Chen YD, Zhang L, Zhou ZP, Lin B, Jiang ZJ, Tang C, Dang YW, Xia YW, Song B, Long LL. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. World J Gastroenterol 2022; 28(31): 4399-4416 [PMID: 36159011 DOI: 10.3748/wjg.v28.i31.4399]
Corresponding Author of This Article
Li-Ling Long, MD, Chairman, Chief Doctor, Professor, Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, China. cjr.longliling@vip.163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Observational Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastroenterol. Aug 21, 2022; 28(31): 4399-4416 Published online Aug 21, 2022. doi: 10.3748/wjg.v28.i31.4399
Table 1 Demographics, alpha fetal protein, bilirubin, tumor characteristics, and microvascular infiltration of the patients with small hepatocellular carcinoma in data sets of three hospitals
Characteristics
Hospital A (n = 221)
Hospital B (n = 94)
Hospital C (n = 100)
Age (yr)
mean ± SD: 51.2 ± 10.9 (range 29-78)
mean ± SD: 53.04 ± 10.59 (range 28-77)
mean ± SD: 54.01 ± 10.82 (range 28-85)
Male/female
189 (85.5%)/32 (14.5%)
84 (89.4%)/10 (10.6%)
85 (85.5%)/15 (15.0%)
Causes of liver disease
Hepatitis B
162 (73.3%)
71 (75.6%)
82 (82.0%)
Hepatitis C
21 (9.5%)
10 (10.6%)
6 (6.0%)
Alcoholic hepatitis
29 (13.1%)
8 (8.5%)
2 (2.0%)
Others
9 (4.1%)
5 (5.3%)
10 (10.0%)
Cirrhosis
Present
173 (78.3%)
69 (73.4%)
70 (70%)
Absent
48 (21.7%)
25 (26.6%)
30 (30%)
AFP (ng/mL)
Median: 26.10 (range 0.98-25451.00)
Median: 9.34 (range 1.09-6740.42)
Median: 31.070 (range 0.713- 4587.000)
TBiL (μmol/L)
Median: 12.5 (range 2.9-64.6)
Median: 17.4 (range 3.6-446.9)
Median: 13.2 (range 4.4-47.2)
DBiL (μmol/L)
Median: 3.9 (range 1.0-17.0)
Median: 4.5 (range 1.0-218.9)
Median: 5.50 (range 1.50-26.84)
MELD scores
mean ± SD: 13.9 ± 4.8 (range 7.0-26.9)
mean ± SD: 13.8 ± 5.8 (range 6.0-35.5)
mean ± SD: 11.8 ± 4.5 (range 5.2-25.6)
Child-Pugh classes
A
205 (93.2%)
81 (86.2%)
86 (86.0%)
B
13 (5.9%)
12 (12.8%)
13 (13.0%)
C
2 (0.9%)
1 (1.1%)
1 (1.0%)
Edmondson-steiner grade
Grade I
32 (14.5%)
12 (12.8%)
8 (8.0%)
Grade II
142 (64.3%)
68 (72.3%)
71 (71.0%)
Grade III
47 (21.2%)
14 (14.9%)
21 (21.0%)
Tumor size (cm)
mean ± SD: 2.04 ± 0.67 (range 0.60-3.00)
mean ± SD: 2.17 ± 0.42 (range 0.80-3.00)
mean ± SD: 2.20 ± 0.41 (range 0.90-3.00)
MVI
Positive
64 (28.9%)
22 (23.4%)
16 (16.0%)
Negative
157 (71.1%)
72 (76.6%)
84 (84.0%)
Table 2 Age, gender, alpha-fetoprotein and radiologic features of patients with small hepatocellular carcinoma and relationship with microvascular infiltration
Hospital A (n = 221)
Hospital B (n = 94)
Hospital C (n = 100)
Positive
Negative
P value
Positive
Negative
P value
Positive
Negative
P value
Age (yr)
50.9 ± 10.7
51.3 ± 10.9
0.840
51.7 ± 12.3
53.1 ± 10.1
0.597
53.5 ± 9.1
53.7 ± 11.0
0.958
Gender
0.593
0.443
0.259
Female
8
24
1
9
1
14
Male
56
133
21
63
15
70
AFP (ng/mL)
33.91 (range 1.40-25451.00)
22.52 (range 1-18929)
0.026
38.97 (range 1.90-6740.40)
5.43 (range 1.10-2018.79)
0.010
109.72 (range 0.80-2278.00)
24.41 (range 0.71-4587.00)
0.032
Size (cm)
2.34 ± 0.56
1.92 ± 0.67
0.036
2.43 ± 0.57
2.11 ± 0.66
0.047
2.47 ± 0.43
2.21 ± 0.64
0.054
Nonsmooth tumor margin
0.019
0.003
0.004
Absent
37
116
13
64
6
62
Present
27
41
9
8
10
22
Capsule
0.020
0.062
0.756
Absent
39
120
21
55
10
49
Present
25
37
25
17
6
35
Peritumoral hypointensity
0.002
0.304
0.007
Absent
47
141
17
63
70
8
Present
17
16
5
9
14
8
Table 3 Diagnostic performance of alpha-fetoprotein and radiologic features for assessing microvascular infiltration of small hepatocellular carcinoma by receiver operating characteristic curve analysis
AFP
Tumor size
Nonsmooth tumor margin
Incomplete capsule
Peritumoral hypointensity
Hospital A
AUC
0.597
0.675
0.580
0.577
0.582
95%CI
0.528-0.662
0.609-0.736
0.512-0.646
0.509-0.643
0.514-0.648
P value
0.024
< 0.001
0.024
0.027
0.007
Sensitivity
34.92
70.31
42.19
39.06
26.56
Specificity
81.82
61.15
73.89
76.43
89.81
Hospital B
AUC
0.683
0.639
0.649
0.595
0.551
95%CI
0.577-0.777
0.553-0.735
0.544-0.745
0.489-0.695
0.445-0.654
P value
0.006
0.035
0.008
0.005
0.304
Sensitivity
63.64
81.82
71.43
95.45
22.73
Specificity
72.06
44.44
88.89
23.61
87.50
Hospital C
AUC
0.669
0.576
0.682
0.521
0.667
95%CI
0.568-0.760
0.473-0.675
0.581-0.771
0.419-0.622
0.565-0.758
P value
0.016
0.213
0.007
0.759
0.014
Sensitivity
87.50
68.75
62.50
62.50
50.00
Specificity
52.38
54.76
73.81
41.67
83.33
Table 4 Receiver operator characteristic curve analysis of radiomics scores with different sequences of magnetic resonance imaging for predict microvascular infiltration of small hepatocellular carcinoma
T1WI
T2WI
DWI
AP
PVP
HBP
Training set
AUC
0.740
0.878
0.991
0.763
0.739
0.976
95%CI
0.661-0.808
0.814-0.926
0.958-0.999
0.695-0.823
0.661-0.807
0.940-0.991
P value
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
Sensitivity
77.08
82.98
95.74
71.43
56.25
89.83
Specificity
68.00
82.00
96.04
79.37
78.22
99.27
Testing set
AUC
0.776
0.813
0.971
0.788
0.790
0.979
95%CI
0.611-0.895
0.651-0.922
0.858-0.999
0.642-0.894
0.630-0.904
0.911-1.000
P value
0.0004
< 0.001
< 0.001
0.0014
0.0001
< 0.001
Sensitivity
91.67
58.33
100.00
64.29
84.62
100.00
Specificity
57.69
92.00
84.62
93.75
73.08
91.43
Validation Hospital B
AUC
0.834
0.825
0.816
0.810
0.847
0.970
95%CI
0.742-0.904
0.732-0.896
0.678-0.876
0.715-0.884
0.758-0.913
0.912-0.994
P value
< 0.001
< 0.001
0.0002
< 0.001
< 0.001
< 0.001
Sensitivity
63.64
95.45
71.43
57.14
54.55
95.45
Specificity
94.29
57.75
88.89
88.89
98.61
98.57
Validation Hospital C
AUC
0.766
0.761
0.801
0.824
0.833
0.803
95%CI
0.672-0.844
0.669-0.839
0.710-0.871
0.737-0.892
0.748-0.898
0.680-0.834
P value
0.0001
0.0003
< 0.001
< 0.001
< 0.001
0.007
Sensitivity
80.00
60.00
90.00
86.67
85.71
83.33
Specificity
70.45
89.01
68.89
68.54
72.83
77.67
Table 5 Predictive performance of the nomogram prediction model for estimating the risk of microvascular infiltration presence in patients with small hepatocellular carcinoma
Training set
Testing set
Validation Hospital B
Validation Hospital C
T1WI
C-index
0.771
0.846
0.895
0.830
95%CI
0.695-0.836
0.594-0.883
0.775-0.925
0.667-0.850
P value
< 0.001
0.0014
< 0.001
0.0001
T2WI
C-index
0.895
0.917
0.886
0.808
95%CI
0.834-0.940
0.640-0.915
0.746-0.906
0.654-0.867
P value
< 0.001
0.0001
< 0.001
0.0015
DWI
C-index
0.990
0.970
0.843
0.869
95%CI
0.957-0.999
0.843-0.997
0.685-0.881
0.694-0.899
P value
< 0.001
< 0.001
0.0001
< 0.001
AP
C-index
0.774
0.794
0.886
0.874
95%CI
0.706-0.833
0.615-0.876
0.695-0.899
0.674-0.884
P value
< 0.001
0.0025
< 0.001
< 0.001
PVP
C-index
0.746
0.831
0.918
0.870
95%CI
0.668-0.814
0.650-0.916
0.791-0.934
0.732-0.887
P value
< 0.001
< 0.001
< 0.001
< 0.001
HBP
C-index
0.990
0.971
0.912
0.808
95%CI
0.944-0.993
0.892-0.999
0.918-0.996
0.635-0.892
P value
< 0.001
< 0.001
< 0.001
0.0081
Citation: Chen YD, Zhang L, Zhou ZP, Lin B, Jiang ZJ, Tang C, Dang YW, Xia YW, Song B, Long LL. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. World J Gastroenterol 2022; 28(31): 4399-4416