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. 2021 Dec 13;33:102912. doi: 10.1016/j.nicl.2021.102912

Fig. 7.

Fig. 7

Receiver-operating characteristic (ROC) curves for the 3 cases from Fig. 1. Panel A shows ROC curves for predicting firm consistency (n = 7) from the pooled soft and variable (n = 9) based on MK10 (gray line) and MKA 10 (black line) in the whole tumor-ROI. Based on MK10 the AUC is 0.83 with confidence interval [0.43; 1.00] with optimal cut-point value (gray dot) with specificity 100 % and sensitivity 71 %. Based on MKA 10 the AUC is 0.84 with confidence interval [0.52; 0.98] with optimal cut-point value (black dot) with specificity 78 % and sensitivity 86 %. Panel B shows ROC curve for predicting grade II (n = 8) from grade I (n = 22) based on MKI std in the rim-ROI. The AUC is 0.65 with confidence intervals [0.42; 0.84]. Optimal cut-point value (gray dot) yields specificity of 77 % and sensitivity 50 %. Finally, panel C shows ROC curve for prediction of psammomatous type based on MK50 and MKA 50. The AUC for MK50 is 0.63 with confidence interval [0.18; 1.00] with optimal cut-point value with specificity of 100 % and sensitivity 40 % (gray dot) and for MKA 50 0.81 with confidence intervals [0.07; 1.00] with optimal cut-point value with specificity 96 % and sensitivity 80 %. Large confidence intervals (not shown graphically in the figure) in all cases highlight limitations of the small dataset and thus limit the interpretability of the AUC value.