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DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer
OBJECTIVES: To assess volumetric DCE-MRI radiomics nomogram in predicting response to neoadjuvant chemotherapy (nCT) in EC patients. METHODS: This retrospective analysis of a prospective study enrolled EC patients with stage cT1N + M0 or cT2-4aN0-3M0 who received DCE-MRI within 7 days before chemoth...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777517/ https://www.ncbi.nlm.nih.gov/pubmed/35201487 http://dx.doi.org/10.1007/s12672-022-00464-7 |
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author | Qu, Jinrong Ma, Ling Lu, Yanan Wang, Zhaoqi Guo, Jia Zhang, Hongkai Yan, Xu Liu, Hui Kamel, Ihab R. Qin, Jianjun Li, Hailiang |
author_facet | Qu, Jinrong Ma, Ling Lu, Yanan Wang, Zhaoqi Guo, Jia Zhang, Hongkai Yan, Xu Liu, Hui Kamel, Ihab R. Qin, Jianjun Li, Hailiang |
author_sort | Qu, Jinrong |
collection | PubMed |
description | OBJECTIVES: To assess volumetric DCE-MRI radiomics nomogram in predicting response to neoadjuvant chemotherapy (nCT) in EC patients. METHODS: This retrospective analysis of a prospective study enrolled EC patients with stage cT1N + M0 or cT2-4aN0-3M0 who received DCE-MRI within 7 days before chemotherapy, followed by surgery. Response assessment was graded from 1 to 5 according to the tumor regression grade (TRG). Patients were stratified into responders (TRG1 + 2) and non-responders (TRG3 + 4 + 5). 72 radiomics features and vascular permeability parameters were extracted from DCE-MRI. The discriminating performance was assessed with ROC. Decision curve analysis (DCA) was used for comparing three different models. RESULTS: This cohort included 82 patients, and 72 tumor radiomics features and vascular permeability parameters acquired from DCE-MRI. mRMR and LASSO were performed to choose the optimized subset of radiomics features, and 3 features were selected to create the radiomics signature that were significantly associated with response (P < 0.001). AUC of combining radiomics signature and DCE-MRI performance in the training (n = 41) and validation (n = 41) cohort was 0.84 (95% CI 0.57–1) and 0.86 (95% CI 0.74–0.97), respectively. This combined model showed the best discrimination between responders and non-responders, and showed the highest positive and positive predictive value in both training set and test set. CONCLUSIONS: The radiomics features are useful for nCT response prediction in EC patients. |
format | Online Article Text |
id | pubmed-8777517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-87775172022-02-03 DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer Qu, Jinrong Ma, Ling Lu, Yanan Wang, Zhaoqi Guo, Jia Zhang, Hongkai Yan, Xu Liu, Hui Kamel, Ihab R. Qin, Jianjun Li, Hailiang Discov Oncol Research OBJECTIVES: To assess volumetric DCE-MRI radiomics nomogram in predicting response to neoadjuvant chemotherapy (nCT) in EC patients. METHODS: This retrospective analysis of a prospective study enrolled EC patients with stage cT1N + M0 or cT2-4aN0-3M0 who received DCE-MRI within 7 days before chemotherapy, followed by surgery. Response assessment was graded from 1 to 5 according to the tumor regression grade (TRG). Patients were stratified into responders (TRG1 + 2) and non-responders (TRG3 + 4 + 5). 72 radiomics features and vascular permeability parameters were extracted from DCE-MRI. The discriminating performance was assessed with ROC. Decision curve analysis (DCA) was used for comparing three different models. RESULTS: This cohort included 82 patients, and 72 tumor radiomics features and vascular permeability parameters acquired from DCE-MRI. mRMR and LASSO were performed to choose the optimized subset of radiomics features, and 3 features were selected to create the radiomics signature that were significantly associated with response (P < 0.001). AUC of combining radiomics signature and DCE-MRI performance in the training (n = 41) and validation (n = 41) cohort was 0.84 (95% CI 0.57–1) and 0.86 (95% CI 0.74–0.97), respectively. This combined model showed the best discrimination between responders and non-responders, and showed the highest positive and positive predictive value in both training set and test set. CONCLUSIONS: The radiomics features are useful for nCT response prediction in EC patients. Springer US 2022-01-08 /pmc/articles/PMC8777517/ /pubmed/35201487 http://dx.doi.org/10.1007/s12672-022-00464-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Qu, Jinrong Ma, Ling Lu, Yanan Wang, Zhaoqi Guo, Jia Zhang, Hongkai Yan, Xu Liu, Hui Kamel, Ihab R. Qin, Jianjun Li, Hailiang DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title | DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title_full | DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title_fullStr | DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title_full_unstemmed | DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title_short | DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
title_sort | dce-mri radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777517/ https://www.ncbi.nlm.nih.gov/pubmed/35201487 http://dx.doi.org/10.1007/s12672-022-00464-7 |
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