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MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively

BACKGROUND: Lymph‐vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI. PURPOSE: To develop and validate an axial T(1) contrast‐enhanced (CE) MR‐based radiomics nomogram that...

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Autores principales: Li, Zhicong, Li, Hailin, Wang, Shiyu, Dong, Di, Yin, Fangfang, Chen, An, Wang, Siwen, Zhao, Guangming, Fang, Mengjie, Tian, Jie, Wu, Sufang, Wang, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587470/
https://www.ncbi.nlm.nih.gov/pubmed/30362652
http://dx.doi.org/10.1002/jmri.26531
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author Li, Zhicong
Li, Hailin
Wang, Shiyu
Dong, Di
Yin, Fangfang
Chen, An
Wang, Siwen
Zhao, Guangming
Fang, Mengjie
Tian, Jie
Wu, Sufang
Wang, Han
author_facet Li, Zhicong
Li, Hailin
Wang, Shiyu
Dong, Di
Yin, Fangfang
Chen, An
Wang, Siwen
Zhao, Guangming
Fang, Mengjie
Tian, Jie
Wu, Sufang
Wang, Han
author_sort Li, Zhicong
collection PubMed
description BACKGROUND: Lymph‐vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI. PURPOSE: To develop and validate an axial T(1) contrast‐enhanced (CE) MR‐based radiomics nomogram that incorporated a radiomics signature and some clinical parameters for predicting LVSI of cervical cancer preoperatively. STUDY TYPE: Retrospective. POPULATION: In all, 105 patients were randomly divided into two cohorts at a 2:1 ratio. FIELD STRENGTH/SEQUENCE: T(1) CE MRI sequences at 1.5T. ASSESSMENT: Univariate analysis was performed on the radiomics features and clinical parameters. Multivariate analysis was performed to determine the optimal feature subset. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of prediction model and radiomics nomogram. STATISTICAL TESTS: The Mann–Whitney U‐test and the chi‐square test were used to evaluate the performance of clinical characteristics and LVSI status by pathology. The minimum‐redundancy/maximum‐relevance and recursive feature elimination methods were applied to select the features. The radiomics model was constructed using logistic regression. RESULTS: Three radiomics features and one clinical characteristic were selected. The radiomics nomogram showed favorable discrimination between LVSI and non‐LVSI groups. The AUC was 0.754 (95% confidence interval [CI], 0.6326–0.8745) in the training cohort and 0.727 (95% CI, 0.5449–0.9097) in the validation cohort. The specificity and sensitivity were 0.756 and 0.828 in the training cohort and 0.773 and 0.692 in the validation cohort. DATA CONCLUSION: T(1) CE MR‐based radiomics nomogram serves as a noninvasive biomarker in the prediction of LVSI in patients with cervical cancer preoperatively. Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1420–1426.
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spelling pubmed-65874702019-07-02 MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively Li, Zhicong Li, Hailin Wang, Shiyu Dong, Di Yin, Fangfang Chen, An Wang, Siwen Zhao, Guangming Fang, Mengjie Tian, Jie Wu, Sufang Wang, Han J Magn Reson Imaging Original Research BACKGROUND: Lymph‐vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI. PURPOSE: To develop and validate an axial T(1) contrast‐enhanced (CE) MR‐based radiomics nomogram that incorporated a radiomics signature and some clinical parameters for predicting LVSI of cervical cancer preoperatively. STUDY TYPE: Retrospective. POPULATION: In all, 105 patients were randomly divided into two cohorts at a 2:1 ratio. FIELD STRENGTH/SEQUENCE: T(1) CE MRI sequences at 1.5T. ASSESSMENT: Univariate analysis was performed on the radiomics features and clinical parameters. Multivariate analysis was performed to determine the optimal feature subset. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of prediction model and radiomics nomogram. STATISTICAL TESTS: The Mann–Whitney U‐test and the chi‐square test were used to evaluate the performance of clinical characteristics and LVSI status by pathology. The minimum‐redundancy/maximum‐relevance and recursive feature elimination methods were applied to select the features. The radiomics model was constructed using logistic regression. RESULTS: Three radiomics features and one clinical characteristic were selected. The radiomics nomogram showed favorable discrimination between LVSI and non‐LVSI groups. The AUC was 0.754 (95% confidence interval [CI], 0.6326–0.8745) in the training cohort and 0.727 (95% CI, 0.5449–0.9097) in the validation cohort. The specificity and sensitivity were 0.756 and 0.828 in the training cohort and 0.773 and 0.692 in the validation cohort. DATA CONCLUSION: T(1) CE MR‐based radiomics nomogram serves as a noninvasive biomarker in the prediction of LVSI in patients with cervical cancer preoperatively. Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1420–1426. John Wiley and Sons Inc. 2018-10-26 2019-05 /pmc/articles/PMC6587470/ /pubmed/30362652 http://dx.doi.org/10.1002/jmri.26531 Text en © 2018 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Research
Li, Zhicong
Li, Hailin
Wang, Shiyu
Dong, Di
Yin, Fangfang
Chen, An
Wang, Siwen
Zhao, Guangming
Fang, Mengjie
Tian, Jie
Wu, Sufang
Wang, Han
MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title_full MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title_fullStr MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title_full_unstemmed MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title_short MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
title_sort mr‐based radiomics nomogram of cervical cancer in prediction of the lymph‐vascular space invasion preoperatively
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587470/
https://www.ncbi.nlm.nih.gov/pubmed/30362652
http://dx.doi.org/10.1002/jmri.26531
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