Computer-Assisted Analysis of Ultrasonographic Features of Calcified Thyroid Nodules

Abstract

Brief Description of the Purpose of the Studyto determine computerized US features of calcified thyroid nodules that are useful in the differentiation between malignant and benign lesions.MethodsDigital US images of 99 pathologically-proven thyroid nodules with calcifications (malignant: benign = 78: 21) were evaluated. We designed and implemented a CAA scheme to quantitatively analyze the 24 US features of the calcified thyroid nodules based in two categories: morphology and calcification. We performed Student’s t-test and discriminant analysis and generated receiver operating characteristic (ROC) curves and the corresponding areas under the curve (AUC) in order to compare morphology, calcification and combined features.Main ResultsAmong the 24 analyzed features, 10/12 (83.3%) morphology and 7/12 (58.3%) calcification features showed significant differences between malignant and benign thyroid nodules (p < 0.05). The AUC values for morphology, calcification and combined features were 0.81 (95% CI, 0.75-0.86), 0.79 (95% CI, 0.73-0.84), and 0.86 (95% CI, 0.81-0.91), respectively. The combined features showed a significantly higher AUC value than morphology or calcification features alone (p < 0.05).Importance of the ConclusionsCombined morphology and calcification features from CAA had a significantly higher diagnostic performance in differentiating malignant from benign calcified thyroid nodules when compared to the use of morphology or calcification features alone. Brief Description of the Purpose of the Studyto determine computerized US features of calcified thyroid nodules that are useful in the differentiation between malignant and benign lesions. to determine computerized US features of calcified thyroid nodules that are useful in the differentiation between malignant and benign lesions. MethodsDigital US images of 99 pathologically-proven thyroid nodules with calcifications (malignant: benign = 78: 21) were evaluated. We designed and implemented a CAA scheme to quantitatively analyze the 24 US features of the calcified thyroid nodules based in two categories: morphology and calcification. We performed Student’s t-test and discriminant analysis and generated receiver operating characteristic (ROC) curves and the corresponding areas under the curve (AUC) in order to compare morphology, calcification and combined features. Digital US images of 99 pathologically-proven thyroid nodules with calcifications (malignant: benign = 78: 21) were evaluated. We designed and implemented a CAA scheme to quantitatively analyze the 24 US features of the calcified thyroid nodules based in two categories: morphology and calcification. We performed Student’s t-test and discriminant analysis and generated receiver operating characteristic (ROC) curves and the corresponding areas under the curve (AUC) in order to compare morphology, calcification and combined features. Main ResultsAmong the 24 analyzed features, 10/12 (83.3%) morphology and 7/12 (58.3%) calcification features showed significant differences between malignant and benign thyroid nodules (p < 0.05). The AUC values for morphology, calcification and combined features were 0.81 (95% CI, 0.75-0.86), 0.79 (95% CI, 0.73-0.84), and 0.86 (95% CI, 0.81-0.91), respectively. The combined features showed a significantly higher AUC value than morphology or calcification features alone (p < 0.05). Among the 24 analyzed features, 10/12 (83.3%) morphology and 7/12 (58.3%) calcification features showed significant differences between malignant and benign thyroid nodules (p < 0.05). The AUC values for morphology, calcification and combined features were 0.81 (95% CI, 0.75-0.86), 0.79 (95% CI, 0.73-0.84), and 0.86 (95% CI, 0.81-0.91), respectively. The combined features showed a significantly higher AUC value than morphology or calcification features alone (p < 0.05). Importance of the ConclusionsCombined morphology and calcification features from CAA had a significantly higher diagnostic performance in differentiating malignant from benign calcified thyroid nodules when compared to the use of morphology or calcification features alone. Combined morphology and calcification features from CAA had a significantly higher diagnostic performance in differentiating malignant from benign calcified thyroid nodules when compared to the use of morphology or calcification features alone.