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©The Author(s) 2022.
World J Clin Oncol. Nov 24, 2022; 13(11): 918-928
Published online Nov 24, 2022. doi: 10.5306/wjco.v13.i11.918
Published online Nov 24, 2022. doi: 10.5306/wjco.v13.i11.918
Table 1 Tumor features on magnetic resonance imaging
Total | MVI group | Non-MVI group | P value | |
Tumors, n (%) | 50 (100) | 15 (30) | 35 (70) | |
Size (mm), mean (SD) | 56.4 (34.6) | 41.3 (29.1) | 0.107 | |
Multiplicity, n (%) | 0.087 | |||
Single | 43 (86) | 15 (100) | 28 (80) | |
Multifocal | 7 (14) | 0 | 7 (20) | |
T1 (unenhanced), n (%) | 0.346 | |||
Hypointense | 46 (92) | 13 (87) | 33 (94) | |
Isointense | 2 (4) | 1 (7) | 1 (3) | |
Hyperintense | 2 (4) | 1 (7) | 1 (3) | |
T1 (arterial phase), n (%) | 0.663 | |||
Hypointense | 6 (12) | 1 (7) | 5 (14) | |
Isointense | 6 (12) | 1 (7) | 5 (14) | |
Hyperintense | 38 (76) | 13 (87) | 25 (71) | |
T1 (portal venous phase), n (%) | 0.231 | |||
Hypointense | 42 (84) | 14 (93) | 28 (80) | |
Isointense | 6 (12) | 0 (0) | 6 (17) | |
Hyperintense | 2 (4) | 1 (7) | 1 (3) | |
T1 (equilibrium phase), n (%) | 0.654 | |||
Hypointense | 45 (90) | 14 (93) | 31 (89) | |
Isointense | 4 (8) | 1 (7) | 3 (9) | |
Hyperintense | 0 | 0 (0) | 0 (0) | |
T1 (HPB phase), n (%) | 0.664 | |||
Hypointense | 33 (66) | 9 (60) | 24 (69) | |
Isointense | 1 (2) | 0 | 1 (3) | |
Not performed | 16 (32) | 6 (40) | 10 (28) | |
T2 hyperintensity, n (%) | 0.451 | |||
Present | 42 (84) | 12 (80) | 30 (86) | |
Absent | 8 (16) | 3 (20) | 5 (14) | |
Restricted diffusion, n (%) | 0.745 | |||
Present | 44 (88) | 13 (87) | 31 (89) | |
Absent | 5 (10) | 2 (13) | 3 (9) | |
Not performed | 1 (2) | 0 (0) | 1 (3) | |
Visible vessels (arterial phase), n (%) | 0.001 | |||
Present | 11 (22) | 8 (53) | 3 (9) | |
Absent | 39 (78) | 7 (47) | 32 (91) | |
Visible vessels (portal venous phase), n (%) | 0.043 | |||
Present | 8 (16) | 5 (33) | 3 (9) | |
Absent | 42 (84) | 10 (67) | 32 (91) | |
Peritumoral enhancement, n (%) | 0.248 | |||
Present | 15 (30) | 6 (40) | 9 (26) | |
Absent | 35 (70) | 9 (60) | 26 (74) | |
Hypodense halo, n (%) | 0.524 | |||
Present | 5 (10) | 1 (7) | 4 (11) | |
Absent | 45 (90) | 14 (93) | 31 (89) | |
Border between tumour and liver, n (%) | 0.428 | |||
Sharp | 34 (68) | 11 (73) | 23 (66) | |
Ill-defined | 16 (32) | 4 (27) | 12 (34) | |
Tumor margins, n (%) | 0.477 | |||
Smooth | 28 (56) | 9 (60) | 19 (54) | |
Non-smooth | 22 (44) | 6 (40) | 16 (46) | |
LI-RADS, n (%) | 0.05 | |||
LR-4 | 10 (20) | 0 (0) | 10 (29) | |
LR-5 | 27 (54) | 10 (67) | 17 (49) | |
LR-M | 13 (26) | 5 (33) | 8 (22) |
- Citation: Sim JZT, Hui TCH, Chuah TK, Low HM, Tan CH, Shelat VG. Efficacy of texture analysis of pre-operative magnetic resonance imaging in predicting microvascular invasion in hepatocellular carcinoma. World J Clin Oncol 2022; 13(11): 918-928
- URL: https://www.wjgnet.com/2218-4333/full/v13/i11/918.htm
- DOI: https://dx.doi.org/10.5306/wjco.v13.i11.918