Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
Table 2
Diagnostic performance of selected texture features to differentiate benign thyroid nodules from malignant nodules.
Texture parameter
Benign lesions (n = 14)
Malignant lesions (n = 20)
value
Cut-off
Sensitivity (%)
Specificity (%)
AUC
Mean
SD
Mean
SD
Mean in histogram
40 keV
1124.8
39.6
1091.3
52.3
0.052
N/A
N/A
N/A
0.682
60 keV
1091.9
26.2
1059.8
94.5
0.163
N/A
N/A
N/A
0.664
80 keV
1085.7
18.5
1071.9
9.4
0.019
<1080.9
57.1
85.0
0.771¶
Median in histogram
40 keV
1124.8
39.2
1099.7
27.1
0.034
<1112.0
64.3
85.0
0.686
60 keV
1092.8
26.0
1072.6
39.4
0.103
N/A
N/A
N/A
0.679
80 keV
1086.7
18.6
1071.9
9.5
0.014
<1080.9
71.0
75.0
0.771¶
Contrast in GLCM
40 keV
23.6
18.9
18.0
12.5
0.309
N/A
N/A
N/A
0.629
60 keV
21.3
20.1
17.2
27.1
0.635
N/A
N/A
N/A
0.629
80 keV
18.5
15.3
8.4
4.3
0.031
<15.12
50.0
85.0
0.693
Skewness in GLGM
40 keV
36.3
12.3
28.6
7.6
0.030
<37.00
50.0
85.0
0.696
60 keV
36.0
12.2
28.8
7.4
0.064
N/A
N/A
N/A
0.671
80 keV
36.4
12.0
28.8
7.4
0.030
<29.49
78.6
65.0
0.696
MGR in GLGM
40 keV
5.792
3.559
9.340
5.805
0.035
>3.301
95.0
35.7
0.689
60 keV
5.041
2.880
7.993
4.479
0.038
>3.692
85.0
50.0
0.693
80 keV
4.850
2.696
7.615
4.199
0.038
>3.639
85.0
50.0
0.704
VGR in GLGM
40 keV
19974.2
10745.3
30478.1
16424.1
0.044
>15036
85.0
42.4
0.689
60 keV
18824.2
10530.9
28949.7
15235.9
0.039
>12098
95.0
35.7
0.696
80 keV
17957.5
10154.8
28800.9
15431.2
0.028
>14288
85.0
50.0
0.721
GLCM = gray-level co-occurrence matrix; GLGM = gray-level gradient matrix; MGR = mean gradients; VGR = a variance of gradients; AUC = area under receiver operating characteristic curve; significant differences are defined as ;¶highest AUC among 41 texture features.
