The Added Prognostic Value of Preoperative Dynamic Contrast-Enhanced MRI Histogram Analysis in Patients with Glioblastoma: Analysis of Overall and Progression-Free Survival
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Jong-Hee Chang | S. Ahn | E. Kim | Seung-Koo Lee | T. Rim | S. Kim | S. Lee | J. H. Chang | S S Ahn | T H Rim | Y S Choi | D W Kim | S-K Lee | J H Chang | S-G Kang | E H Kim | S H Kim | S. Kang | Y. S. Choi | D. W. Kim | E. Kim | Y.S. Choi | J.H. Chang | S. Kang | S. H. Kim | S. Ahn | E.H. Kim | S. Kim | D.W. Kim | S. Ahn | Tyler Hyungtaek Rim | Yoon Seong Choi | Daigeun Kim
[1] M Takahashi,et al. Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. , 1998, AJR. American journal of roentgenology.
[2] O Salonen,et al. MRI enhancement and microvascular density in gliomas. Correlation with tumor cell proliferation. , 1999, Investigative radiology.
[3] M. Knopp,et al. Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols , 1999, Journal of magnetic resonance imaging : JMRI.
[4] P. Carmeliet,et al. Angiogenesis in cancer and other diseases , 2000, Nature.
[5] Susan M. Chang,et al. Glioblastoma Patients Epidermal Growth Factor Receptor , and Survival in Analysis of Complex Relationships between Age , p 53 , Updated , 2001 .
[6] Z L Gokaslan,et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. , 2001, Journal of neurosurgery.
[7] K. Makino,et al. Influence of p53 mutations on prognosis of patients with glioblastoma , 2002, Cancer.
[8] A. Padhani,et al. Reproducibility of dynamic contrast‐enhanced MRI in human muscle and tumours: comparison of quantitative and semi‐quantitative analysis , 2002, NMR in biomedicine.
[9] Jeffrey L Duerk,et al. Determining and optimizing the precision of quantitative measurements of perfusion from dynamic contrast enhanced MRI , 2003, Journal of magnetic resonance imaging : JMRI.
[10] Kenji Tada,et al. Prognostic value of epidermal growth factor receptor in patients with glioblastoma multiforme. , 2003, Cancer research.
[11] Glyn Johnson,et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. , 2004, AJNR. American journal of neuroradiology.
[12] Raymond Sawaya,et al. Prognostic significance of preoperative MRI scans in glioblastoma multiforme , 2004, Journal of Neuro-Oncology.
[13] Ying Lu,et al. Survival analysis in patients with glioblastoma multiforme: Predictive value of choline‐to‐n‐acetylaspartate index, apparent diffusion coefficient, and relative cerebral blood volume , 2004, Journal of magnetic resonance imaging : JMRI.
[14] T W Redpath,et al. The effects of renal variation upon measurements of perfusion and leakage volume in breast tumours. , 2004, Physics in medicine and biology.
[15] Paul S Mischel,et al. MR imaging correlates of survival in patients with high-grade gliomas. , 2005, AJNR. American journal of neuroradiology.
[16] Koji Yoshimoto,et al. Molecular determinants of the response of glioblastomas to EGFR kinase inhibitors. , 2005, The New England journal of medicine.
[17] R. Mirimanoff,et al. MGMT gene silencing and benefit from temozolomide in glioblastoma. , 2005, The New England journal of medicine.
[18] R M Weisskoff,et al. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. , 2006, AJNR. American journal of neuroradiology.
[19] P. Kelly,et al. Perfusion Magnetic Resonance Imaging Predicts Patient Outcome as an Adjunct to Histopathology: A Second Reference Standard in the Surgical and Nonsurgical Treatment of Low-grade Gliomas , 2006, Neurosurgery.
[20] A. Jackson,et al. Do cerebral blood volume and contrast transfer coefficient predict prognosis in human glioma? , 2006, AJNR. American journal of neuroradiology.
[21] Toshihiro Kumabe,et al. Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. , 2006, Radiology.
[22] Areen K. Al-Bashir,et al. New algorithm for quantifying vascular changes in dynamic contrast‐enhanced MRI independent of absolute T1 values , 2007, Magnetic Resonance in Medicine.
[23] T. Hirai,et al. Malignant supratentorial astrocytoma treated with postoperative radiation therapy: prognostic value of pretreatment quantitative diffusion-weighted MR imaging. , 2007, Radiology.
[24] D. Busam,et al. An Integrated Genomic Analysis of Human Glioblastoma Multiforme , 2008, Science.
[25] K. Schmainda,et al. Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. , 2008, Radiology.
[26] Douglas C. Miller,et al. Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. , 2008, Radiology.
[27] G. Johnson,et al. Relative cerebral blood volume measurements of low-grade gliomas predict patient outcome in a multi-institution setting. , 2010, European journal of radiology.
[28] J. Debbins,et al. Optimized Preload Leakage-Correction Methods to Improve the Diagnostic Accuracy of Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging in Posttreatment Gliomas , 2010, American Journal of Neuroradiology.
[29] Melissa Bondy,et al. Polymorphisms of LIG4, BTBD2, HMGA2, and RTEL1 genes involved in the double-strand break repair pathway predict glioblastoma survival. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[30] H. Mehdorn,et al. Outcome evaluation in glioblastoma patients using different ranking scores: KPS, GOS, mRS and MRC. , 2010, European journal of cancer care.
[31] A. Olivi,et al. Prognostic significance of contrast-enhancing anaplastic astrocytomas in adults. , 2010, Journal of neurosurgery.
[32] N. Forbes,et al. Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response , 2010, British Journal of Cancer.
[33] Konstantin Nikolaou,et al. Quantitative Pulmonary Perfusion Magnetic Resonance Imaging: Influence of Temporal Resolution and Signal-to-Noise Ratio , 2010, Investigative radiology.
[34] S. Sourbron. Technical aspects of MR perfusion. , 2010, European journal of radiology.
[35] Roger Newson,et al. Comparing the Predictive Powers of Survival Models Using Harrell's C or Somers’ D , 2010 .
[36] Erwin G. Van Meir,et al. Exciting New Advances in Neuro‐Oncology: The Avenue to a Cure for Malignant Glioma , 2010, CA: a cancer journal for clinicians.
[37] M S Brown,et al. Apparent Diffusion Coefficient Histogram Analysis Stratifies Progression-Free Survival in Newly Diagnosed Bevacizumab-Treated Glioblastoma , 2011, American Journal of Neuroradiology.
[38] J. Boxerman,et al. The Role of Preload and Leakage Correction in Gadolinium-Based Cerebral Blood Volume Estimation Determined by Comparison with MION as a Criterion Standard , 2012, American Journal of Neuroradiology.
[39] L. Astrakas,et al. Diffusion tensor and dynamic susceptibility contrast MRI in glioblastoma , 2012, Clinical Neurology and Neurosurgery.
[40] Rakesh K. Gupta,et al. Dynamic Contrast-Enhanced Magnetic Resonance Imaging–Derived kep as a Potential Biomarker of Matrix Metalloproteinase 9 Expression in Patients With Glioblastoma Multiforme: A Pilot Study , 2012, Journal of computer assisted tomography.
[41] Young Suk Kim,et al. MGMT gene promoter methylation as a potent prognostic factor in glioblastoma treated with temozolomide-based chemoradiotherapy: a single-institution study. , 2012, International journal of radiation oncology, biology, physics.
[42] T. Jiang,et al. Glioblastoma with an oligodendroglioma component: distinct clinical behavior, genetic alterations, and outcome. , 2012, Neuro-oncology.
[43] M. Manzoni,et al. Gastroenteric neuroendocrine neoplasms classification: Comparison of prognostic models , 2013, Cancer.
[44] Michael Ingrisch,et al. Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer , 2013, Journal of Pharmacokinetics and Pharmacodynamics.
[45] Song-Cheol Kim,et al. Increased number of metastatic lymph nodes in adenocarcinoma of the ampulla of Vater as a prognostic factor: a proposal of new nodal classification. , 2014, Surgery.
[46] Seong Ho Park,et al. Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading , 2014, American Journal of Neuroradiology.
[47] H. Goldschmidt,et al. Revised International Staging System for Multiple Myeloma: A Report From International Myeloma Working Group. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[48] S. Choi,et al. Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging. , 2015, Radiology.
[49] J. Mercier,et al. Preoperative Prognostic Value of Dynamic Contrast-Enhanced MRI–Derived Contrast Transfer Coefficient and Plasma Volume in Patients with Cerebral Gliomas , 2015, American Journal of Neuroradiology.
[50] David Bonekamp,et al. Association of overall survival in patients with newly diagnosed glioblastoma with contrast‐enhanced perfusion MRI: Comparison of intraindividually matched T1‐ and T2*‐based bolus techniques , 2015, Journal of magnetic resonance imaging : JMRI.
[51] À. Rovira,et al. Pixel-by-Pixel Comparison of Volume Transfer Constant and Estimates of Cerebral Blood Volume from Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast-Enhanced MR Imaging in High-Grade Gliomas , 2015, American Journal of Neuroradiology.