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Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
BACKGROUND: To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer. METHODS: In total, 101 patients (training cohort, n = 67; validat...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417065/ https://www.ncbi.nlm.nih.gov/pubmed/30866965 http://dx.doi.org/10.1186/s13014-019-1246-8 |
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author | Jeon, Seung Hyuck Song, Changhoon Chie, Eui Kyu Kim, Bohyoung Kim, Young Hoon Chang, Won Lee, Yoon Jin Chung, Joo-Hyun Chung, Jin Beom Lee, Keun-Wook Kang, Sung-Bum Kim, Jae-Sung |
author_facet | Jeon, Seung Hyuck Song, Changhoon Chie, Eui Kyu Kim, Bohyoung Kim, Young Hoon Chang, Won Lee, Yoon Jin Chung, Joo-Hyun Chung, Jin Beom Lee, Keun-Wook Kang, Sung-Bum Kim, Jae-Sung |
author_sort | Jeon, Seung Hyuck |
collection | PubMed |
description | BACKGROUND: To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer. METHODS: In total, 101 patients (training cohort, n = 67; validation cohort, n = 34) with locally advanced rectal adenocarcinoma between 2008 and 2015 were included. We extracted 55 features from T2-weighted magnetic resonance imaging (MRI) scans. Delta-radiomics feature was defined as the difference in radiomics feature before and after CCRT. Signatures were developed to predict local recurrence (LR), distant metastasis (DM), and disease-free survival (DFS) from 2D and 3D features. The least absolute shrinkage and selection operator regression was used to select features and build signatures. The delta-radiomics signatures and clinical factors were integrated into Cox regression analysis to determine if the signatures were independent prognostic factors. RESULTS: The radiomics signatures for LR, DM, and DFS were developed and validated using both 2D and 3D features. Outcomes were significantly different in the low- and high-risk patients dichotomized by optimal cutoff in both the training and validation cohorts. In multivariate analysis, the signatures were independent prognostic factors even when considering the clinical parameters. There were no significant differences in C-index from 2D vs. 3D signatures. CONCLUSIONS: This is the first study to develop delta-radiomics signatures for rectal cancer. The signatures successfully predicted the outcomes and were independent prognostic factors. External validation is warranted to ensure their performance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-019-1246-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6417065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64170652019-03-25 Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer Jeon, Seung Hyuck Song, Changhoon Chie, Eui Kyu Kim, Bohyoung Kim, Young Hoon Chang, Won Lee, Yoon Jin Chung, Joo-Hyun Chung, Jin Beom Lee, Keun-Wook Kang, Sung-Bum Kim, Jae-Sung Radiat Oncol Research BACKGROUND: To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer. METHODS: In total, 101 patients (training cohort, n = 67; validation cohort, n = 34) with locally advanced rectal adenocarcinoma between 2008 and 2015 were included. We extracted 55 features from T2-weighted magnetic resonance imaging (MRI) scans. Delta-radiomics feature was defined as the difference in radiomics feature before and after CCRT. Signatures were developed to predict local recurrence (LR), distant metastasis (DM), and disease-free survival (DFS) from 2D and 3D features. The least absolute shrinkage and selection operator regression was used to select features and build signatures. The delta-radiomics signatures and clinical factors were integrated into Cox regression analysis to determine if the signatures were independent prognostic factors. RESULTS: The radiomics signatures for LR, DM, and DFS were developed and validated using both 2D and 3D features. Outcomes were significantly different in the low- and high-risk patients dichotomized by optimal cutoff in both the training and validation cohorts. In multivariate analysis, the signatures were independent prognostic factors even when considering the clinical parameters. There were no significant differences in C-index from 2D vs. 3D signatures. CONCLUSIONS: This is the first study to develop delta-radiomics signatures for rectal cancer. The signatures successfully predicted the outcomes and were independent prognostic factors. External validation is warranted to ensure their performance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-019-1246-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-12 /pmc/articles/PMC6417065/ /pubmed/30866965 http://dx.doi.org/10.1186/s13014-019-1246-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Jeon, Seung Hyuck Song, Changhoon Chie, Eui Kyu Kim, Bohyoung Kim, Young Hoon Chang, Won Lee, Yoon Jin Chung, Joo-Hyun Chung, Jin Beom Lee, Keun-Wook Kang, Sung-Bum Kim, Jae-Sung Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title | Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title_full | Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title_fullStr | Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title_full_unstemmed | Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title_short | Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
title_sort | delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417065/ https://www.ncbi.nlm.nih.gov/pubmed/30866965 http://dx.doi.org/10.1186/s13014-019-1246-8 |
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