| [1] |
Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263.
|
| [2] |
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[J]. CA Cancer J Clin, 2021, 71(3): 209-249.
|
| [3] |
Xie D, Shi J, Zhou J, et al. Clinical practice guidelines and real-life practice in hepatocellular carcinoma: A Chinese perspective[J]. Clin Mol Hepatol, 2023, 29(2): 206-216.
|
| [4] |
Bi WL, Hosny A, Schabath MB, et al. Artificial intelligence in cancer imaging: Clinical challenges and applications[J]. CA Cancer J Clin, 2019, 69(2): 127-157.
|
| [5] |
Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis [J]. Eur J Cancer, 2012, 48(4): 441-446.
|
| [6] |
Bera K, Braman N, Gupta A, et al. Predicting cancer outcomes with radiomics and artificial intelligence in radiology[J]. Nat Rev Clin Oncol, 2022, 19(2): 132-146.
|
| [7] |
Soffer S, Ben-Cohen A, Shimon O, et al. Convolutional Neural Networks for Radiologic Images: A Radiologist's Guide[J]. Radiology, 2019, 290(3): 590-606.
|
| [8] |
Mao Y, Wang J, Zhu Y, et al. Gd-EOB-DTPA-enhanced MRI radiomic features for predicting histological grade of hepatocellular carcinoma [J]. Hepatobiliary Surg Nutr, 2022, 11(1): 13-24.
|
| [9] |
Zhu Z, Wu K, Lu J, et al. Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study[J]. BMC Med Imaging, 2025, 25(1): 105.
|
| [10] |
Zhong Y, Chen L, Ding F, et al. Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks[J]. Front Oncol, 2024, 14: 1401095.
|
| [11] |
Hu HT, Wang Z, Huang XW, et al. Ultrasound-based radiomics score: a potential biomarker for the prediction of microvascular invasion in hepatocellular carcinoma[J]. Eur Radiol, 2019, 29(6): 2890-2901.
|
| [12] |
Fan Y, Yu Y, Wang X, et al. Radiomic analysis of Gd-EOB-DTPA- enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma [J]. BMC Med Imaging, 2021, 21(1): 100.
|
| [13] |
Wang W, Gu D, Wei J, et al. A radiomics-based biomarker for cytokeratin 19 status of hepatocellular carcinoma with gadoxetic acid-enhanced MRI[J]. Eur Radiol, 2020, 30(5): 3004-3014.
|
| [14] |
Chen S, Feng S, Wei J, et al. Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging[J]. Eur Radiol, 2019, 29(8): 4177-4187.
|
| [15] |
Gong XQ, Liu N, Tao YY, et al. Radiomics models based on multisequence MRI for predicting PD-1/PD-L1 expression in hepatocellular carcinoma[J]. Sci Rep, 2023, 13(1): 7710.
|
| [16] |
Yang Y, Zhou Y, Zhou C, et al. Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma[J]. Eur J Surg Oncol, 2022, 48(5): 1068-1077.
|
| [17] |
Xu X, Zhang HL, Liu QP, et al. Radiomic analysis of contrast- enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma[J]. J Hepatol, 2019, 70(6): 1133-1144.
|
| [18] |
Shi S, Mao XC, Cao YQ, et al. CT Radiomics Features of Abdominal Adipose and Muscle Tissues Can Predict the Postoperative Early Recurrence of Hepatocellular Carcinoma[J]. Acad Radiol, 2023, S1076-6332(23)00536-6.
|
| [19] |
Tian H, Xie Y, Wang Z. Radiomics for preoperative prediction of early recurrence in hepatocellular carcinoma: a meta-analysis[J]. Front Oncol, 2023, 13: 1114983.
|
| [20] |
Wang Y, Zhang Y, Xiao J, et al. Multicenter Integration of MR Radiomics, Deep Learning, and Clinical Indicators for Predicting Hepatocellular Carcinoma Recurrence After Thermal Ablation[J]. J Hepatocell Carcinoma, 2024, 11: 1861-1874.
|
| [21] |
Wu JP, Ding WZ, Wang YL, et al. Radiomics analysis of ultrasound to predict recurrence of hepatocellular carcinoma after microwave ablation[J]. Int J Hyperthermia, 2022, 39(1): 595-604.
|
| [22] |
Kang W, Tang P, Luo Y, et al. Multiparametric MRI-based Machine Learning Radiomics for Predicting Treatment Response to Transarterial Chemoembolization Combined with Targeted and Immunotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Study[J]. Acad Radiol, 2025, 32(4): 2013-2026.
|
| [23] |
Han B, Zheng R, Zeng H, et al. Cancer incidence and mortality in China, 2022[J]. J Natl Cancer Cent, 2024, 4(1): 47-53.
|
| [24] |
Park JW, Chen M, Colombo M, et al. Global patterns of hepatocellular carcinoma management from diagnosis to death: the BRIDGE Study[J]. Liver Int, 2015, 35(9): 2155-66.
|
| [25] |
Liang XJ, Song XY, Wu JL, et al. Advances in Multi-Omics Study of Prognostic Biomarkers of Diffuse Large B-Cell Lymphoma[J]. Int J Biol Sci, 2022, 18(4): 1313-1327.
|
| [26] |
Xie Y, Wang F, Wei J, et al. Noninvasive prognostic classification of ITH in HCC with multi-omics insights and therapeutic implications [J]. Sci Adv, 2025, 11(18): eads8323.
|