased from 4.7 cc ± 0.7 cc and 5.7 cc ± 0.7 cc at pre‐RT to 2.8 cc ± 0.4 cc and 3.5 cc ± 0.5 cc at mid‐RT. Smaller V(HC) at mid‐RT (area under the curve [AUC] = 0.67, P = .05; AUC = 0.66, P = .05) and further decrease in V(HC) at mid‐RT (AUC = 0.7, P = .01; AUC = 0.69, P = .03) were associated with longer progression‐free survival (PFS) in both discovery and validation cohort. No significant predictive effects were shown in GTV and V(HBV) at any time point. In conclusion, we demonstrated that V(HC) represents aggressive subvolumes in LAEC. Further analysis will be carried out to confirm the correlations between the changes in image‐phenotype subvolumes and local failure to determine the radiation‐resistant tumor subvolumes, which may be useful for dose escalation. |
format | Online Article Text |
id | pubmed-8645758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86457582021-12-17 Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI Wang, Peiliang Wang, Xin Xu, Liang Yu, Jinming Teng, Feifei Cancer Sci Original Articles Chemoradiation therapy (CRT) of locally advanced esophageal cancer (LAEC), although improving outcomes of patients, still results in 50% of local failure. An early prediction could identify patients at high risk of poor response for individualized adaptive treatment. We aimed to investigate physiological changes in LAEC using diffusion and perfusion magnetic resonance imaging (MRI) for early prediction of treatment response. In the study, 115 LAEC patients treated with CRT were enrolled (67 in the discovery cohort and 48 in the validation cohort). MRI scans were performed before radiotherapy (pre‐RT) and at week 3 during RT (mid‐RT). Gross tumor volume (GTV) of primary tumor was delineated on T2‐weighted images. Within the GTV, the hypercellularity volume (V(HC)) and high blood volume (V(HBV)) were defined based on the analysis of ADC and fractional plasma volume (Vp) histogram distributions within the tumors in the discovery cohort. The median GTVs were 28 cc ± 2.2 cc at pre‐RT and 16.7 cc ± 1.5 cc at mid‐RT. Respectively, V(HC) and V(HBV) decreased from 4.7 cc ± 0.7 cc and 5.7 cc ± 0.7 cc at pre‐RT to 2.8 cc ± 0.4 cc and 3.5 cc ± 0.5 cc at mid‐RT. Smaller V(HC) at mid‐RT (area under the curve [AUC] = 0.67, P = .05; AUC = 0.66, P = .05) and further decrease in V(HC) at mid‐RT (AUC = 0.7, P = .01; AUC = 0.69, P = .03) were associated with longer progression‐free survival (PFS) in both discovery and validation cohort. No significant predictive effects were shown in GTV and V(HBV) at any time point. In conclusion, we demonstrated that V(HC) represents aggressive subvolumes in LAEC. Further analysis will be carried out to confirm the correlations between the changes in image‐phenotype subvolumes and local failure to determine the radiation‐resistant tumor subvolumes, which may be useful for dose escalation. John Wiley and Sons Inc. 2021-10-20 2021-12 /pmc/articles/PMC8645758/ /pubmed/34618997 http://dx.doi.org/10.1111/cas.15156 Text en © 2021 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Wang, Peiliang Wang, Xin Xu, Liang Yu, Jinming Teng, Feifei Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title | Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title_full | Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title_fullStr | Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title_full_unstemmed | Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title_short | Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI |
title_sort | prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion mri |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8645758/ https://www.ncbi.nlm.nih.gov/pubmed/34618997 http://dx.doi.org/10.1111/cas.15156 |
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