Skip to main content

Table 4 ROC analysis of radiomic features in prediction of immunohistochemical status

From: Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI

IHC status Radiomic feature AUROC
ER(+) VS. ER(−) Histogram 0.973 (0.949–0.997)
Texture 0.762 (0.674–0.851)
GLCM 0.963 (0.929–0.998)
RLM 0.967 (0.937–0.997)
PR(+) VS. PR(−) Histogram 0.925 (0.879–0.972)
Texture 0.731 (0.637–0.824)
GLCM 0.939 (0.892–0.986)
RLM 0.923 (0.875–0.971)
HER2(+) VS. HER2(−) Histogram 0.902 (0.847–0.957)
Texture 0.722 (0.627–0.818)
GLCM 0.911 (0.860–0.962)
RLM 0.974 (0.944–1.000)
Ki-67 low VS. high Histogram 0.926 (0.870–0.981)
Texture 0.718 (0.615–0.820)
GLCM 0.975 (0.949–1.000)
RLM 0.946 (0.905–0.988)
\