CURRENT STATUS AND PROGRESS OF MRI RADIOMICS IN HEPATOCELLULAR CARCINOMA

Authors

  • Zilin Liu Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai Hospital Affiliated with Jinan University, Jinan University (Zhuhai People’s Hospital), Zhuhai 519000, China
  • Yong Li (Corresponding Author) Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai Hospital Affiliated with Jinan University, Jinan University (Zhuhai People’s Hospital), Zhuhai 519000, China

Keywords:

hepatocellular carcinoma, magnetic resonance imaging, radiomics, accurate diagnosis, risk stratification, prognosis prediction

Abstract

Hepatocellular carcinoma (HCC) is a common malignant tumor in the human digestive tract. It has high recurrence, poor prognosis, and difficulty in early detection. Relative to this, magnetic resonance imaging (MRI) has good soft-tissue resolution and multi-parameter imaging advantages, significant for accurate liver cancer diagnosis and prognosis. Meanwhile, radiomics can extract high-dimensional and quantitative features to quantify tumor heterogeneity, exhibiting great potential in differential diagnosis, risk stratification, and prognosis evaluation of liver cancer. This article reviewed the research progress of the MRI omics of HCC.

References

[1] Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin, 2021;71(3):209-249.

[2] Wei KR, Peng XB, Liang ZH, et al. Liver Cancer Epidemiology Worldwide. China Cancer. 2015;24(8):621-630.

[3] Shimozawa N, Hanazaki K. Long-term prognosis after hepatic resection for small hepatocellular carcinoma. J Am Coll Surgeons. 2004;198(3):356-365.

[4] Shah SA, Cleary SP, Wei AC, et al. Recurrence after liver resection for hepatocellular carcinoma: Risk factors, treatment, and outcomes. Surgery. 2007;141(3):330-339.

[5] Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: Extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441-446.

[6] Lambin P, Roelofs E, Reymen B, et al. Rapid Learning health care in oncology - An approach towards decision support systems enabling customised radiotherapy. Radiother Oncol. 2013;109(1):159-164.

[7] Wu JJ, Liu A, Cui JJ, et al. Radiomics-based classification of hepatocellular carcinoma and hepatic haemangioma on precontrast magnetic resonance images. BMC Med Imaging. 2019;19(1).

[8] Sammon J, Fischer S, Menezes R, et al. MRI features of combined hepatocellular-cholangiocarcinoma versus mass forming intrahepatic cholangiocarcinoma. Cancer Imaging. 2018;18(1).

[9] Liu XY, Khalvati F, Namdar K, et al. Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment planning?. Eur Radiol. 2021;31(1):244-255.

[10] Erkan B, Meier J, Clark TJ, et al. Non-invasive diagnostic criteria of hepatocellular carcinoma: Comparison of diagnostic accuracy of updated LI-RADS with clinical practice guidelines of OPTN-UNOS, AASLD, NCCN, EASL-EORTC, and KLSCG-NCC. PLoS One. 2019;14(12):e0226291.

[11] Zhong X, Guan TP, Tang DR, et al. Differentiation of small (≤3 cm) hepatocellular carcinomas from benign nodules in cirrhotic liver: the added value of MRI-based radiomics analysis to LI-RADS version 2018 algorithm. BMC Gastroenterol. 2021;21(1).

[12] Lewis S, Peti S, Hectors SJ, et al. Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers. Abdom Radiol. 2019;44(3):912-922.

[13] Cong WM, Bu H, Chen J, et al. Practice guidelines for the pathological diagnosis of primary liver cancer: 2015 update. World J Gastroenterol. 2016;22(42):9279.

[14] Chinese Societies of Liver Cancer, Chinese Anti-Ca, Liver Cancer Study Group, Chinese Society of Hepat, Chinese Societies of Pathology, Chinese Anti-Cancer, et al. Evidence-based practice guidelines for the standardized pathological diagnosis of primary liver cancer (2015 edition). Chinese J Hepatob Surg. 2015;21(3):145-151.

[15] Huang XL, Long LL, Wei JQ, et al. Radiomics for diagnosis of dual-phenotype hepatocellular carcinoma using Gd-EOB-DTPA-enhanced MRI and patient prognosis. J Cancer Res Clin. 2019;145(12):2995-3003.

[16] Wang XH, Long LH, Cui Y, et al. MRI-based radiomics model for preoperative prediction of 5-year survival in patients with hepatocellular carcinoma. Br J Cancer. 2020;122(7):978-985.

[17] Zhang JH, Wang XL, Zhang LX, et al. Radiomics predict postoperative survival of patients with primary liver cancer with different pathological types. Ann Transl Med. 2020;8(13):820-820.

[18] Imamura H, Matsuyama Y, Tanaka E, et al. Risk factors contributing to early and late phase intrahepatic recurrence of hepatocellular carcinoma after hepatectomy. J Hepatol. 2003;38(2):200-207.

[19] Hao SH, Fan P, Chen SF, et al. Distinct Recurrence Risk Factors for Intrahepatic Metastasis and Multicenter Occurrence After Surgery in Patients with Hepatocellular Carcinoma. J Gastrointest Surg. 2017;21(2):312-320.

[20] Tabrizian P, Jibara G, Shrager B, et al. Recurrence of Hepatocellular Cancer After Resection. Ann Surg. 2015;261(5):947-955.

[21] Hui TCH, Chuah TK, Low HM, et al. Predicting early recurrence of hepatocellular carcinoma with texture analysis of preoperative MRI: a radiomics study. Clin Radiol. 2018;73(12):1056.e11-1056.e16.

[22] Zhao Y, Wu J, Zhang Q, et al. Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy. J Magn Reson Imaging. 2021;53(4):1066-1079.

[23] Tsurusaki M, Murakami T. Surgical and Locoregional Therapy of HCC: TACE. Liver Cancer. 2015;4(3):165-175.

[24] Kucukay F, Badem S, Karan A, et al. A Single-Center Retrospective Comparison of Doxorubicin-Loaded HepaSphere Transarterial Chemoembolization with Conventional Transarterial Chemoembolization for Patients with Unresectable Hepatocellular Carcinoma. J Vasc Interv Radiol. 2015;26(11):1622-1629.

[25] Takaki S, Sakaguchi H, Anai H, et al. Long-Term Outcome of Transcatheter Subsegmental and Segmental Arterial Chemoembolization Using Lipiodol for Hepatocellular Carcinoma. Cardiovasc Interv Radiol. 2012;35(3):544-554.

[26] Song WL, Yu XL, Guo DJ, et al. MRI-Based Radiomics: Associations With the Recurrence-Free Survival of Patients With Hepatocellular Carcinoma Treated With Conventional Transcatheter Arterial Chemoembolization. J Magn Reson Imaging. 2020;52(2):461-473.

[27] Yuan CW, Wang ZC, Gu DS, et al. Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram. Cancer Imaging. 2019;19(1).

[28] Zheng BH, Liu LZ, Zhang ZZ, et al. Radiomics score: A potential prognostic imaging feature for postoperative survival of solitary HCC patients. BMC Cancer. 2018;18(1).

[29] Zhang XF, Li J, Shen F, et al. Significance of presence of microvascular invasion in specimens obtained after surgical treatment of hepatocellular carcinoma. J Gastroen Hepatol. 2018;33(2):347-354.

[30] Isik B, Gonultas F, Sahin T, et al. Microvascular Venous Invasion in Hepatocellular Carcinoma: Why Do Recurrences Occur?. J Gastrointest Cancer. 2020;51(4):1133-1136.

[31] Lee S, Kang TW, Song KD, et al. Effect of Microvascular Invasion Risk on Early Recurrence of Hepatocellular Carcinoma After Surgery and Radiofrequency Ablation. Ann Surg. 2021;273(3):564-571.

[32] 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 Magn Reson Imaging. 2021;54(2):526-536.

[33] Yang L, Gu DS, Wei JW, et al. A Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Liver Cancer. 2019;8(5):373-386.

[34] Nebbia G, Zhang Q, Arefan D, et al. Pre-operative Microvascular Invasion Prediction Using Multiparametric Liver MRI Radiomics. J Digit Imaging. 2020;33(6):1376-1386.

[35] Zhou W, Zhang LJ, Wang KX, et al. Malignancy characterization of hepatocellular carcinomas based on texture analysis of contrast-enhanced MR images. J Magn Reson Imaging. 2017;45(5):1476-1484.

[36] Wu MH, Tan HN, Gao F, et al. Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Eur Radiol. 2019;29(6):2802-2811.

[37] Geng ZJ, Zhang YF, Wang ST, et al. Radiomics Analysis of Susceptibility Weighted Imaging for Hepatocellular Carcinoma: Exploring the Correlation between Histopathology and Radiomics Features. Magn Reson Med Sci. 2021;20(3):253-263.

[38] Bell M, Turkbey EB, Escorcia FE. Radiomics, Radiogenomics, and Next-Generation Molecular Imaging to Augment Diagnosis of Hepatocellular Carcinoma. Cancer J. 2020;26(2):108-115.

[39] Liu B, Yang X, Sun J, et al. Research prog

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Published

2022-02-14

Issue

Vol. 5 No. 1 (2022)

Section

Research Article

How to Cite

Zilin Liu, Yong Li. Current Status And Progress Of Mri Radiomics In Hepatocellular Carcinoma. Acta Translational Medicine. 2022, 5(1): 1-7.