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Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma
OBJECTIVE: To develop and validate an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: “Radiomics” enables the investigation of huge amounts of radiological features in parallel by extracting high-throughput imaging data. MRI provides better tissue con...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998897/ https://www.ncbi.nlm.nih.gov/pubmed/36910599 http://dx.doi.org/10.3389/fonc.2023.1074445 |
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author | Xu, Xinsen Qu, Jiaqi Zhang, Yijue Qian, Xiaohua Chen, Tao Liu, Yingbin |
author_facet | Xu, Xinsen Qu, Jiaqi Zhang, Yijue Qian, Xiaohua Chen, Tao Liu, Yingbin |
author_sort | Xu, Xinsen |
collection | PubMed |
description | OBJECTIVE: To develop and validate an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: “Radiomics” enables the investigation of huge amounts of radiological features in parallel by extracting high-throughput imaging data. MRI provides better tissue contrast with no ionizing radiation for PDAC. METHODS: There were 78 PDAC patients enrolled in this study. In total, there were 386 radiomics features extracted from MRI scan, which were screened by the least absolute shrinkage and selection operator algorithm to develop a risk score. Cox multivariate regression analysis was applied to develop the radiomics-based nomogram. The performance was assessed by discrimination and calibration. RESULTS: The radiomics-based risk-score was significantly associated with PDAC overall survival (OS) (P < 0.05). With respect to survival prediction, integrating the risk score, clinical data and TNM information into the nomogram exhibited better performance than the TNM staging system, radiomics model and clinical model. In addition, the nomogram showed fine discrimination and calibration. CONCLUSIONS: The radiomics nomogram incorporating the radiomics data, clinical data and TNM information exhibited precise survival prediction for PDAC, which may help accelerate personalized precision treatment. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov, identifier NCT05313854. |
format | Online Article Text |
id | pubmed-9998897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99988972023-03-11 Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma Xu, Xinsen Qu, Jiaqi Zhang, Yijue Qian, Xiaohua Chen, Tao Liu, Yingbin Front Oncol Oncology OBJECTIVE: To develop and validate an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: “Radiomics” enables the investigation of huge amounts of radiological features in parallel by extracting high-throughput imaging data. MRI provides better tissue contrast with no ionizing radiation for PDAC. METHODS: There were 78 PDAC patients enrolled in this study. In total, there were 386 radiomics features extracted from MRI scan, which were screened by the least absolute shrinkage and selection operator algorithm to develop a risk score. Cox multivariate regression analysis was applied to develop the radiomics-based nomogram. The performance was assessed by discrimination and calibration. RESULTS: The radiomics-based risk-score was significantly associated with PDAC overall survival (OS) (P < 0.05). With respect to survival prediction, integrating the risk score, clinical data and TNM information into the nomogram exhibited better performance than the TNM staging system, radiomics model and clinical model. In addition, the nomogram showed fine discrimination and calibration. CONCLUSIONS: The radiomics nomogram incorporating the radiomics data, clinical data and TNM information exhibited precise survival prediction for PDAC, which may help accelerate personalized precision treatment. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov, identifier NCT05313854. Frontiers Media S.A. 2023-02-24 /pmc/articles/PMC9998897/ /pubmed/36910599 http://dx.doi.org/10.3389/fonc.2023.1074445 Text en Copyright © 2023 Xu, Qu, Zhang, Qian, Chen 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 Xu, Xinsen Qu, Jiaqi Zhang, Yijue Qian, Xiaohua Chen, Tao Liu, Yingbin Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title | Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title_full | Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title_fullStr | Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title_full_unstemmed | Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title_short | Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
title_sort | development and validation of an mri-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998897/ https://www.ncbi.nlm.nih.gov/pubmed/36910599 http://dx.doi.org/10.3389/fonc.2023.1074445 |
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