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Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia

OBJECTIVE: Prostate cancer and hyperplasia require different treatment strategies and have completely different outcomes; thus, preoperative identification of prostate cancer and hyperplasia is very important. The purpose of this study was to evaluate the application value of magnetic resonance imag...

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Autores principales: Gui, Shaogao, Lan, Min, Wang, Chaoxiong, Nie, Si, Fan, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047828/
https://www.ncbi.nlm.nih.gov/pubmed/35494065
http://dx.doi.org/10.3389/fonc.2022.859625
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author Gui, Shaogao
Lan, Min
Wang, Chaoxiong
Nie, Si
Fan, Bing
author_facet Gui, Shaogao
Lan, Min
Wang, Chaoxiong
Nie, Si
Fan, Bing
author_sort Gui, Shaogao
collection PubMed
description OBJECTIVE: Prostate cancer and hyperplasia require different treatment strategies and have completely different outcomes; thus, preoperative identification of prostate cancer and hyperplasia is very important. The purpose of this study was to evaluate the application value of magnetic resonance imaging (MRI)-derived radiomic nomogram based on T2-weighted images (T2WI) in differentiating prostate cancer and hyperplasia. MATERIALS AND METHODS: One hundred forty-six patients (66 cases of prostate cancer and 80 cases of prostate hyperplasia) who were confirmed by surgical pathology between September 2019 and September 2019 were selected. We manually delineated T2WI of all patients using ITK-SNAP software and radiomic analysis using Analysis Kit (AK) software. A total of 396 tumor texture features were extracted. Subsequently, the effective features were selected using the LASSO algorithm, and the radiomic feature model was constructed. Next, combined with independent clinical risk factors, a multivariate Logistic regression model was used to establish a radiomic nomogram. The receiver operator characteristic (ROC) curve was used to evaluate the prediction performance of the radiomic nomogram. Finally, the clinical application value of the nomogram was evaluated by decision curve analysis. RESULTS: The PSA and the selected imaging features were significantly correlated with the differential diagnosis of prostate cancer and hyperplasia. The radiomic model had good discrimination efficiency for prostate cancer and hyperplasia. The training set (AUC = 0.85; 95% CI: 0.77–0.92) and testing set (AUC = 0.84; 95% CI: 0.72–0.96) were effective. The radiomic nomogram, combined with the radiomic characteristics of MRI and independent clinical risk factors, showed better differentiation efficiency in the training set (AUC = 0.91; 95% CI: 0.85–0.97) and testing set (AUC = 0.90; 95% CI: 0.81–0.99). The decision curve showed the clinical application value of the radiomic nomogram. CONCLUSION: The radiomic nomogram of T2-MRI combined with clinical risk factors can easily identify prostate cancer and hyperplasia. It also provides suggestions for further clinical events.
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spelling pubmed-90478282022-04-29 Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia Gui, Shaogao Lan, Min Wang, Chaoxiong Nie, Si Fan, Bing Front Oncol Oncology OBJECTIVE: Prostate cancer and hyperplasia require different treatment strategies and have completely different outcomes; thus, preoperative identification of prostate cancer and hyperplasia is very important. The purpose of this study was to evaluate the application value of magnetic resonance imaging (MRI)-derived radiomic nomogram based on T2-weighted images (T2WI) in differentiating prostate cancer and hyperplasia. MATERIALS AND METHODS: One hundred forty-six patients (66 cases of prostate cancer and 80 cases of prostate hyperplasia) who were confirmed by surgical pathology between September 2019 and September 2019 were selected. We manually delineated T2WI of all patients using ITK-SNAP software and radiomic analysis using Analysis Kit (AK) software. A total of 396 tumor texture features were extracted. Subsequently, the effective features were selected using the LASSO algorithm, and the radiomic feature model was constructed. Next, combined with independent clinical risk factors, a multivariate Logistic regression model was used to establish a radiomic nomogram. The receiver operator characteristic (ROC) curve was used to evaluate the prediction performance of the radiomic nomogram. Finally, the clinical application value of the nomogram was evaluated by decision curve analysis. RESULTS: The PSA and the selected imaging features were significantly correlated with the differential diagnosis of prostate cancer and hyperplasia. The radiomic model had good discrimination efficiency for prostate cancer and hyperplasia. The training set (AUC = 0.85; 95% CI: 0.77–0.92) and testing set (AUC = 0.84; 95% CI: 0.72–0.96) were effective. The radiomic nomogram, combined with the radiomic characteristics of MRI and independent clinical risk factors, showed better differentiation efficiency in the training set (AUC = 0.91; 95% CI: 0.85–0.97) and testing set (AUC = 0.90; 95% CI: 0.81–0.99). The decision curve showed the clinical application value of the radiomic nomogram. CONCLUSION: The radiomic nomogram of T2-MRI combined with clinical risk factors can easily identify prostate cancer and hyperplasia. It also provides suggestions for further clinical events. Frontiers Media S.A. 2022-04-14 /pmc/articles/PMC9047828/ /pubmed/35494065 http://dx.doi.org/10.3389/fonc.2022.859625 Text en Copyright © 2022 Gui, Lan, Wang, Nie and Fan 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
Gui, Shaogao
Lan, Min
Wang, Chaoxiong
Nie, Si
Fan, Bing
Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title_full Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title_fullStr Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title_full_unstemmed Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title_short Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia
title_sort application value of radiomic nomogram in the differential diagnosis of prostate cancer and hyperplasia
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047828/
https://www.ncbi.nlm.nih.gov/pubmed/35494065
http://dx.doi.org/10.3389/fonc.2022.859625
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