Table 3. Features showing statistical difference between non-responders and responders.
Feature | P value | Standard error | 95% CI | AUC | Sens | Spec | Cut-off |
---|---|---|---|---|---|---|---|
F_Skewness | 0.010 | 0.083 | 0.571–0.852 | 0.728 | 0.684 | 0.792 | ≤−0.271 |
LoG2.5_glszm_SALGLE | 0.013 | 0.081 | 0.564–0.847 | 0.721 | 0.421 | 0.958 | ≤4.99×10−3 |
WHLH_F_Mean | 0.013 | 0.081 | 0.564–0.847 | 0.721 | 0.684 | 0.791 | −3.42×10−3 |
glcm_CS | 0.037 | 0.086 | 0.527–0.819 | 0.686 | 0.421 | 0.958 | ≤−4.547 |
WLLL_F_Skewness | 0.037 | 0.087 | 0.527–0.819 | 0.686 | 0.736 | 0.667 | ≤−0.087 |
WHLH_glszm_SAE | 0.047 | 0.084 | 0.518–0.812 | 0.678 | 0.526 | 0.833 | ≤0.401 |
F, first order; LoG2.5, volume preprocessed using Laplacian of Gaussian band pass filter with 2.5 filter width; GLSZM, gray-level size-zone matrix; SALGLE, small area low gray level emphasis; WHLH, volume with a wavelet high-pass filter along x-direction, a low-pass filter along y-direction and a high-pass filter along z-direction; GLCM, gray-level co-occurrence matrix; CI, confidence interval; AUC, area under the curve; Sens, Sensitivity; Spec, Specificity; Responders, patients with CR and PR; non-responders, patients with SD.