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Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma

BACKGROUND: Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It’s important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. METHODS: Patients with E...

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Autores principales: Zhao, Yu-Ting, Chen, Si-Ye, Liu, Xin, Yang, Yong, Chen, Bo, Song, Yong-Wen, Fang, Hui, Jin, Jing, Liu, Yue-Ping, Jing, Hao, Tang, Yuan, Li, Ning, Lu, Ning-Ning, Wang, Shu-Lian, Ouyang, Han, Hu, Chen, Liu, Jin, Wang, Zhi, Chen, Fan, Yin, Lin, Zhong, Qiu-Zi, Men, Kuo, Dai, Jian-Rong, Qi, Shu-Nan, Li, Ye-Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878926/
https://www.ncbi.nlm.nih.gov/pubmed/36698118
http://dx.doi.org/10.1186/s12885-023-10557-3
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author Zhao, Yu-Ting
Chen, Si-Ye
Liu, Xin
Yang, Yong
Chen, Bo
Song, Yong-Wen
Fang, Hui
Jin, Jing
Liu, Yue-Ping
Jing, Hao
Tang, Yuan
Li, Ning
Lu, Ning-Ning
Wang, Shu-Lian
Ouyang, Han
Hu, Chen
Liu, Jin
Wang, Zhi
Chen, Fan
Yin, Lin
Zhong, Qiu-Zi
Men, Kuo
Dai, Jian-Rong
Qi, Shu-Nan
Li, Ye-Xiong
author_facet Zhao, Yu-Ting
Chen, Si-Ye
Liu, Xin
Yang, Yong
Chen, Bo
Song, Yong-Wen
Fang, Hui
Jin, Jing
Liu, Yue-Ping
Jing, Hao
Tang, Yuan
Li, Ning
Lu, Ning-Ning
Wang, Shu-Lian
Ouyang, Han
Hu, Chen
Liu, Jin
Wang, Zhi
Chen, Fan
Yin, Lin
Zhong, Qiu-Zi
Men, Kuo
Dai, Jian-Rong
Qi, Shu-Nan
Li, Ye-Xiong
author_sort Zhao, Yu-Ting
collection PubMed
description BACKGROUND: Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It’s important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. METHODS: Patients with ENKTCL in a prospectively cohort were systemically reviewed and all the pretreatment MRI were acquisitioned. An unsupervised spectral clustering method was used to identify risk groups of patients and radiomic features. A nomogram-revised risk index (NRI) plus MRI radiomics signature (NRI-M) was developed, and compared with the NRI. RESULTS: The 2 distinct type I and II groups of the MRI radiomics signatures were identified. The 5-year OS rates between the type I and type II groups were 87.2% versus 67.3% (P = 0.002) in all patients, and 88.8% versus 69.2% (P = 0.003) in early-stage patients. The discrimination and calibration of the NRI-M for OS prediction demonstrated a better performance than that of either MRI radiomics or NRI, with a mean area under curve (AUC) of 0.748 and 0.717 for predicting the 5-year OS in all-stages and early-stage patients. CONCLUSIONS: The NRI-M model has good performance for predicting the prognosis of ENKTCL and may help design clinical trials and improve clinical decision making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10557-3.
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spelling pubmed-98789262023-01-27 Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma Zhao, Yu-Ting Chen, Si-Ye Liu, Xin Yang, Yong Chen, Bo Song, Yong-Wen Fang, Hui Jin, Jing Liu, Yue-Ping Jing, Hao Tang, Yuan Li, Ning Lu, Ning-Ning Wang, Shu-Lian Ouyang, Han Hu, Chen Liu, Jin Wang, Zhi Chen, Fan Yin, Lin Zhong, Qiu-Zi Men, Kuo Dai, Jian-Rong Qi, Shu-Nan Li, Ye-Xiong BMC Cancer Research BACKGROUND: Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It’s important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. METHODS: Patients with ENKTCL in a prospectively cohort were systemically reviewed and all the pretreatment MRI were acquisitioned. An unsupervised spectral clustering method was used to identify risk groups of patients and radiomic features. A nomogram-revised risk index (NRI) plus MRI radiomics signature (NRI-M) was developed, and compared with the NRI. RESULTS: The 2 distinct type I and II groups of the MRI radiomics signatures were identified. The 5-year OS rates between the type I and type II groups were 87.2% versus 67.3% (P = 0.002) in all patients, and 88.8% versus 69.2% (P = 0.003) in early-stage patients. The discrimination and calibration of the NRI-M for OS prediction demonstrated a better performance than that of either MRI radiomics or NRI, with a mean area under curve (AUC) of 0.748 and 0.717 for predicting the 5-year OS in all-stages and early-stage patients. CONCLUSIONS: The NRI-M model has good performance for predicting the prognosis of ENKTCL and may help design clinical trials and improve clinical decision making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10557-3. BioMed Central 2023-01-25 /pmc/articles/PMC9878926/ /pubmed/36698118 http://dx.doi.org/10.1186/s12885-023-10557-3 Text en © The Author(s) 2023 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhao, Yu-Ting
Chen, Si-Ye
Liu, Xin
Yang, Yong
Chen, Bo
Song, Yong-Wen
Fang, Hui
Jin, Jing
Liu, Yue-Ping
Jing, Hao
Tang, Yuan
Li, Ning
Lu, Ning-Ning
Wang, Shu-Lian
Ouyang, Han
Hu, Chen
Liu, Jin
Wang, Zhi
Chen, Fan
Yin, Lin
Zhong, Qiu-Zi
Men, Kuo
Dai, Jian-Rong
Qi, Shu-Nan
Li, Ye-Xiong
Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title_full Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title_fullStr Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title_full_unstemmed Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title_short Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
title_sort risk stratification and prognostic value of multi-modal mri-based radiomics for extranodal nasal-type nk/t-cell lymphoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878926/
https://www.ncbi.nlm.nih.gov/pubmed/36698118
http://dx.doi.org/10.1186/s12885-023-10557-3
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