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Research progress in predicting microvascular invasion of hepatocellular carcinoma by preoperative MRI
WANG Shaoyi  ZHOU Zhipeng 

Cite this article as: Wang SY, Zhou ZP. Research progress in predicting microvascular invasion of hepatocellular carcinoma by preoperative MRI[J]. Chin J Magn Reson Imaging, 2022, 13(2): 155-158, 162. DOI:10.12015/issn.1674-8034.2022.02.039.


[Abstract] Microvascular invasion (MVI) is one of the important factors affecting postoperative recurrence and metastasis of hepatocellular carcinoma, and is closely related to the prognosis and treatment of patients. However, MVI can only be diagnosed by pathology. Accurate prediction of MVI by MRI is of great significance and prospect for selecting treatment measures and improving the prognosis of patients. Many MRI-based imaging features have been proposed for the prediction of MVI, including tumor size, number, incomplete capsule, uneven margins, peritumoral enhancement in arterial phase, and peritumoral hypointensity in hepatobiliary phase. As an emerging field, radiomics may be an accurate and effective tool for predicting MVI in patients with hepatocellular carcinoma, and it has also been used by researchers to explore the link with MVI in recent years. This article reviewed the research on preoperative MRI examination and MRI-based radiomics model for predicting MVI in hepatocellular carcinoma.
[Keywords] hepatocellular carcinoma；microvascular invasion；magnetic resonance imaging；radiomics；diffusion weighted imaging；prognosis

WANG Shaoyi   ZHOU Zhipeng*  

Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin 541000, China

Zhou ZP, E-mail: bigbird_zhou@hotmail.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Guangxi Key Laboratory of Molecular Medicine in Liver Injury and Repair (No. GXLIRMMKL-K202010); Major Special Projects of Guilin Scientific Research and Technology Development Program (No. 20190202-2).
Received  2021-10-20
Accepted  2022-01-30
DOI: 10.12015/issn.1674-8034.2022.02.039
Cite this article as: Wang SY, Zhou ZP. Research progress in predicting microvascular invasion of hepatocellular carcinoma by preoperative MRI[J]. Chin J Magn Reson Imaging, 2022, 13(2): 155-158, 162. DOI:10.12015/issn.1674-8034.2022.02.039.

[1]
Sayiner M, Golabi P, Younossi ZM. Disease burden of hepatocellular carcinoma: a global perspective[J]. Dig Dis Sci, 2019, 64(4): 910-917. DOI: 10.1007/s10620-019-05537-2.
[2]
Njei B, Rotman Y, Ditah I, et al. Emerging trends in hepatocellular carcinoma incidence and mortality[J]. Hepatology, 2015, 61(1): 191-199. DOI: 10.1002/hep.27388.
[3]
Erstad DJ, Tanabe KK. Prognostic and therapeutic implications of microvascular invasion in hepatocellular carcinoma[J]. Ann Surg Oncol, 2019, 26(5): 1474-1493. DOI: 10.1245/s10434-019-07227-9.
[4]
He XC, An WH, Zhao HQ, et al. Microvascular invasion in hepatocellular carcinoma: definition and criteria for pathological grading[J]. J Clin Hepatol, 2020, 36(5): 1181-1184. DOI: 10.3969/j.issn.1001-5256.2020.05.052.
[5]
Lee EC, Kim SH, Park H, et al. Survival analysis after liver resection for hepatocellular carcinoma: a consecutive cohort of 1002 patients[J]. J Gastroenterol Hepatol, 2017, 32(5): 1055-1063. DOI: 10.1111/jgh.13632.
[6]
Si AF, Huang X, Lei ZQ, et al. The influence of microvascular invasion on the prognosis of patients with hepatocellular carcinoma after liver transplantation[J]. Chin Clin Oncol, 2020, 25(4):316-321. DOI: 10.3969/j.issn.1009-0460.2020.04.006.
[7]
Kaibori M, Ishizaki M, Matsui K, et al. Predictors of microvascular invasion before hepatectomy for hepatocellular carcinoma[J]. J Surg Oncol, 2010, 102(5): 462-468. DOI: 10.1002/jso.21631.
[8]
Chandarana H, Robinson E, Hajdu CH, et al. Microvascular invasion in hepatocellular carcinoma: is it predictable with pretransplant MRI?[J]. AJR Am J Roentgenol, 2011, 196(5): 1083-1089. DOI: 10.2214/AJR.10.4720.
[9]
Zhao WC, Fan LF, Yang N, et al. Preoperative predictors of microvascular invasion in multinodular hepatocellular carcinoma[J]. Eur J Surg Oncol, 2013, 39(8): 858-864. DOI: 10.1016/j.ejso.2013.04.003.
[10]
Wei H, Jiang HY, Liu XJ, et al. Can LI-RADS imaging features at gadoxetic acid-enhanced MRI predict aggressive features on pathology of single hepatocellular carcinoma? [J]. Eur J Radiol, 2020, 132: 109312. DOI: 10.1016/j.ejrad.2020.109312.
[11]
Lim JH, Choi D, Park CK, et al. Encapsulated hepatocellular carcinoma: CT-pathologic correlations[J]. Eur Radiol, 2006, 16(10): 2326-2333. DOI: 10.1007/s00330-006-0203-8.
[12]
Adachi E, Maeda T, Kajiyama K, et al. Factors correlated with portal venous invasion by hepatocellular carcinoma: univariate and multivariate analyses of 232 resected cases without preoperative treatments[J]. Cancer, 1996, 77(10): 2022-2031. DOI: 10.1002/(SICI)1097-0142(19960515)77:10＜2022:AID-CNCR9＞3.0.CO;2-S.
[13]
Zhao H, Hua Y, Dai T, et al. Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma[J]. Eur J Radiol, 2017, 88: 32-40. DOI: 10.1016/j.ejrad.2016.12.030.
[14]
Zhu F, Yang F, Li J, et al. Incomplete tumor capsule on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis[J]. Abdom Radiol (NY), 2019, 44(9): 3049-3057. DOI: 10.1007/s00261-019-02126-9.
[15]
Song L, Li JW, Luo Y. The importance of a nonsmooth tumor margin and incomplete tumor capsule in predicting HCC microvascular invasion on preoperative imaging examination: a systematic review and meta-analysis[J]. Clin Imaging, 2021, 76: 77-82. DOI: 10.1016/j.clinimag.2020.11.057.
[16]
Wu TH, Hatano E, Yamanaka K, et al. A non-smooth tumor margin on preoperative imaging predicts microvascular invasion of hepatocellular carcinoma[J]. Surg Today, 2016, 46(11): 1275-1281. DOI: 10.1007/s00595-016-1320-x.
[17]
Lee S, Kim SH, Lee JE, et al. Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma[J]. J Hepatol, 2017, 67(3): 526-534. DOI: 10.1016/j.jhep.2017.04.024.
[18]
Chen JB, Zhou J, Kuang SC, et al. Liver imaging reporting and data system category 5: MRI predictors of microvascular invasion and recurrence after hepatectomy for hepatocellular carcinoma[J]. AJR Am J Roentgenol, 2019, 213(4): 821-830. DOI: 10.2214/AJR.19.21168.
[19]
Xu PJ, Yan FH, Wang JH, et al. Added value of breathhold diffusion-weighted MRI in detection of small hepatocellular carcinoma lesions compared with dynamic contrast-enhanced MRI alone using receiver operating characteristic curve analysis[J]. J Magn Reson Imaging, 2009, 29(2): 341-349. DOI: 10.1002/jmri.21650.
[20]
Xu PJ, Zeng MS, Liu K, et al. Microvascular invasion in small hepatocellular carcinoma: is it predictable with preoperative diffusion-weighted imaging?[J]. J Gastroenterol Hepatol, 2014, 29(2): 330-336. DOI: 10.1111/jgh.12358.
[21]
Suh YJ, Kim MJ, Choi JY, et al. Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging[J]. Liver Transpl, 2012, 18(10): 1171-1178. DOI: 10.1002/lt.23502.
[22]
Jing MY, Cao YT, Deng J, et al. The value of minimum apparent diffusion coefficient in evaluating the invasiveness of hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2021, 12(5): 16-20. DOI: 10.12015/issn.1674-8034.2021.05.004.
[23]
Rosenkrantz AB, Padhani AR, Chenevert TL, et al. Body diffusion kurtosis imaging: basic principles, applications, and considerations for clinical practice[J]. J Magn Reson Imaging, 2015, 42(5): 1190-1202. DOI: 10.1002/jmri.24985.
[24]
Wang WT, Yang L, Yang ZX, et al. Assessment of microvascular invasion of hepatocellular carcinoma with diffusion kurtosis imaging[J]. Radiology, 2018, 286(2): 571-580. DOI: 10.1148/radiol.2017170515.
[25]
Cao LK, Chen J, Duan T, et al. Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade[J]. Quant Imaging Med Surg, 2019, 9(4): 590-602. DOI: 10.21037/qims.2019.02.14.
[26]
Wei Y, Huang ZX, Tang HH, et al. IVIM improves preoperative assessment of microvascular invasion in HCC[J]. Eur Radiol, 2019, 29(10): 5403-5414. DOI: 10.1007/s00330-019-06088-w.
[27]
Li HX, Zhang J, Zheng ZY, et al. Preoperative histogram analysis of intravoxel incoherent motion (IVIM) for predicting microvascular invasion in patients with single hepatocellular carcinoma[J]. Eur J Radiol, 2018, 105: 65-71. DOI: 10.1016/j.ejrad.2018.05.032.
[28]
Kim MJ, Lee M, Choi JY, et al. Imaging features of small hepatocellular carcinomas with microvascular invasion on gadoxetic acid-enhanced MR imaging[J]. Eur J Radiol, 2012, 81(10): 2507-2512. DOI: 10.1016/j.ejrad.2011.11.014.
[29]
Motosugi U, Ichikawa T, Sou H, et al. Distinguishing hypervascular pseudolesions of the liver from hypervascular hepatocellular carcinomas with gadoxetic acid-enhanced MR imaging[J]. Radiology, 2010, 256(1): 151-158. DOI: 10.1148/radiol.10091885.
[30]
Huang MQ, Liao B, Xu P, et al. Prediction of microvascular invasion in hepatocellular carcinoma: preoperative Gd-EOB-DTPA-dynamic enhanced MRI and histopathological correlation[J]. Contrast Media Mol Imaging, 2018, 2018: 9674565. DOI: 10.1155/2018/9674565.
[31]
Kim KA, Kim MJ, Jeon HM, et al. Prediction of microvascular invasion of hepatocellular carcinoma: usefulness of peritumoral hypointensity seen on gadoxetate disodium-enhanced hepatobiliary phase images[J]. J Magn Reson Imaging, 2012, 35(3): 629-634. DOI: 10.1002/jmri.22876.
[32]
Lee S, Kim KW, Jeong WK, et al. Gadoxetic acid-enhanced MRI as a predictor of recurrence of HCC after liver transplantation[J]. Eur Radiol, 2020, 30(2): 987-995. DOI: 10.1007/s00330-019-06424-0.
[33]
Chou CT, Chen RC, Lee CW, et al. Prediction of microvascular invasion of hepatocellular carcinoma by pre-operative CT imaging[J]. Br J Radiol, 2012, 85(1014): 778-783. DOI: 10.1259/bjr/65897774.
[34]
Hu HT, Shen SL, Wang Z, et al. Peritumoral tissue on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis[J]. Abdom Radiol (NY), 2018, 43(12): 3324-3330. DOI: 10.1007/s00261-018-1646-5.
[35]
Sun WJ, Gao ZL, Yang GH, et al. Prediction of microvascular invasion based on enhanced mode magnetic resonance imaging for patients with hepatocellular carcinoma[J]. Chin J Hepatobiliary Surg, 2021, 27(3): 175-180. DOI: 10.3760/cma.j.cn113884-20200418-00207.
[36]
Zhu YJ, Feng B, Wang BZ, et al. Value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging and diffusion-weighted MR imaging in predicting microvascular invasion in hepatocellular carcinoma and the prognostic significance[J]. Chin J Oncol, 2021, 43(3): 312-317. DOI: 10.3760/cma.j.cn112152-20191009-00652.
[37]
Aerts HJ, Velazquez ER, Leijenaar RT, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach[J]. Nat Commun, 2014, 5: 4006. DOI: 10.1038/ncomms5006.
[38]
Meng XP, Wang YC, Zhou JY, et al. Comparison of MRI and CT for the prediction of microvascular invasion in solitary hepatocellular carcinoma based on a non-radiomics and radiomics method: which imaging modality is better?[J]. J Magn Reson Imaging, 2021, 54(2): 526-536. DOI: 10.1002/jmri.27575.
[39]
Feng ST, Jia YM, Liao B, et al. Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI[J]. Eur Radiol, 2019, 29(9): 4648-4659. DOI: 10.1007/s00330-018-5935-8.
[40]
Duan YY, Zhou KP, Bian J, et al. Predicting microvascular invasion of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature[J]. Chin J Magn Reson Imaging, 2020, 11(3): 195-200. DOI: 10.12015/issn.1674-8034.2020.03.007.
[41]
Zhang Y, Shu ZY, Ye Q, et al. Preoperative prediction of microvascular invasion in hepatocellular carcinoma via multi-parametric MRI radiomics[J]. Front Oncol, 2021, 11: 633596. DOI: 10.3389/fonc.2021.633596.
[42]
Nebbia G, Zhang Q, Arefan D, et al. Pre-operative microvascular invasion prediction using multi-parametric liver MRI radiomics[J]. J Digit Imaging, 2020, 33(6): 1376-1386. DOI: 10.1007/s10278-020-00353-x.
[43]
Yang Y, Fan WJ, Gu T, et al. Radiomic features of multi-ROI and multi-phase MRI for the prediction of microvascular invasion in solitary hepatocellular carcinoma[J]. Front Oncol, 2021, 11: 756216. DOI: 10.3389/fonc.2021.756216.
[44]
Chong HH, Yang L, Sheng RF, et al. Multi-scale and multi-parametric radiomics of gadoxetate disodium-enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma≤5 cm[J]. Eur Radiol, 2021, 31(7): 4824-4838. DOI: 10.1007/s00330-020-07601-2.
[45]
Huang JC, Tian WW, Zhang LL, et al. Preoperative prediction power of imaging methods for microvascular invasion in hepatocellular carcinoma: a systemic review and meta-analysis[J]. Front Oncol, 2020, 10: 887. DOI: 10.3389/fonc.2020.00887.

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