Cargando…
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1784878593597243392 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9878926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT zhaoyuting riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT chensiye riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT liuxin riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT yangyong riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT chenbo riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT songyongwen riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT fanghui riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT jinjing riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT liuyueping riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT jinghao riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT tangyuan riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT lining riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT luningning riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT wangshulian riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT ouyanghan riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT huchen riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT liujin riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT wangzhi riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT chenfan riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT yinlin riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT zhongqiuzi riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT menkuo riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT daijianrong riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT qishunan riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma AT liyexiong riskstratificationandprognosticvalueofmultimodalmribasedradiomicsforextranodalnasaltypenktcelllymphoma |