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©The Author(s) 2020.
World J Gastroenterol. Mar 21, 2020; 26(11): 1208-1220
Published online Mar 21, 2020. doi: 10.3748/wjg.v26.i11.1208
Published online Mar 21, 2020. doi: 10.3748/wjg.v26.i11.1208
Table 1 Categories of the quantitative radiomics features obtained for analysis
Groups | Detailed parameters |
First-order and distribution statistics, n = 23 | Minimum intensity, Maximum intensity, Mean intensity, Median intensity, Standard deviation, Variance, Volume count, Voxel value sum, Range mean deviation, Relative deviation, Skewness, Kurtosis, Uniformity, Energy, Entropy, Frequency size, Quantile 5, Quantile 10, Quantile 25, Quantile 50, Quantile 75, Quantile 90, Quantile 95 |
Gray-level co-occurrence matrix, n = 28 | Glcm bin size, Glcm total frequency, Glcm matrix mean, Glcm relative Frequency, Energy, Entropy, Inertia, Correlation, Inverse difference moment, Cluster shade, Cluster prominence, Haralick correlation, Haralick entropy, Angular second moment, Contrast, Haralick variance, sum Average, sum Variance, sum Entropy, Difference variance, Difference entropy, Inverse difference moment normalized, Minimum intensity, Maximum intensity, Number of intensity bins, Minimum size, Maximum size, Number of size bins |
Gray-level run length matrix, n = 10 | Short run emphasis (SRE), Long run emphasis (LRE), Gray level non-uniformity (GLN), Run length non-uniformity (RLN), Low gray level run emphasis (LGLRE), High gray level run emphasis (HGLRE), Short run low gray level emphasis (SRLGLE), Short run high gray level emphasis (SRHGLE), Long run low gray level emphasis (LRLGLE), Long run high gray level emphasis (LRHGLE) |
Table 2 Clinicopathological characteristics of 101 hepatitis B virus-related cirrhotic patients with hepatocellular carcinoma
Patients with | Patients without | P value | |
Liver failure, n = 15 | Liver failure, n = 86 | ||
Sex | 0.439 | ||
Male | 9 (90) | 50 (89) | |
Female | 1 (10) | 6 (12) | |
Age in yr | 55 (22-78) | 55 (40-67) | 0.958 |
Primary tumor | |||
Tumor size in mm12 | 59 (15-154) | 38 (10-197) | 0.069 |
Single, n | 4 (27) | 60 (70) | |
Multiple in n | 11 (73) | 26 (30) | |
Baseline serological index1 | |||
Aspartate aminotransferase in IU/L | 59 (17-116) | 33 (17-1663) | 0.030 |
Alanine aminotransferase in IU/L | 34 (17-98) | 31 (11-1491) | 0.248 |
Total bilirubin in mg/dL | 18.2 (8.2-37.9) | 15.7 (3.2-35.5) | 0.314 |
Albumin in g/L | 38.7 (30.9-45.8) | 40.3 (23.0-50.3) | 0.135 |
Alkaline phosphatase in U/L | 131 (71-365) | 91 (41-410) | 0.004 |
Platelet as /L | 200 (111-496) | 188 (49-489) | 0.462 |
Prothrombin time in s | 12.8 (11.3-14.9) | 12.3 (10.6-16.8) | 0.138 |
Cholinesterase in U/L | 6271 (2522-8417) | 6714 (2334-12360) | 0.110 |
ICG test1 | |||
Elimination rate constant in K as min-1 | 0.13 (0.09-0.19) | 0.21 (0.12-0.29) | 0.308 |
Retention rate at 15 min as R15 in % | 8.2 (1.3-28.4) | 12.8 (6.1-18.0) | 0.002 |
The half-life as T1/2 in min | 6.36 (3.73-7.88) | 3.27 (2.39-5.68) | 0.061 |
Baseline score | |||
Child-Pugh classification | 0.786 | ||
A | 15 (100) | 81 (94) | |
B | 0 (0) | 5 (6) | |
C | 0 (0) | 0 (0) | |
Fibrosis grade on specimen | 0.174 | ||
F1 | 1 (7) | 9 (11) | |
F2 | 0 (0) | 8 (9) | |
F3 | 0 (0) | 7 (8) | |
F4 | 9 (60) | 14 (16) | |
N/A | 5 (33) | 48 (56) |
Table 3 Receiver operating characteristics analysis of the predictive value of clinical prediction model, radiomics signature and radiomics-based model
Clinical prediction model | Radiomics signature | Radiomics-based model | |
AUC (95%CI) | 0.810 (0.691-0.929) | 0.809 (0.713-0.906) | 0.894 (0.823-0.964) |
Optimized Youden Index | 0.579 | 0.556 | 0.712 |
Sensitivity (95%CI) | 0.800 (0.514-0.947) | 0.800 (0.514-0.947) | 0.933 (0.660-0.997) |
Specificity (95%CI) | 0.779 (0.674-0.858) | 0.756 (0.649-0.839) | 0.779 (0.674-0.859) |
PPV (95%CI) | 0.387 (0.224-0.577) | 0.364 (0.210-0.549) | 0.424 (0.260-0.606) |
NPV (95%CI) | 0.957 (0.872-0.989) | 0.956 (0.868-0.989) | 0.985 (0.910-0.999) |
Accuracy (95%CI) | 0.782 (0.691-0.852) | 0.762 (0.670-0.835) | 0.802 (0.713-0.869) |
- Citation: Zhu WS, Shi SY, Yang ZH, Song C, Shen J. Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure. World J Gastroenterol 2020; 26(11): 1208-1220
- URL: https://www.wjgnet.com/1007-9327/full/v26/i11/1208.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i11.1208