Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
Article
Google Scholar
Fan ST, Lo CM, Poon RTP, Yeung C, Liu CL, Yuen WK, Lam CM, Ng KKC, Chan SC. Continuous improvement of survival outcomes of resection of hepatocellular carcinoma A 20-year experience. Ann Surg. 2011;253(4):745–58.
Article
Google Scholar
Tabrizian P, Jibara G, Shrager B, Schwartz M, Roayaie S. Recurrence of hepatocellular cancer after resection patterns, treatments, and prognosis. Ann Surg. 2015;261(5):947–55.
Article
Google Scholar
Scholzen T, Gerdes J. The Ki-67 protein: from the known and the unknown. J Cell Physiol. 2000;182(3):311–22.
Article
CAS
Google Scholar
Yang C, Zhang J, Ding M, Xu K, Li L, Mao L, Zheng J. Ki67 targeted strategies for cancer therapy. Clin Transl Oncol. 2018;20(5):570–5.
Article
CAS
Google Scholar
Murakami K, Kasajima A, Kawagishi N, Ohuchi N, Sasano H. Microvessel density in hepatocellular carcinoma: prognostic significance and review of the previous published work. Hepatol Res. 2015;45(12):1185–94.
Article
CAS
Google Scholar
Sofocleous CT, Garg S, Petrovic LM, Gonen M, Petre EN, Klimstra DS, Solomon SB, Brown KT, Brody LA, Covey AM, et al. Ki-67 is a prognostic biomarker of survival after radiofrequency ablation of liver malignancies. Ann Surg Oncol. 2012;19(13):4262–9.
Article
Google Scholar
Yang C, Su H, Liao X, Han C, Yu T, Zhu G, Wang X, Winkler CA, O’Brien SJ, Peng T. Marker of proliferation Ki-67 expression is associated with transforming growth factor beta 1 and can predict the prognosis of patients with hepatic B virus-related hepatocellular carcinoma. Cancer Manag Res. 2018;10:679–96.
Article
CAS
Google Scholar
Luo Y, Ren F, Liu Y, Shi Z, Tan Z, Xiong H, Dang Y, Chen G. Clinicopathological and prognostic significance of high Ki-67 labeling index in hepatocellular carcinoma patients: a meta-analysis. Int J Clin Exp Med. 2015;8(7):10235–47.
PubMed
PubMed Central
Google Scholar
Shi W, Hu J, Zhu S, Shen X, Zhang X, Yang C, Gao H, Zhang H. Expression of MTA2 and Ki-67 in hepatocellular carcinoma and their correlation with prognosis. Int J Clin Exp Pathol. 2015;8(10):13083–9.
CAS
PubMed
PubMed Central
Google Scholar
Mitsuhashi N, Kobayashi S, Doki T, Kimura F, Shimizu H, Yoshidome H, Ohtsuka M, Kato A, Yoshitomi H, Nozawa S, et al. Clinical significance of alpha-fetoprotein: involvement in proliferation, angiogenesis, and apoptosis of hepatocellular carcinoma. J Gastroenterol Hepatol. 2008;23(7 Pt 2):e189–97.
Article
CAS
Google Scholar
Guzman G, Alagiozian-Angelova V, Layden-Almer JE, Layden TJ, Testa G, Benedetti E, Kajdacsy-Balla A, Cotler SJ. p53, Ki-67, and serum alpha feto-protein as predictors of hepatocellular carcinoma recurrence in liver transplant patients. Mod Pathol. 2005;18(11):1498–503.
Article
CAS
Google Scholar
Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, Zegers CM, Gillies R, Boellard R, Dekker A, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441–6.
Article
Google Scholar
Kumar V, Gu Y, Basu S, Berglund A, Eschrich SA, Schabath MB, Forster K, Aerts HJ, Dekker A, Fenstermacher D, et al. Radiomics: the process and the challenges. Magn Reson Imaging. 2012;30(9):1234–48.
Article
Google Scholar
Chen S, Feng S, Wei J, Liu F, Li B, Li X, Hou Y, Gu D, Tang M, Xiao H, et al. Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging. Eur Radiol. 2019;29(8):4177–87.
Article
Google Scholar
Juan MW, Yu J, Peng GX, Jun LJ, Feng SP, Fang LP. Correlation between DCE-MRI radiomics features and Ki-67 expression in invasive breast cancer. Oncol Lett. 2018;16(4):5084–90.
PubMed
PubMed Central
Google Scholar
Wei J, Yang G, Hao X, Gu D, Tan Y, Wang X, Dong D, Zhang S, Wang L, Zhang H, et al. A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication. Eur Radiol. 2019;29(2):877–88.
Article
Google Scholar
Wu Q, Shi D, Dou S, Shi L, Liu M, Dong L, Chang X, Wang M. Radiomics analysis of multiparametric MRI evaluates the pathological features of cervical squamous cell carcinoma. J Magn Reson Imaging. 2019;49(4):1141–8.
Article
Google Scholar
Bakr S, Echegaray S, Shah R, Kamaya A, Louie J, Napel S, Kothary N, Gevaert O. Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study. J Med Imaging (Bellingham). 2017;4(4):041303.
Google Scholar
Peng J, Zhang J, Zhang Q, Xu Y, Zhou J, Liu L. A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma. Diagn Interv Radiol. 2018;24(3):121–7.
Article
Google Scholar
Li Y, Yan C, Weng S, Shi Z, Sun H, Chen J, Xu X, Ye R, Hong J. Texture analysis of multi-phase MRI images to detect expression of Ki67 in hepatocellular carcinoma. Clin Radiol. 2019;74(10):813.e819–27.
Article
Google Scholar
Ye Z, Jiang H, Chen J, Liu X, Wei Y, Xia C, Duan T, Cao L, Zhang Z, Song B. Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: a prospective study. Chin J Cancer Res. 2019;31(5):806–17.
Article
CAS
Google Scholar
van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts H. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104–7.
Article
Google Scholar
Schwier M, van Griethuysen J, Vangel MG, Pieper S, Peled S, Tempany C, Aerts H, Kikinis R, Fennessy FM, Fedorov A. Repeatability of multiparametric prostate MRI radiomics features. Sci Rep. 2019;9(1):9441.
Article
Google Scholar
Leijenaar RT, Carvalho S, Velazquez ER, van Elmpt WJ, Parmar C, Hoekstra OS, Hoekstra CJ, Boellaard R, Dekker AL, Gillies RJ, et al. Stability of FDG-PET radiomics features: an integrated analysis of test-retest and inter-observer variability. Acta Oncol. 2013;52(7):1391–7.
Article
CAS
Google Scholar
Huang X, Long L, Wei J, Li Y, Xia Y, Zuo P, Chai X. Radiomics for diagnosis of dual-phenotype hepatocellular carcinoma using Gd-EOB-DTPA-enhanced MRI and patient prognosis. J Cancer Res Clin Oncol. 2019;145(12):2995–3003.
Article
CAS
Google Scholar
Davenport MS, Viglianti BL, Al-Hawary MM, Caoili EM, Kaza RK, Liu PS, Maturen KE, Chenevert TL, Hussain HK. Comparison of acute transient dyspnea after intravenous administration of gadoxetate disodium and gadobenate dimeglumine: effect on arterial phase image quality. Radiology. 2013;266(2):452–61.
Article
Google Scholar
Li H, Xiao Y, Wang S, Li Y, Zhong X, Situ W, Xiao E, Zhang Z. TWIST-VIBE five-arterial-phase technology decreases transient severe motion after bolus injection of Gd-EOB-DTPA. Clin Radiol. 2017;72(9):800.e801–6.
Article
Google Scholar
Aerts HJWL, Velazquez ER, Leijenaar RTH, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006.
Article
CAS
Google Scholar
Lambin P, Leijenaar RTH, Deist TM, Peerlings J, de Jong EEC, van Timmeren J, Sanduleanu S, Larue RTHM, Even AJG, Jochems A, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14(12):749–62.
Article
Google Scholar