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Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study

Medical diagnostic imaging is essential for the differential diagnosis of cervical lymphadenopathy. Here we develop an ultrasound radiomics method for accurately differentiating cervical lymph node tuberculosis (LNTB), cervical lymphoma, reactive lymph node hyperplasia, and metastatic lymph nodes es...

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Autores principales: Liu, Yajing, Chen, Jifan, Zhang, Chao, Li, Qunying, Zhou, Hang, Zeng, Yiqing, Zhang, Ying, Li, Jia, Xv, Wen, Li, Wencun, Zhu, Jianing, Zhao, Yanan, Chen, Qin, Huang, Yi, Li, Hongming, Huang, Ying, Yang, Gaoyi, Huang, Pintong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152112/
https://www.ncbi.nlm.nih.gov/pubmed/35656511
http://dx.doi.org/10.3389/fonc.2022.856605
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author Liu, Yajing
Chen, Jifan
Zhang, Chao
Li, Qunying
Zhou, Hang
Zeng, Yiqing
Zhang, Ying
Li, Jia
Xv, Wen
Li, Wencun
Zhu, Jianing
Zhao, Yanan
Chen, Qin
Huang, Yi
Li, Hongming
Huang, Ying
Yang, Gaoyi
Huang, Pintong
author_facet Liu, Yajing
Chen, Jifan
Zhang, Chao
Li, Qunying
Zhou, Hang
Zeng, Yiqing
Zhang, Ying
Li, Jia
Xv, Wen
Li, Wencun
Zhu, Jianing
Zhao, Yanan
Chen, Qin
Huang, Yi
Li, Hongming
Huang, Ying
Yang, Gaoyi
Huang, Pintong
author_sort Liu, Yajing
collection PubMed
description Medical diagnostic imaging is essential for the differential diagnosis of cervical lymphadenopathy. Here we develop an ultrasound radiomics method for accurately differentiating cervical lymph node tuberculosis (LNTB), cervical lymphoma, reactive lymph node hyperplasia, and metastatic lymph nodes especially in the multi-operator, cross-machine, multicenter context. The inter-observer and intra-observer consistency of radiomics parameters from the region of interest were 0.8245 and 0.9228, respectively. The radiomics model showed good and repeatable diagnostic performance for multiple classification diagnosis of cervical lymphadenopathy, especially in LNTB (area under the curve, AUC: 0.673, 0.662, and 0.626) and cervical lymphoma (AUC: 0.623, 0.644, and 0.602) in the whole set, training set, and test set, respectively. However, the diagnostic performance of lymphadenopathy among skilled radiologists was varied (Kappa coefficient: 0.108, *p < 0.001). The diagnostic performance of radiomics is comparable and more reproducible compared with those of skilled radiologists. Our study offers a more comprehensive method for differentiating LNTB, cervical lymphoma, reactive lymph node hyperplasia, and metastatic LN.
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spelling pubmed-91521122022-06-01 Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study Liu, Yajing Chen, Jifan Zhang, Chao Li, Qunying Zhou, Hang Zeng, Yiqing Zhang, Ying Li, Jia Xv, Wen Li, Wencun Zhu, Jianing Zhao, Yanan Chen, Qin Huang, Yi Li, Hongming Huang, Ying Yang, Gaoyi Huang, Pintong Front Oncol Oncology Medical diagnostic imaging is essential for the differential diagnosis of cervical lymphadenopathy. Here we develop an ultrasound radiomics method for accurately differentiating cervical lymph node tuberculosis (LNTB), cervical lymphoma, reactive lymph node hyperplasia, and metastatic lymph nodes especially in the multi-operator, cross-machine, multicenter context. The inter-observer and intra-observer consistency of radiomics parameters from the region of interest were 0.8245 and 0.9228, respectively. The radiomics model showed good and repeatable diagnostic performance for multiple classification diagnosis of cervical lymphadenopathy, especially in LNTB (area under the curve, AUC: 0.673, 0.662, and 0.626) and cervical lymphoma (AUC: 0.623, 0.644, and 0.602) in the whole set, training set, and test set, respectively. However, the diagnostic performance of lymphadenopathy among skilled radiologists was varied (Kappa coefficient: 0.108, *p < 0.001). The diagnostic performance of radiomics is comparable and more reproducible compared with those of skilled radiologists. Our study offers a more comprehensive method for differentiating LNTB, cervical lymphoma, reactive lymph node hyperplasia, and metastatic LN. Frontiers Media S.A. 2022-05-17 /pmc/articles/PMC9152112/ /pubmed/35656511 http://dx.doi.org/10.3389/fonc.2022.856605 Text en Copyright © 2022 Liu, Chen, Zhang, Li, Zhou, Zeng, Zhang, Li, Xv, Li, Zhu, Zhao, Chen, Huang, Li, Huang, Yang and Huang 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
Liu, Yajing
Chen, Jifan
Zhang, Chao
Li, Qunying
Zhou, Hang
Zeng, Yiqing
Zhang, Ying
Li, Jia
Xv, Wen
Li, Wencun
Zhu, Jianing
Zhao, Yanan
Chen, Qin
Huang, Yi
Li, Hongming
Huang, Ying
Yang, Gaoyi
Huang, Pintong
Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title_full Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title_fullStr Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title_full_unstemmed Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title_short Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study
title_sort ultrasound-based radiomics can classify the etiology of cervical lymphadenopathy: a multi-center retrospective study
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152112/
https://www.ncbi.nlm.nih.gov/pubmed/35656511
http://dx.doi.org/10.3389/fonc.2022.856605
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