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MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer

BACKGROUND: The depth of cervical stromal invasion is one of the important prognostic factors affecting decision-making for early stage cervical cancer (CC). This study aimed to develop and validate a T2-weighted imaging (T2WI)-based radiomics model and explore independent risk factors (factors with...

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Autores principales: Ren, Jing, Li, Yuan, Yang, Jun-Jun, Zhao, Jia, Xiang, Yang, Xia, Chen, Cao, Ying, Chen, Bo, Guan, Hui, Qi, Ya-Fei, Tang, Wen, Chen, Kuan, He, Yong-Lan, Jin, Zheng-Yu, Xue, Hua-Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800977/
https://www.ncbi.nlm.nih.gov/pubmed/35092505
http://dx.doi.org/10.1186/s13244-022-01156-0
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author Ren, Jing
Li, Yuan
Yang, Jun-Jun
Zhao, Jia
Xiang, Yang
Xia, Chen
Cao, Ying
Chen, Bo
Guan, Hui
Qi, Ya-Fei
Tang, Wen
Chen, Kuan
He, Yong-Lan
Jin, Zheng-Yu
Xue, Hua-Dan
author_facet Ren, Jing
Li, Yuan
Yang, Jun-Jun
Zhao, Jia
Xiang, Yang
Xia, Chen
Cao, Ying
Chen, Bo
Guan, Hui
Qi, Ya-Fei
Tang, Wen
Chen, Kuan
He, Yong-Lan
Jin, Zheng-Yu
Xue, Hua-Dan
author_sort Ren, Jing
collection PubMed
description BACKGROUND: The depth of cervical stromal invasion is one of the important prognostic factors affecting decision-making for early stage cervical cancer (CC). This study aimed to develop and validate a T2-weighted imaging (T2WI)-based radiomics model and explore independent risk factors (factors with statistical significance in both univariate and multivariate analyses) of middle or deep stromal invasion in early stage CC. METHODS: Between March 2017 and March 2021, a total of 234 International Federation of Gynecology and Obstetrics IB1-IIA1 CC patients were enrolled and randomly divided into a training cohort (n = 188) and a validation cohort (n = 46). The radiomics features of each patient were extracted from preoperative sagittal T2WI, and key features were selected. After independent risk factors were identified, a combined model and nomogram incorporating radiomics signature and independent risk factors were developed. Diagnostic accuracy of radiologists was also evaluated. RESULTS: The maximal tumor diameter (MTD) on magnetic resonance imaging was identified as an independent risk factor. In the validation cohort, the radiomics model, MTD, and combined model showed areas under the curve of 0.879, 0.844, and 0.886. The radiomics model and combined model showed the same sensitivity and specificity of 87.9% and 84.6%, which were better than radiologists (sensitivity, senior = 75.7%, junior = 63.6%; specificity, senior = 69.2%, junior = 53.8%) and MTD (sensitivity = 69.7%, specificity = 76.9%). CONCLUSION: MRI-based radiomics analysis outperformed radiologists for the preoperative diagnosis of middle or deep stromal invasion in early stage CC, and the probability can be individually evaluated by a nomogram.
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spelling pubmed-88009772022-02-02 MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer Ren, Jing Li, Yuan Yang, Jun-Jun Zhao, Jia Xiang, Yang Xia, Chen Cao, Ying Chen, Bo Guan, Hui Qi, Ya-Fei Tang, Wen Chen, Kuan He, Yong-Lan Jin, Zheng-Yu Xue, Hua-Dan Insights Imaging Original Article BACKGROUND: The depth of cervical stromal invasion is one of the important prognostic factors affecting decision-making for early stage cervical cancer (CC). This study aimed to develop and validate a T2-weighted imaging (T2WI)-based radiomics model and explore independent risk factors (factors with statistical significance in both univariate and multivariate analyses) of middle or deep stromal invasion in early stage CC. METHODS: Between March 2017 and March 2021, a total of 234 International Federation of Gynecology and Obstetrics IB1-IIA1 CC patients were enrolled and randomly divided into a training cohort (n = 188) and a validation cohort (n = 46). The radiomics features of each patient were extracted from preoperative sagittal T2WI, and key features were selected. After independent risk factors were identified, a combined model and nomogram incorporating radiomics signature and independent risk factors were developed. Diagnostic accuracy of radiologists was also evaluated. RESULTS: The maximal tumor diameter (MTD) on magnetic resonance imaging was identified as an independent risk factor. In the validation cohort, the radiomics model, MTD, and combined model showed areas under the curve of 0.879, 0.844, and 0.886. The radiomics model and combined model showed the same sensitivity and specificity of 87.9% and 84.6%, which were better than radiologists (sensitivity, senior = 75.7%, junior = 63.6%; specificity, senior = 69.2%, junior = 53.8%) and MTD (sensitivity = 69.7%, specificity = 76.9%). CONCLUSION: MRI-based radiomics analysis outperformed radiologists for the preoperative diagnosis of middle or deep stromal invasion in early stage CC, and the probability can be individually evaluated by a nomogram. Springer International Publishing 2022-01-29 /pmc/articles/PMC8800977/ /pubmed/35092505 http://dx.doi.org/10.1186/s13244-022-01156-0 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 Original Article
Ren, Jing
Li, Yuan
Yang, Jun-Jun
Zhao, Jia
Xiang, Yang
Xia, Chen
Cao, Ying
Chen, Bo
Guan, Hui
Qi, Ya-Fei
Tang, Wen
Chen, Kuan
He, Yong-Lan
Jin, Zheng-Yu
Xue, Hua-Dan
MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title_full MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title_fullStr MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title_full_unstemmed MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title_short MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
title_sort mri-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800977/
https://www.ncbi.nlm.nih.gov/pubmed/35092505
http://dx.doi.org/10.1186/s13244-022-01156-0
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