Fig 1.
Representative image of tumor segmentation using thyroid US.
A diagonal region-of-interest (ROI) was drawn along the tumor border (red line) for feature extraction.
Table 1.
Demographic features of the total thyroid cancers and conventional PTCs<20-mm according to the presence of BRAFV600E mutation.
Fig 2.
Texture feature selection using the least absolute shrinkage and selection operator (LASSO) logistic regression model.
(A) Tuning parameter (lambda, λ) selection in the LASSO model used 10-fold cross validation for 527 thyroid cancers. The mean deviance (goodness-of-fit statistics, red dots) was plotted versus log(λ), error bars displaying the range of standard error. Dotted vertical lines were drawn at the point of minimum deviance (λ value = 0.03229), and at the point where maximum λ was obtained among errors smaller than the standard error of minimum deviance (λ value = 0.08984). (B) LASSO coefficient profiles of the 730 texture features. A coefficient profile was plotted versus log(λ). The gray vertical line was drawn at the value selected using 10-fold cross validation, where the optimal λ resulted in 8 nonzero coefficients. (C) Tuning parameter (lambda, λ) selection in the LASSO model used 10-fold cross validation for 389 conventional PTCs <20-mm. The mean deviance (goodness-of-fit statistics, red dots) was plotted versus log(λ), error bars displaying the range of standard error. Dotted vertical lines were drawn at the point of minimum deviance (λ value = 0.0329208), and at the point where maximum λ was obtained among errors smaller than the standard error of minimum deviance (λ value = 0.072595). (D) LASSO coefficient profiles plotted versus log(λ), gray vertical line was drawn at the value selected using 10-fold cross validation, where the optimal λ resulted in 4 nonzero coefficients.
Table 2.
Univariable and multivariable analysis in predicting the presence of BRAFV600E mutation in the training cohort of the total thyroid cancers and conventional PTC<20-mm.
Fig 3.
Calibration plots of the grouped prediction models for the presence of BRAFV600E mutation.
For each plot, the y-axis represents the actual probability of BRAFV600E mutation, and the x-axis represents the predicted risk for BRAFV600E mutation. (A) Calibration plot for the total thyroid cancers and (B) conventional PTCs measuring <20-mm included in this study.
Table 3.
Discrimination ability of the models in the total thyroid cancers and the conventional PTCs<20-mm.