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Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma

BRAF(V600E) is the most common mutated gene in thyroid cancer and is most closely related to papillary thyroid carcinoma(PTC). We investigated the value of elasticity and grayscale ultrasonography for predicting BRAF(V600E) mutations in PTC. METHODS: 138 patients with PTC who underwent preoperative...

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Autores principales: Wang, Yu-guo, Xu, Fei-ju, Agyekum, Enock Adjei, Xiang, Hong, Wang, Yuan-dong, Zhang, Jin, Sun, Hui, Zhang, Guo-liang, Bo, Xiang-shu, Lv, Wen-zhi, Wang, Xian, Hu, Shu-dong, Qian, Xiao-qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9074386/
https://www.ncbi.nlm.nih.gov/pubmed/35527993
http://dx.doi.org/10.3389/fendo.2022.872153
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author Wang, Yu-guo
Xu, Fei-ju
Agyekum, Enock Adjei
Xiang, Hong
Wang, Yuan-dong
Zhang, Jin
Sun, Hui
Zhang, Guo-liang
Bo, Xiang-shu
Lv, Wen-zhi
Wang, Xian
Hu, Shu-dong
Qian, Xiao-qin
author_facet Wang, Yu-guo
Xu, Fei-ju
Agyekum, Enock Adjei
Xiang, Hong
Wang, Yuan-dong
Zhang, Jin
Sun, Hui
Zhang, Guo-liang
Bo, Xiang-shu
Lv, Wen-zhi
Wang, Xian
Hu, Shu-dong
Qian, Xiao-qin
author_sort Wang, Yu-guo
collection PubMed
description BRAF(V600E) is the most common mutated gene in thyroid cancer and is most closely related to papillary thyroid carcinoma(PTC). We investigated the value of elasticity and grayscale ultrasonography for predicting BRAF(V600E) mutations in PTC. METHODS: 138 patients with PTC who underwent preoperative ultrasound between January 2014 and 2021 were retrospectively examined. Patients were divided into BRAF(V600E) mutation-free group (n=75) and BRAF(V600E) mutation group (n=63). Patients were randomly divided into training (n=96) and test (n=42) groups. A total of 479 radiomic features were extracted from the grayscale and elasticity ultra-sonograms. Regression analysis was done to select the features that provided the most information. Then, 10-fold cross-validation was used to compare the performance of different classification algorithms. Logistic regression was used to predict BRAF(V600E) mutations. RESULTS: Eight radiomics features were extracted from the grayscale ultrasonogram, and five radiomics features were extracted from the elasticity ultrasonogram. Three models were developed using these radiomic features. The models were derived from elasticity ultrasound, grayscale ultrasound, and a combination of grayscale and elasticity ultrasound, with areas under the curve (AUC) 0.952 [95% confidence interval (CI), 0.914−0.990], AUC 0.792 [95% CI, 0.703−0.882], and AUC 0.985 [95% CI, 0.965−1.000] in the training dataset, AUC 0.931 [95% CI, 0.841−1.000], AUC 0. 725 [95% CI, 0.569−0.880], and AUC 0.938 [95% CI, 0.851−1.000] in the test dataset, respectively. CONCLUSION: The radiomic model based on grayscale and elasticity ultrasound had a good predictive value for BRAF(V600E) gene mutations in patients with PTC.
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spelling pubmed-90743862022-05-07 Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma Wang, Yu-guo Xu, Fei-ju Agyekum, Enock Adjei Xiang, Hong Wang, Yuan-dong Zhang, Jin Sun, Hui Zhang, Guo-liang Bo, Xiang-shu Lv, Wen-zhi Wang, Xian Hu, Shu-dong Qian, Xiao-qin Front Endocrinol (Lausanne) Endocrinology BRAF(V600E) is the most common mutated gene in thyroid cancer and is most closely related to papillary thyroid carcinoma(PTC). We investigated the value of elasticity and grayscale ultrasonography for predicting BRAF(V600E) mutations in PTC. METHODS: 138 patients with PTC who underwent preoperative ultrasound between January 2014 and 2021 were retrospectively examined. Patients were divided into BRAF(V600E) mutation-free group (n=75) and BRAF(V600E) mutation group (n=63). Patients were randomly divided into training (n=96) and test (n=42) groups. A total of 479 radiomic features were extracted from the grayscale and elasticity ultra-sonograms. Regression analysis was done to select the features that provided the most information. Then, 10-fold cross-validation was used to compare the performance of different classification algorithms. Logistic regression was used to predict BRAF(V600E) mutations. RESULTS: Eight radiomics features were extracted from the grayscale ultrasonogram, and five radiomics features were extracted from the elasticity ultrasonogram. Three models were developed using these radiomic features. The models were derived from elasticity ultrasound, grayscale ultrasound, and a combination of grayscale and elasticity ultrasound, with areas under the curve (AUC) 0.952 [95% confidence interval (CI), 0.914−0.990], AUC 0.792 [95% CI, 0.703−0.882], and AUC 0.985 [95% CI, 0.965−1.000] in the training dataset, AUC 0.931 [95% CI, 0.841−1.000], AUC 0. 725 [95% CI, 0.569−0.880], and AUC 0.938 [95% CI, 0.851−1.000] in the test dataset, respectively. CONCLUSION: The radiomic model based on grayscale and elasticity ultrasound had a good predictive value for BRAF(V600E) gene mutations in patients with PTC. Frontiers Media S.A. 2022-04-22 /pmc/articles/PMC9074386/ /pubmed/35527993 http://dx.doi.org/10.3389/fendo.2022.872153 Text en Copyright © 2022 Wang, Xu, Agyekum, Xiang, Wang, Zhang, Sun, Zhang, Bo, Lv, Wang, Hu and Qian 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 Endocrinology
Wang, Yu-guo
Xu, Fei-ju
Agyekum, Enock Adjei
Xiang, Hong
Wang, Yuan-dong
Zhang, Jin
Sun, Hui
Zhang, Guo-liang
Bo, Xiang-shu
Lv, Wen-zhi
Wang, Xian
Hu, Shu-dong
Qian, Xiao-qin
Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title_full Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title_fullStr Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title_full_unstemmed Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title_short Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAF(V600E) Mutations in Papillary Thyroid Carcinoma
title_sort radiomic model for determining the value of elasticity and grayscale ultrasound diagnoses for predicting braf(v600e) mutations in papillary thyroid carcinoma
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9074386/
https://www.ncbi.nlm.nih.gov/pubmed/35527993
http://dx.doi.org/10.3389/fendo.2022.872153
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