Advanced magnetic resonance imaging in glioblastoma: a review.
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Spyridon Bakas | Gaurav Shukla | Rahul Nikam | Wenyin Shi | S. Bakas | G. Shukla | G. Alexander | Rahul M. Nikam | K. Talekar | J. Palmer | W. Shi | Joshua D Palmer | Gregory S Alexander | Kiran Talekar
[1] Christos Davatzikos,et al. In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The ϕ-Index , 2017, Clinical Cancer Research.
[3] S. Cha,et al. Update on brain tumor imaging: from anatomy to physiology. , 2006, AJNR. American journal of neuroradiology.
[4] B. Małkowski,et al. Pre-irradiation tumour volumes defined by MRI and dual time-point FET-PET for the prediction of glioblastoma multiforme recurrence: A prospective study. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[5] P. Bagri,et al. Addition of magnetic resonance imaging to computed tomography-based three-dimensional conformal radiotherapy planning for postoperative treatment of astrocytomas: Changes in tumor volume and isocenter shift , 2015, South Asian Journal of Cancer.
[6] Walter J Curran,et al. Dose-dense temozolomide for newly diagnosed glioblastoma: a randomized phase III clinical trial. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[7] Mitchel S Berger,et al. Functional outcome after language mapping for glioma resection. , 2008, The New England journal of medicine.
[8] A. Field,et al. Mean apparent diffusion coefficient values in defining radiotherapy planning target volumes in glioblastoma. , 2015, Quantitative imaging in medicine and surgery.
[9] Thomas Filleron,et al. Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme. , 2014, International journal of radiation oncology, biology, physics.
[10] R. Kerbel. Tumor angiogenesis: past, present and the near future. , 2000, Carcinogenesis.
[11] Gang Wang,et al. Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors , 2016, Radiation Oncology.
[12] A. Kaye,et al. Early perfusion MRI predicts survival outcome in patients with recurrent glioblastoma treated with bevacizumab and carboplatin , 2016, Journal of Neuro-Oncology.
[13] N. Magné,et al. Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation , 2016, European Radiology.
[14] Veit Rohde,et al. EXTENT OF RESECTION AND SURVIVAL IN GLIOBLASTOMA MULTIFORME: IDENTIFICATION OF AND ADJUSTMENT FOR BIAS , 2008, Neurosurgery.
[15] Martin Sill,et al. Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response , 2016, Clinical Cancer Research.
[16] Susan M. Chang,et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[17] Luke Macyszyn,et al. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques. , 2016, Neuro-oncology.
[18] P. Wen,et al. Demonstration of DCE-MRI as an early pharmacodynamic biomarker of response to VEGF Trap in glioblastoma , 2016, Journal of Neuro-Oncology.
[19] Christos Davatzikos,et al. Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework , 2016, BrainLes@MICCAI.
[20] Brian B. Avants,et al. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) , 2015, IEEE Transactions on Medical Imaging.
[21] Max Wintermark,et al. Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival. , 2015, Neuro-oncology.
[22] Maciej A Mazurowski,et al. Algorithmic three-dimensional analysis of tumor shape in MRI improves prognosis of survival in glioblastoma: a multi-institutional study , 2017, Journal of Neuro-Oncology.
[23] J. Barnholtz-Sloan,et al. American Brain Tumor Association Adolescent and Young Adult Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008-2012. , 2016, Neuro-oncology.
[24] J. Chaganti,et al. Accuracy of percentage of signal intensity recovery and relative cerebral blood volume derived from dynamic susceptibility-weighted, contrast-enhanced MRI in the preoperative diagnosis of cerebral tumours , 2015, The neuroradiology journal.
[25] K Sartor,et al. Early postoperative magnetic resonance imaging after resection of malignant glioma: objective evaluation of residual tumor and its influence on regrowth and prognosis. , 1994, Neurosurgery.
[26] P. LaViolette,et al. Evaluation of pre-radiotherapy apparent diffusion coefficient (ADC): patterns of recurrence and survival outcomes analysis in patients treated for glioblastoma multiforme , 2015, Journal of Neuro-Oncology.
[27] R. Velthuizen,et al. Brain tumor target volume determination for radiation treatment planning through automated MRI segmentation. , 2004, International journal of radiation oncology, biology, physics.
[28] Jae-Uk Jeong,et al. Evaluation of variability in target volume delineation for newly diagnosed glioblastoma: a multi-institutional study from the Korean Radiation Oncology Group , 2015, Radiation Oncology.
[29] Z. Ram,et al. Dynamics of FLAIR Volume Changes in Glioblastoma and Prediction of Survival , 2017, Annals of Surgical Oncology.
[30] T. Cloughesy,et al. Response Assessment Criteria for Glioblastoma: Practical Adaptation and Implementation in Clinical Trials of Antiangiogenic Therapy , 2013, Current Neurology and Neuroscience Reports.
[31] R. Mirimanoff,et al. Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. , 2009, The Lancet. Oncology.
[32] Bilwaj Gaonkar,et al. GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation , 2015, Brainles@MICCAI.
[33] Kevin Petrecca,et al. Failure pattern following complete resection plus radiotherapy and temozolomide is at the resection margin in patients with glioblastoma , 2012, Journal of Neuro-Oncology.
[34] Albert Lai,et al. Time course of imaging changes of GBM during extended bevacizumab treatment , 2008, Journal of Neuro-Oncology.
[35] Dima Suki,et al. Association of the Extent of Resection With Survival in Glioblastoma: A Systematic Review and Meta-analysis. , 2016, JAMA oncology.
[36] Eduard Schreibmann,et al. Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients. , 2016, Neuro-oncology.
[37] T. Cloughesy,et al. MRI in patients with high-grade gliomas treated with bevacizumab and chemotherapy , 2006, Neurology.
[38] John A Butman,et al. Phase II trial of single-agent bevacizumab followed by bevacizumab plus irinotecan at tumor progression in recurrent glioblastoma. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[39] Paolo G P Nucifora,et al. Use of diffusion tensor imaging in glioma resection. , 2013, Neurosurgical focus.
[40] Mitchel S. Berger,et al. Operative techniques for gliomas and the value of extent of resection , 2009, Neurotherapeutics.
[41] Z L Gokaslan,et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. , 2001, Journal of neurosurgery.
[42] H. Aerts. The Potential of Radiomic-Based Phenotyping in Precision Medicine: A Review. , 2016, JAMA oncology.
[43] T. Cascino,et al. Response criteria for phase II studies of supratentorial malignant glioma. , 1990, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[44] Shiao Y. Woo,et al. Evaluation of peritumoral edema in the delineation of radiotherapy clinical target volumes for glioblastoma. , 2007, International journal of radiation oncology, biology, physics.
[45] Seung-Koo Lee,et al. Diffusion tensor and perfusion imaging of brain tumors in high-field MR imaging. , 2012, Neuroimaging clinics of North America.
[46] J. K. Smith,et al. Vessel tortuosity and brain tumor malignancy: a blinded study. , 2005, Academic radiology.
[47] J. Lemée,et al. Intratumoral heterogeneity in glioblastoma: don't forget the peritumoral brain zone. , 2015, Neuro-oncology.
[48] G. Biros,et al. Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma. , 2016, Neurosurgery.
[49] Tao Jiang,et al. Residual low ADC and high FA at the resection margin correlate with poor chemoradiation response and overall survival in high-grade glioma patients. , 2016, European journal of radiology.
[50] Luke Macyszyn,et al. Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity. , 2014, Radiology.
[51] J. Gillard,et al. Imaging biomarkers of brain tumour margin and tumour invasion. , 2011, The British journal of radiology.
[52] Martin J. van den Bent,et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. , 2005, The New England journal of medicine.
[53] Tae Min Kim,et al. Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging , 2017, European Radiology.
[54] A. Brandes,et al. MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[55] Geoffrey S Young,et al. Advanced MRI of adult brain tumors. , 2007, Neurologic clinics.
[56] Estanislao Arana,et al. Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study , 2017, European Radiology.
[57] Naoya Hashimoto,et al. Immunotherapy response assessment in neuro-oncology: a report of the RANO working group. , 2015, The Lancet. Oncology.
[58] M A Deeley,et al. Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study , 2011, Physics in medicine and biology.