[1] |
Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68(6):394-424.
|
[2] |
He X, Wu J, Holtorf AP, et al. Health economic assessment of Gd-EOB-DTPA MRI versus ECCM-MRI and multi-detector CT for diagnosis of hepatocellular carcinoma in China[J]. PLoS One, 2018, 13(1):e0191095.
|
[3] |
刘爱祥,王海清,薄文滔,等. 肝细胞癌肝切除术的临床疗效及预后因素分析[J]. 中华消化外科杂志, 2019, 18(4):368-374.
|
[4] |
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.
|
[5] |
Kumar V, Gu Y, Basu S, et al. Radiomics: the process and the challenges[J]. Magn Reson Imaging, 2012, 30(9):1234-1248.
|
[6] |
Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data[J]. Radiology, 2016, 278(2):563-577.
|
[7] |
乔婷,王峻峰,胡苹苹,等. 三维重建技术与二维影像辅助肝切除术的Meta分析[J]. 中国普通外科杂志, 2021, 30(7): 805-813.
|
[8] |
Rizzo S, Botta F, Raimondi S, et al. Radiomics: the facts and the challenges of image analysis[J]. Eur Radiol Exp, 2018, 2(1):36.
|
[9] |
Zwanenburg A, Vallières M, Abdalah MA, et al. The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping[J]. Radiology, 2020, 295(2):328-338.
|
[10] |
中华人民共和国国家卫生健康委员会医政医管局. 原发性肝癌诊疗规范(2019年版)[J]. 临床肝胆病杂志, 2020, 36(2): 277-292.
|
[11] |
Feng ST, Jia Y, 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.
|
[12] |
Zhu YJ, Feng B, Wang S, et al. Model-based three-dimensional texture analysis of contrast-enhanced magnetic resonance imaging as a potential tool for preoperative prediction of microvascular invasion in hepatocellular carcinoma[J]. Oncol Lett, 2019, 18(1):720-732.
|
[13] |
Acharya UR, Hagiwara Y, Sudarshan VK, et al. Towards precision medicine: from quantitative imaging to radiomics[J]. J Zhejiang Univ Sci B, 2018, 19(1):6-24.
|
[14] |
Dong Y, Wang QM, Li Q, et al. Preoperative prediction of microvascular invasion of hepatocellular carcinoma: radiomics algorithm based on ultrasound original radio frequency signals[J]. Front Oncol, 2019(9):1203.
|
[15] |
Bakr S, Echegaray S, Shah R, et al. Noninvasive radiomics signature based on quantitative analysis of computed tomography images asa surrogate for microvascular invasion in hepatocellular carcinoma:a pilot study[J]. J Med Imaging, 2017, 4(4):041303.
|
[16] |
Peng J, Zhang J, Zhang Q, et al. A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma[J]. Diagn Interv Radiol, 2018, 24(3):121-127.
|
[17] |
Ma X, Wei J, Gu D, et al. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT[J]. Eur Radiol, 2019, 29(7):3595-3605.
|
[18] |
Yang L, Gu D, Wei J, et al. A radiomics nomogram for preoperative prediction of microvascular invasion in hepatocellular carcinoma[J]. Liver Cancer, 2019, 8(5):373-386.
|
[19] |
Zhang R, Xu L, Wen X, et al. A nomogram based on bi-regional radiomics features from multimodal magnetic resonance imaging for preoperative prediction of microvascular invasion in hepatocellular carcinoma[J]. Quant Imaging Med Surg, 2019, 9(9):1503-1515.
|
[20] |
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.
|
[21] |
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.
|
[22] |
Li Y, Zhang Y, Fang Q, et al. Radiomics analysis of [18F]FDGPET/CT for microvascular invasion and prognosis prediction invery-early- and early-stage hepatocellular carcinoma[J]. Eur J Nucl Med Mol Imaging, 2021, 48(8):2599-2614.
|
[23] |
Zhang W, Yang R, Liang F, et al. Prediction of microvascular invasion in hepatocellular carcinoma with a multi-disciplinary team-like radiomics fusion model on dynamic contrast-enhanced computed tomography[J]. Front Oncol, 2021(11):660629.
|
[24] |
Story MD, Durante M. Radiogenomics[J]. Med Phys, 2018, 45(11):e1111-1122.
|