Radiomics in predicting mutation status for thyroid cancer: A preliminary study using radiomics features for predicting BRAFV600E mutations in papillary thyroid carcinoma
Radiomics in predicting mutation status for thyroid cancer: A preliminary study using radiomics features for predicting BRAFV600E mutations in papillary thyroid carcinoma
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DOI：
10.1371/journal.pone.0228968
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发表时间：
2020-02-13
期刊：
影响因子：
3.7
通讯作者：
Kwak, Jin Young
中科院分区：
文献类型：
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作者：
Yoon, Jung Hyun;Han, Kyunghwa;Kwak, Jin Young
目的评价超声（US）放射组学技术是否能够预测诊断为甲状腺乳头状癌（PTC）患者BRAF（V600E）突变的存在。方法纳入2015年12月至2017年5月接受手术治疗的PTC患者527例（培训：387例，验证：140例）。所有患者手术标本均进行BRAF（V600E）突变分析。527例患者术前US图像进行特征提取（PTC平均大小：16.4mm +/- 7.9，范围：10-85 mm）。采用最小绝对收缩和选择算子（LASSO）回归模型生成放射组学评分。采用单变量/多变量logistic回归分析评估Radiomics评分等因素对BRAF（V600E）突变的预测作用。包括常规PTC的亚组分析
PurposeTo evaluate whether if ultrasonography (US)-based radiomics enables prediction of the presence of BRAF(V600E) mutations among patients diagnosed as papillary thyroid carcninoma (PTC).MethodsFrom December 2015 to May 2017, 527 patients who had been treated surgically for PTC were included (training: 387, validation: 140). All patients had BRAF(V600E) mutation analysis performed on surgical specimen. Feature extraction was performed using preoperative US images of the 527 patients (mean size of PTC: 16.4mm +/- 7.9, range, 10-85 mm). A Radiomics Score was generated by using the least absolute shrinkage and selection operator (LASSO) regression model. Univariable/multivariable logistic regression analysis was performed to evaluate the factors including Radiomics Score in predicting BRAF(V600E) mutation. Subgroup analysis including conventional PTC