HCC advances in diagnosis and prognosis: Digital and Imaging
暂无分享,去创建一个
[1] P. Lee,et al. Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals , 2021, Cancer Imaging.
[2] Robert M. Marks,et al. LI-RADS Past, Present, and Future, From the AJR Special Series on Radiology Reporting and Data Systems. , 2020, AJR. American journal of roentgenology.
[3] K. Carriere,et al. Interobserver Variability and Diagnostic Performance of Gadoxetic Acid-enhanced MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma. , 2020, Radiology.
[4] Myeong-Jin Kim,et al. Gadoxetic acid-enhanced MRI of macrotrabecular-massive hepatocellular carcinoma and its prognostic implications. , 2020, Journal of hepatology.
[5] M. Ronot,et al. Similar performance of liver stiffness measurement and liver surface nodularity for the detection of portal hypertension in patients with hepatocellular carcinoma , 2020, JHEP reports : innovation in hepatology.
[6] Kaiyu Wang,et al. Prediction Model for Intermediate‐Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization , 2020, Journal of magnetic resonance imaging : JMRI.
[7] A. Luciani,et al. Multiphase Liver MRI for Identifying the Macrotrabecular-Massive Subtype of Hepatocellular Carcinoma. , 2020, Radiology.
[8] M. Ronot,et al. Relevance of liver surface nodularity for preoperative risk assessment in patients with resectable hepatocellular carcinoma , 2020, The British journal of surgery.
[9] B. Taouli,et al. MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma , 2020, European Radiology.
[10] M. Ronot,et al. Imaging of liver tumours: What’s new? , 2020, Liver international : official journal of the International Association for the Study of the Liver.
[11] Huan Liu,et al. MRI‐Based Radiomics: Associations With the Recurrence‐Free Survival of Patients With Hepatocellular Carcinoma Treated With Conventional Transcatheter Arterial Chemoembolization , 2019, Journal of magnetic resonance imaging : JMRI.
[12] Manal M. Hassan,et al. A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization. , 2019, Radiology. Artificial intelligence.
[13] L. Schwartz,et al. Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules , 2019, European Radiology.
[14] Ho Sung Kim,et al. Reproducibility and Generalizability in Radiomics Modeling: Possible Strategies in Radiologic and Statistical Perspectives , 2019, Korean journal of radiology.
[15] Jing Zhang,et al. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma. , 2019, Journal of hepatology.
[16] Hui Zhang,et al. Development of a prognostic score for recommended TACE candidates with hepatocellular carcinoma: A multicentre observational study. , 2019, Journal of hepatology.
[17] K. Ngiam,et al. Big data and machine learning algorithms for health-care delivery. , 2019, The Lancet. Oncology.
[18] Kathryn J Fowler,et al. Accuracy of the Liver Imaging Reporting and Data System in Computed Tomography and Magnetic Resonance Image Analysis of Hepatocellular Carcinoma or Overall Malignancy-A Systematic Review. , 2019, Gastroenterology.
[19] Myeong-Jin Kim,et al. Evaluation of Early Response to Treatment of Hepatocellular Carcinoma with Yttrium-90 Radioembolization Using Quantitative Computed Tomography Analysis , 2019, Korean journal of radiology.
[20] Raymond Y Huang,et al. Artificial intelligence in cancer imaging: Clinical challenges and applications , 2019, CA: a cancer journal for clinicians.
[21] Xin Li,et al. Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI , 2019, European Radiology.
[22] M. Abecassis,et al. Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases , 2018, Hepatology.
[23] R. Yeung,et al. Precision oncology in liver cancer. , 2018, Annals of translational medicine.
[24] A. Luciani,et al. Macrotrabecular‐massive hepatocellular carcinoma: A distinctive histological subtype with clinical relevance , 2018, Hepatology.
[25] A. Luciani,et al. Advanced Hepatocellular Carcinoma: Pretreatment Contrast-enhanced CT Texture Parameters as Predictive Biomarkers of Survival in Patients Treated with Sorafenib. , 2018, Radiology.
[26] M. Abecassis,et al. AASLD guidelines for the treatment of hepatocellular carcinoma , 2018, Hepatology.
[27] D. Sinn,et al. Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma. , 2017, Journal of hepatology.
[28] Xiaoping Liu,et al. Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma. , 2017, Cancer research.
[29] R. Lencioni,et al. Lipiodol transarterial chemoembolization for hepatocellular carcinoma: A systematic review of efficacy and safety data , 2016, Hepatology.
[30] Paul Kinahan,et al. Radiomics: Images Are More than Pictures, They Are Data , 2015, Radiology.
[31] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[32] L Pagliaro,et al. Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference. European Association for the Study of the Liver. , 2001, Journal of hepatology.
[33] G. Tourassi. Journey toward computer-aided diagnosis: role of image texture analysis. , 1999, Radiology.