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Objective To evaluate the association between quantitative ultrasonographic features and clinical ,pathological and immunohistochemical features of triple negative invasive breast carcinoma( TNBC) . Methods With the ethical approval , 96 patients who were pathologically confirmed as TNBC were retrospectively reviewed . All patients were sub-grouped according to age ,tumor size ,pathological grade , Ki67 expression level and human epidermal growth factor receptor 2 ( HER-2) score .Ultrasound images were segmented for the breast carcinoma mass using a phase-based active contour model . The high-throughput radiomics features were extracted based on the two-dimensional sonographic features . There were 460 features extracted from each ultrasound image . A series of computer aided algorithms including K-svd algorithm ,sparse representation ,support vector machine ( SVM ) and radial basis function were used to determine the high-throughput sonographic features that were highly correlated to clinical ,pathological and immunohistochemical features of TNBC . The performance efficacy was expressed by accuracy and area under curve ( AUC) of the ROC curve . Results The high-throughput ultrasonographic features of invasive TNBC could predict its pathological grade ,Ki67 level and HER-2 score with the accuracy 92 .2％ -96 .9％and AUC 98 .7％ -99 .9％ . There were 82 radiomics features selected for predicting the pathological grade of TNBC , the feature with the maximum weight was the elliptic-normalized eccentricity based on morphological features . There were 100 features selected for predicting the Ki67 expression level ,the feature with the maximum weight was the standard deviation of the annular region based on the boundary texture features . There were 85 features selected for the prediction of HER-2 score ,the most powerful parameter was the intensity based on NGTDM texture features . Conclusions Quantitative high-throughput ultrasonographic features are correlated with the pathological and immunohistochemical characteristics of invasive TNBC . High-throughput ultrasonographic features are valuable in predicting biological behavior of TNBC .
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Objective To compare the difference of diagnostic ability between ultrasound radiomics ( USR) and different conventional imaging models of central neck ( Ⅵ ) lymph node metastasis in papillary thyroid carcinoma ( PTC) . Methods A training set of 609 cases was set up . USR features were extracted and screened by USR method . A weighted formula was established to calculate the USR score of each patient by ultrasound image . T he USR score of the best diagnostic ability was obtained by statistical method and set as the diagnostic criterion . A test set of 326 cases was established to compare the diagnostic ability of USR score with ultrasound ( US ) ,computed tomography ( CT ) and US combined CT . Results T he accuracy ,sensitivity ,specificity ,area under ROC curve and Youden index of USR score in test set were 0 .804 ,0 .867 ,0 .770 ,0 .766 ,0 .533 ,respectively ,which were significantly higher than the corresponding values of US ,CT and US combined CT ( all P ＝ 0 .000 ) . Conclusions USR score obtained with USR method can effectively predict lymph node metastasis in Ⅵ region of PTC . T he diagnostic efficiency and clinical value of USR score were significantly higher than those of conventional medical imaging models .
ABSTRACT
Objective@#To compare the difference of diagnostic ability between ultrasound radiomics (USR) and different conventional imaging models of central neck (Ⅵ) lymph node metastasis in papillary thyroid carcinoma (PTC).@*Methods@#A training set of 609 cases was set up. USR features were extracted and screened by USR method. A weighted formula was established to calculate the USR score of each patient by ultrasound image. The USR score of the best diagnostic ability was obtained by statistical method and set as the diagnostic criterion. A test set of 326 cases was established to compare the diagnostic ability of USR score with ultrasound (US), computed tomography (CT) and US combined CT.@*Results@#The accuracy, sensitivity, specificity, area under ROC curve and Youden index of USR score in test set were 0.804, 0.867, 0.770, 0.766, 0.533, respectively, which were significantly higher than the corresponding values of US, CT and US combined CT(all P=0.000).@*Conclusions@#USR score obtained with USR method can effectively predict lymph node metastasis in Ⅵ region of PTC. The diagnostic efficiency and clinical value of USR score were significantly higher than those of conventional medical imaging models.