Quantitative Analysis of (18)F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy.
暂无分享,去创建一个
Ruijiang Li | Hiroki Shirato | Daniel T Chang | Yi Cui | Muthuraman Alagappan | Albert C Koong | Erqi Pollom | Ruijiang Li | A. Koong | H. Shirato | D. Chang | E. Pollom | Yi Cui | Jie Song | M. Alagappan | Jie Song
[1] Lei Xing,et al. Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. , 2016, Radiology.
[2] P. Lambin,et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.
[3] E. Saad,et al. Pretreatment CA 19-9 level as a prognostic factor in patients with advanced pancreatic cancer treated with gemcitabine , 2002, International journal of gastrointestinal cancer.
[4] Sunil J Rao,et al. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .
[5] Florent Tixier,et al. Visual Versus Quantitative Assessment of Intratumor 18F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer , 2014, The Journal of Nuclear Medicine.
[6] E Yorke,et al. Four-dimensional (4D) PET/CT imaging of the thorax. , 2004, Medical physics.
[7] Tai-Hsien Ou Yang,et al. Development of a Prognostic Model for Breast Cancer Survival in an Open Challenge Environment , 2013, Science Translational Medicine.
[8] W. Lu,et al. Computerized PET/CT image analysis in the evaluation of tumour response to therapy. , 2015, The British journal of radiology.
[9] D. Rubin,et al. Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of (18)F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis. , 2016, Radiology.
[10] S. Goodman,et al. Pancreaticoduodenectomy for Cancer of the Head of the Pancreas 201 Patients , 1995, Annals of surgery.
[11] Byung Il Kim,et al. Prognostic value of SUVmax measured by Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography with Computed Tomography in Patients with Pancreatic Cancer , 2012, Nuclear Medicine and Molecular Imaging.
[12] F. Brooks,et al. The Effect of Small Tumor Volumes on Studies of Intratumoral Heterogeneity of Tracer Uptake , 2014, The Journal of Nuclear Medicine.
[13] M. Endo,et al. Preoperative FDG-PET Predicts Early Recurrence and a Poor Prognosis After Resection of Pancreatic Adenocarcinoma , 2015, Annals of Surgical Oncology.
[14] M. Hatt,et al. Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer , 2011, The Journal of Nuclear Medicine.
[15] Issam El-Naqa,et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes , 2009, Pattern Recognit..
[16] A. Jemal,et al. Cancer statistics, 2014 , 2014, CA: a cancer journal for clinicians.
[17] Vicky Goh,et al. Non-Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of (18)F-FDG Uptake at PET-Association with Treatment Response and Prognosis. , 2015, Radiology.
[18] Andre Dekker,et al. Radiomics: the process and the challenges. , 2012, Magnetic resonance imaging.
[19] P. Lambin,et al. Stability of FDG-PET Radiomics features: An integrated analysis of test-retest and inter-observer variability , 2013, Acta oncologica.
[20] C. Kang,et al. Prognostic Value of Metabolic Tumor Volume and Total Lesion Glycolysis on Preoperative 18F-FDG PET/CT in Patients with Pancreatic Cancer , 2014, The Journal of Nuclear Medicine.
[21] M. Hatt,et al. 18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort , 2015, The Journal of Nuclear Medicine.
[22] Vicky Goh,et al. Are Pretreatment 18F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy? , 2013, The Journal of Nuclear Medicine.
[23] Max A. Viergever,et al. elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.
[24] T. Pawlik,et al. Baseline metabolic tumor volume and total lesion glycolysis are associated with survival outcomes in patients with locally advanced pancreatic cancer receiving stereotactic body radiation therapy. , 2014, International journal of radiation oncology, biology, physics.
[25] A. Windhorst,et al. Feasibility and repeatability of PET with the hypoxia tracer [(18)F]HX4 in oesophageal and pancreatic cancer. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[26] Shan Tan,et al. Modeling pathologic response of esophageal cancer to chemoradiation therapy using spatial-temporal 18F-FDG PET features, clinical parameters, and demographics. , 2014, International journal of radiation oncology, biology, physics.
[27] R. Tibshirani. The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.
[28] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[29] Olivier Gevaert,et al. Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer. , 2012, Cancer research.
[30] A. Koong,et al. 18Fluorodeoxyglucose PET is prognostic of progression-free and overall survival in locally advanced pancreas cancer treated with stereotactic radiotherapy. , 2010, International journal of radiation oncology, biology, physics.
[31] H. Matsuda,et al. Preoperative 18[F]-fluorodeoxyglucose positron emission tomography/computed tomography predicts early recurrence after pancreatic cancer resection , 2011, International Journal of Clinical Oncology.
[32] Richard M. Simon,et al. Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data , 2011, Briefings Bioinform..
[33] Trevor Hastie,et al. Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent. , 2011, Journal of statistical software.
[34] D. Sahani,et al. State-of-the-art PET/CT of the pancreas: current role and emerging indications. , 2012, Radiographics : a review publication of the Radiological Society of North America, Inc.
[35] J. Fleiss,et al. Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.
[36] Shao Hui Huang,et al. External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma , 2015, Acta oncologica.
[37] D. Winchester,et al. Pancreatic cancer: a report of treatment and survival trends for 100,313 patients diagnosed from 1985-1995, using the National Cancer Database. , 1999, Journal of the American College of Surgeons.
[38] I. El Naqa,et al. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities , 2015, Physics in medicine and biology.