MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma
Tingting Zheng,1,* Wenjuan Hu,1,* Hao Wang,1 Xiaoli Xie,2 Lang Tang,3 Weiyan Liu,4 Pu-Yeh Wu,5 Jingjing Xu,1,* Bin Song1,* 1Department of Radiology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 2Department of Pathology, Minhang Hospital, F...
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Dove Medical Press
2023-01-01
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Series: | Journal of Multidisciplinary Healthcare |
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author | Zheng T Hu W Wang H Xie X Tang L Liu W Wu PY Xu J Song B |
author_facet | Zheng T Hu W Wang H Xie X Tang L Liu W Wu PY Xu J Song B |
author_sort | Zheng T |
collection | DOAJ |
description | Tingting Zheng,1,* Wenjuan Hu,1,* Hao Wang,1 Xiaoli Xie,2 Lang Tang,3 Weiyan Liu,4 Pu-Yeh Wu,5 Jingjing Xu,1,* Bin Song1,* 1Department of Radiology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 2Department of Pathology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 3Department of Ultrasound, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 4Department of General Surgery, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 5GE Healthcare, MR Research China, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin Song; Jingjing Xu, Department of Radiology, Minhang Hospital, Fudan University, No. 170, Xinsong Road, Minhang District, Shanghai, 201199, People’s Republic of China, Email songbin@fudan.edu.cn; sb72778@189.cnPurpose: BRAF V600E mutation can compensate for the low detection rate by fine-needle aspiration (FNA) and is related to aggressiveness and lymph node metastasis. This study aimed to investigate the relationship between texture analysis features based on magnetic resonance imaging (MRI) and mutations.Methods: Retrospective analysis was performed on patients with postoperative pathology confirmed papillary thyroid carcinoma (PTC) from 2017 to 2021. One thousand one hundred and thirty-two texture features were extracted from T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) separately by outlining the tumor volume of interest (VOI). Univariate, minimum redundancy maximum relevance (mRMR), and multivariate analyses were used for feature selection to construct 3 models (T2WI, CE-T1WI, and combined model) to predict mutation. The reproducibility between observers was evaluated by intraclass correlation coefficient (ICC). Receiver operating characteristic (ROC) analysis was used to assess the performance of models. The diagnostic performance of the optimal cut-off value of models were calculated and validated by 10-fold cross-validation.Results: A total of 80 PTCs (22 BRAF V600E wild-type and 58 BRAF V600E mutant) were included in our study. Good interobserver agreement was found on texture features we selected (all ICCs > 0.75). The area under the ROC curves (AUCs) for the T2WI model, CE-T1WI model, and combined model were 0.83 (95% CI: 0.75– 0.91), 0.83 (95% CI: 0.73– 0.90), and 0.88 (95% CI: 0.81– 0.94), respectively. The accuracy, sensitivity, specificity, PPV, and NPV were 0.776, 0.679, 0.905, 0.905, and 0.679 for the T2WI model at a cut-off value of 0.674; 0.755, 0.750, 0.762, 0.808, and 0.696 for the CE-T1WI model at a cut-off value of 0.573; 0.816, 0.893, 0.714, 0.806, and 0.833 for the combined model at a cut-off value of 0.420.Conclusion: MRI-based texture analysis could be a potential method for predicting BRAF V600E mutation in PTC preoperatively.Keywords: magnetic resonance imaging, texture analysis, radiomics, papillary thyroid carcinoma, BRAF V600E |
first_indexed | 2024-04-10T23:35:17Z |
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language | English |
last_indexed | 2024-04-10T23:35:17Z |
publishDate | 2023-01-01 |
publisher | Dove Medical Press |
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spelling | doaj.art-a6628eb2e7924697ab1d584544f75b7d2023-01-11T19:18:15ZengDove Medical PressJournal of Multidisciplinary Healthcare1178-23902023-01-01Volume 1611080837MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid CarcinomaZheng THu WWang HXie XTang LLiu WWu PYXu JSong BTingting Zheng,1,* Wenjuan Hu,1,* Hao Wang,1 Xiaoli Xie,2 Lang Tang,3 Weiyan Liu,4 Pu-Yeh Wu,5 Jingjing Xu,1,* Bin Song1,* 1Department of Radiology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 2Department of Pathology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 3Department of Ultrasound, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 4Department of General Surgery, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China; 5GE Healthcare, MR Research China, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin Song; Jingjing Xu, Department of Radiology, Minhang Hospital, Fudan University, No. 170, Xinsong Road, Minhang District, Shanghai, 201199, People’s Republic of China, Email songbin@fudan.edu.cn; sb72778@189.cnPurpose: BRAF V600E mutation can compensate for the low detection rate by fine-needle aspiration (FNA) and is related to aggressiveness and lymph node metastasis. This study aimed to investigate the relationship between texture analysis features based on magnetic resonance imaging (MRI) and mutations.Methods: Retrospective analysis was performed on patients with postoperative pathology confirmed papillary thyroid carcinoma (PTC) from 2017 to 2021. One thousand one hundred and thirty-two texture features were extracted from T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) separately by outlining the tumor volume of interest (VOI). Univariate, minimum redundancy maximum relevance (mRMR), and multivariate analyses were used for feature selection to construct 3 models (T2WI, CE-T1WI, and combined model) to predict mutation. The reproducibility between observers was evaluated by intraclass correlation coefficient (ICC). Receiver operating characteristic (ROC) analysis was used to assess the performance of models. The diagnostic performance of the optimal cut-off value of models were calculated and validated by 10-fold cross-validation.Results: A total of 80 PTCs (22 BRAF V600E wild-type and 58 BRAF V600E mutant) were included in our study. Good interobserver agreement was found on texture features we selected (all ICCs > 0.75). The area under the ROC curves (AUCs) for the T2WI model, CE-T1WI model, and combined model were 0.83 (95% CI: 0.75– 0.91), 0.83 (95% CI: 0.73– 0.90), and 0.88 (95% CI: 0.81– 0.94), respectively. The accuracy, sensitivity, specificity, PPV, and NPV were 0.776, 0.679, 0.905, 0.905, and 0.679 for the T2WI model at a cut-off value of 0.674; 0.755, 0.750, 0.762, 0.808, and 0.696 for the CE-T1WI model at a cut-off value of 0.573; 0.816, 0.893, 0.714, 0.806, and 0.833 for the combined model at a cut-off value of 0.420.Conclusion: MRI-based texture analysis could be a potential method for predicting BRAF V600E mutation in PTC preoperatively.Keywords: magnetic resonance imaging, texture analysis, radiomics, papillary thyroid carcinoma, BRAF V600Ehttps://www.dovepress.com/mri-based-texture-analysis-for-preoperative-prediction-of-braf-v600e-m-peer-reviewed-fulltext-article-JMDHmagnetic resonance imagingtexture analysisradiomicspapillary thyroid carcinomabraf v600e |
spellingShingle | Zheng T Hu W Wang H Xie X Tang L Liu W Wu PY Xu J Song B MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma Journal of Multidisciplinary Healthcare magnetic resonance imaging texture analysis radiomics papillary thyroid carcinoma braf v600e |
title | MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma |
title_full | MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma |
title_fullStr | MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma |
title_full_unstemmed | MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma |
title_short | MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma |
title_sort | mri based texture analysis for preoperative prediction of braf v600e mutation in papillary thyroid carcinoma |
topic | magnetic resonance imaging texture analysis radiomics papillary thyroid carcinoma braf v600e |
url | https://www.dovepress.com/mri-based-texture-analysis-for-preoperative-prediction-of-braf-v600e-m-peer-reviewed-fulltext-article-JMDH |
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