The Incremental Value of Subjective and Quantitative Assessment of 18F-FDG PET for the Prediction of Pathologic Complete Response to Preoperative Chemoradiotherapy in Esophageal Cancer
暂无分享,去创建一个
Laurence E Court | Marco van Vulpen | David V Fried | Lifei Zhang | Lifei Zhang | D. Fried | L. Court | Steven H. Lin | W. Hofstetter | M. van Vulpen | G. Meijer | P. V. van Rossum | Wayne L Hofstetter | Steven H Lin | Gert J Meijer | Peter S N van Rossum | L. Zhang
[1] C. Tseng,et al. Using Pretreatment Tumor Depth and Length to Select Esophageal Squamous Cell Carcinoma Patients for Nonoperative Treatment After Neoadjuvant Chemoradiotherapy , 2013, Annals of Surgical Oncology.
[2] J. Lagendijk,et al. Diffusion-weighted magnetic resonance imaging for the prediction of pathologic response to neoadjuvant chemoradiotherapy in esophageal cancer. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[3] V. Rusch,et al. Predictive Value of Initial PET-SUVmax in Patients with Locally Advanced Esophageal and Gastroesophageal Junction Adenocarcinoma , 2009, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.
[4] Gary S Collins,et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration , 2015, Annals of Internal Medicine.
[5] 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.
[6] Jinzhong Yang,et al. IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics. , 2015, Medical physics.
[7] D. Wigle,et al. Complete pathologic response after neoadjuvant chemoradiotherapy for esophageal cancer is associated with enhanced survival. , 2009, The Annals of thoracic surgery.
[8] K. McGraw,et al. Forming inferences about some intraclass correlation coefficients. , 1996 .
[9] G. Meijer,et al. Imaging strategies in the management of oesophageal cancer: what’s the role of MRI? , 2013, European Radiology.
[10] 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.
[11] D. Rennie,et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative , 2003, BMJ : British Medical Journal.
[12] J. Reynolds,et al. Value of CT–PET after neoadjuvant chemoradiation in the prediction of histological tumour regression, nodal status and survival in oesophageal adenocarcinoma , 2014, The British journal of surgery.
[13] R. Munden,et al. Detection of interval distant metastases , 2007, Cancer.
[14] J. Ajani,et al. Clinical parameters model for predicting pathologic complete response following preoperative chemoradiation in patients with esophageal cancer. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.
[15] M. Hatt,et al. Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[16] M. Woodward,et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker , 2012, Heart.
[17] Dimitris Visvikis,et al. Baseline 18F-FDG PET image-derived parameters for therapy response prediction in oesophageal cancer , 2011, European Journal of Nuclear Medicine and Molecular Imaging.
[18] Vicky Goh,et al. Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis , 2012, European Journal of Nuclear Medicine and Molecular Imaging.
[19] J. Ajani,et al. 2‐Fluoro‐2‐deoxy‐D‐glucose positron emission tomography imaging is predictive of pathologic response and survival after preoperative chemoradiation in patients with esophageal carcinoma , 2004, Cancer.
[20] J. Ajani,et al. Association between clinical complete response and pathological complete response after preoperative chemoradiation in patients with gastroesophageal cancer: analysis in a large cohort. , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.
[21] Jeffrey S. Morris,et al. Posttherapy pathologic stage predicts survival in patients with esophageal carcinoma receiving preoperative chemoradiation , 2005, Cancer.
[22] E W Steyerberg,et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. , 2012, The New England journal of medicine.
[23] C. Mariette,et al. Is There a Role for Surgery for Patients with a Complete Clinical Response after Chemoradiation for Esophageal Cancer? An Intention-to-Treat Case-Control Study , 2013, Annals of surgery.
[24] Hao Wang,et al. Complete response to neoadjuvant chemoradiotherapy in esophageal carcinoma is associated with significantly improved survival. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[25] R. van Hillegersberg,et al. Imaging of oesophageal cancer with FDG-PET/CT and MRI. , 2015, Clinical radiology.
[26] 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.
[27] Otto S Hoekstra,et al. Esophageal cancer: CT, endoscopic US, and FDG PET for assessment of response to neoadjuvant therapy--systematic review. , 2005, Radiology.
[28] F. Brooks,et al. The Effect of Small Tumor Volumes on Studies of Intratumoral Heterogeneity of Tracer Uptake , 2014, The Journal of Nuclear Medicine.
[29] M. Schwaiger,et al. Metabolic imaging predicts response, survival, and recurrence in adenocarcinomas of the esophagogastric junction. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[30] Shan Tan,et al. Spatial-temporal [¹⁸F]FDG-PET features for predicting pathologic response of esophageal cancer to neoadjuvant chemoradiation therapy. , 2013, International journal of radiation oncology, biology, physics.
[31] J. V. van Sandick,et al. Detecting Interval Metastases and Response Assessment Using 18F-FDG PET/CT After Neoadjuvant Chemoradiotherapy for Esophageal Cancer , 2014, Clinical nuclear medicine.
[32] M. Hatt,et al. Reproducibility of Tumor Uptake Heterogeneity Characterization Through Textural Feature Analysis in 18F-FDG PET , 2012, The Journal of Nuclear Medicine.
[33] Issam El-Naqa,et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes , 2009, Pattern Recognit..
[34] W. Schreurs,et al. PET/CT-based metabolic tumour volume for response prediction of neoadjuvant chemoradiotherapy in oesophageal carcinoma , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[35] 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.
[36] E. Elkin,et al. Decision Curve Analysis: A Novel Method for Evaluating Prediction Models , 2006, Medical decision making : an international journal of the Society for Medical Decision Making.
[37] R. M. Kwee. Prediction of tumor response to neoadjuvant therapy in patients with esophageal cancer with use of 18F FDG PET: a systematic review. , 2010, Radiology.
[38] Kristin D. Brockway,et al. What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom. , 2012, International journal of radiation oncology, biology, physics.
[39] P. Thall,et al. A phase II randomized trial of induction chemotherapy versus no induction chemotherapy followed by preoperative chemoradiation in patients with esophageal cancer. , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.
[40] 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 .
[41] N. Holalkere,et al. Adenocarcinomas of the esophagus: response to chemoradiotherapy is associated with decrease of metabolic tumor volume as measured on PET-CT. Comparison to histopathologic and clinical response evaluation. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[42] C. Tseng,et al. Predictors of pathological complete response to neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma , 2014, World Journal of Surgical Oncology.
[43] S. Baldus,et al. Response Evaluation by Endoscopy, Rebiopsy, and Endoscopic Ultrasound Does Not Accurately Predict Histopathologic Regression After Neoadjuvant Chemoradiation for Esophageal Cancer , 2008, Annals of surgery.
[44] Lin-jun Tong,et al. Can 18F-fluorodeoxyglucose positron emission tomography predict responses to neoadjuvant therapy in oesophageal cancer patients? A meta-analysis , 2011, Nuclear medicine communications.
[45] R. Langer,et al. Assessment of Tumor Regression of Esophageal Adenocarcinomas After Neoadjuvant Chemotherapy: Comparison of 2 Commonly Used Scoring Approaches , 2014, The American journal of surgical pathology.