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The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization

Carcinoma in situ (CIS) of the uterine cervix is a precursor to cervical carcinoma. However, hysterectomy can be avoided in patients who can be treated by cone biopsy. Previous studies have shown that imaging-based approaches allow for the noninvasive visualization of cervical cancer, and radiomics...

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Autores principales: Song, Mengfan, Lin, Jing, Song, Fuzhen, Wu, Dan, Qian, Zhaoxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670468/
https://www.ncbi.nlm.nih.gov/pubmed/33199785
http://dx.doi.org/10.1038/s41598-020-76853-1
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author Song, Mengfan
Lin, Jing
Song, Fuzhen
Wu, Dan
Qian, Zhaoxia
author_facet Song, Mengfan
Lin, Jing
Song, Fuzhen
Wu, Dan
Qian, Zhaoxia
author_sort Song, Mengfan
collection PubMed
description Carcinoma in situ (CIS) of the uterine cervix is a precursor to cervical carcinoma. However, hysterectomy can be avoided in patients who can be treated by cone biopsy. Previous studies have shown that imaging-based approaches allow for the noninvasive visualization of cervical cancer, and radiomics has high accuracy in classifying cancer and predicting treatment outcome for different cancer types. To develop a magnetic resonance (MR)-based radiomics model for identifying residual disease in patients with CIS after cervical conization. Patients who had CIS after conization and finally underwent hysterectomy were collected to comprise a database to establish an imaging model for predicting the residual status after conization. Then, patients who opted for uterine preservation were classified as high-risk or low-risk patients according to the model. The disease-free survival was compared between the different risk groups using the Kaplan–Meier curve. The model built with the Boruta features outperformed the random forest model. Further validation with patients with uterine preservation showed that the patients classified as high risk were more likely to have tumor recurrence/residual disease in the follow-up period. In conclusion, radiomics can be used to identify residual disease in patients with CIS after cervical conization and could have the potential to predict recurrence in patients who opt for uterine preservation.
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spelling pubmed-76704682020-11-18 The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization Song, Mengfan Lin, Jing Song, Fuzhen Wu, Dan Qian, Zhaoxia Sci Rep Article Carcinoma in situ (CIS) of the uterine cervix is a precursor to cervical carcinoma. However, hysterectomy can be avoided in patients who can be treated by cone biopsy. Previous studies have shown that imaging-based approaches allow for the noninvasive visualization of cervical cancer, and radiomics has high accuracy in classifying cancer and predicting treatment outcome for different cancer types. To develop a magnetic resonance (MR)-based radiomics model for identifying residual disease in patients with CIS after cervical conization. Patients who had CIS after conization and finally underwent hysterectomy were collected to comprise a database to establish an imaging model for predicting the residual status after conization. Then, patients who opted for uterine preservation were classified as high-risk or low-risk patients according to the model. The disease-free survival was compared between the different risk groups using the Kaplan–Meier curve. The model built with the Boruta features outperformed the random forest model. Further validation with patients with uterine preservation showed that the patients classified as high risk were more likely to have tumor recurrence/residual disease in the follow-up period. In conclusion, radiomics can be used to identify residual disease in patients with CIS after cervical conization and could have the potential to predict recurrence in patients who opt for uterine preservation. Nature Publishing Group UK 2020-11-16 /pmc/articles/PMC7670468/ /pubmed/33199785 http://dx.doi.org/10.1038/s41598-020-76853-1 Text en © The Author(s) 2020 Open Access This 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/.
spellingShingle Article
Song, Mengfan
Lin, Jing
Song, Fuzhen
Wu, Dan
Qian, Zhaoxia
The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title_full The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title_fullStr The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title_full_unstemmed The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title_short The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
title_sort value of mr-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670468/
https://www.ncbi.nlm.nih.gov/pubmed/33199785
http://dx.doi.org/10.1038/s41598-020-76853-1
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