Perifocal Zone of Brain Gliomas: Application of Diffusion Kurtosis and Perfusion MRI Values for Tumor Invasion Border Determination
暂无分享,去创建一个
A. Bykanov | I. Pronin | N. Zakharova | P. Nikitin | E. Pogosbekian | S. Goryaynov | I. Chekhonin | D. Usachev | A. Batalov | S. A. Galstyan | Anastasia N. Tyurina | Lyudmila M. Fadeeva | A. N. Tyurina | L. M. Fadeeva
[1] I. Pronin,et al. Arterial Spin Labeling Perfusion in Determining the IDH1 Status and Ki-67 Index in Brain Gliomas , 2022, Diagnostics.
[2] I. Pronin,et al. The Role of 3D-pCASL MRI in the Differential Diagnosis of Glioblastoma and Brain Metastases , 2022, Frontiers in Oncology.
[3] A. Bykanov,et al. 3D pCASL-perfusion in preoperative assessment of brain gliomas in large cohort of patients , 2022, Scientific reports.
[4] A. Batalov,et al. 3D pseudo-continuous arterial spin labeling-MRI (3D PCASL-MRI) in the differential diagnosis between glioblastomas and primary central nervous system lymphomas , 2022, Neuroradiology.
[5] Jun Qiu,et al. Application of diffusion kurtosis imaging to the study of edema in solid and peritumoral areas of glioma. , 2021, Magnetic resonance imaging.
[6] A. Luna,et al. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions. , 2021, European journal of radiology.
[7] G. Reifenberger,et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. , 2021, Neuro-oncology.
[8] I. Maximov,et al. Feasibility of generalised diffusion kurtosis imaging approach for brain glioma grading , 2021, Neuroradiology.
[9] C. Giordano,et al. Leptin and Notch Signaling Cooperate in Sustaining Glioblastoma Multiforme Progression , 2020, Biomolecules.
[10] J. Veraart,et al. The diagnostic role of diffusional kurtosis imaging in glioma grading and differentiation of gliomas from other intra-axial brain tumours: a systematic review with critical appraisal and meta-analysis , 2020, Neuroradiology.
[11] Jongho Lee,et al. Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma , 2019, Neuroradiology.
[12] T. Yousry,et al. Role of diffusional kurtosis imaging in grading of brain gliomas: a protocol for systematic review and meta-analysis , 2018, BMJ Open.
[13] U. Klose,et al. Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades , 2018, Clinical Neuroradiology.
[14] U Klose,et al. In vivo assessment of tumor heterogeneity in WHO 2016 glioma grades using diffusion kurtosis imaging: Diagnostic performance and improvement of feasibility in routine clinical practice. , 2017, Journal of neuroradiology. Journal de neuroradiologie.
[15] I. Maximov,et al. Differentiation of glioma malignancy grade using diffusion MRI. , 2017, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.
[16] Örjan Smedby,et al. Quantitative MRI for analysis of peritumoral edema in malignant gliomas , 2017, PloS one.
[17] P. Kalakoti,et al. High-grade Gliomas Exhibit Higher Peritumoral Fractional Anisotropy and Lower Mean Diffusivity than Intracranial Metastases , 2017, Front. Surg..
[18] Markus Nilsson,et al. Diffusion Kurtosis Imaging of Gliomas Grades II and III - A Study of Perilesional Tumor Infiltration, Tumor Grades and Subtypes at Clinical Presentation , 2017, Radiology and oncology.
[19] Elna-Marie Larsson,et al. Extension of diffuse low-grade gliomas beyond radiological borders as shown by the coregistration of histopathological and magnetic resonance imaging data. , 2016, Journal of neurosurgery.
[20] Eudocia Q Lee,et al. Assessment of Brain Tumor Response: RANO and Its Offspring , 2016, Current Treatment Options in Oncology.
[21] G. Reifenberger,et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary , 2016, Acta Neuropathologica.
[22] S. Jespersen,et al. Kurtosis fractional anisotropy, its contrast and estimation by proxy , 2016, Scientific Reports.
[23] G. Biros,et al. Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma. , 2016, Neurosurgery.
[24] J. Qin,et al. Differentiation of high-grade-astrocytomas from solitary-brain-metastases: Comparing diffusion kurtosis imaging and diffusion tensor imaging. , 2015, European journal of radiology.
[25] Wenzhen Zhu,et al. Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation , 2015, Oncotarget.
[26] Yvonne W. Lui,et al. N-acetyl-aspartate levels correlate with intra-axonal compartment parameters from diffusion MRI , 2015, NeuroImage.
[27] Jens H Jensen,et al. Quantitative assessment of diffusional kurtosis anisotropy , 2015, NMR in biomedicine.
[28] Sabine Van Huffel,et al. Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. , 2014, Neuro-oncology.
[29] L. Flors,et al. Gradient of apparent diffusion coefficient values in peritumoral edema helps in differentiation of glioblastoma from solitary metastatic lesions. , 2014, AJR. American journal of roentgenology.
[30] Scott N. Hwang,et al. Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor. , 2014, Radiology.
[31] M. Lipton,et al. Utility of Diffusion Tensor Imaging in Evaluation of the Peritumoral Region in Patients with Primary and Metastatic Brain Tumors , 2014, American Journal of Neuroradiology.
[32] A. Leemans,et al. Comprehensive framework for accurate diffusion MRI parameter estimation , 2013, Magnetic resonance in medicine.
[33] Jinsong Wu,et al. The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas , 2012, Acta Neurochirurgica.
[34] Jan Sijbers,et al. Gliomas: diffusion kurtosis MR imaging in grading. , 2012, Radiology.
[35] Dirk Troost,et al. Addressing diffuse glioma as a systemic brain disease with single-cell analysis. , 2012, Archives of neurology.
[36] Volker Seifert,et al. Intraoperative MRI guidance and extent of resection in glioma surgery: a randomised, controlled trial. , 2011, The Lancet. Oncology.
[37] Joseph A. Helpern,et al. White matter characterization with diffusional kurtosis imaging , 2011, NeuroImage.
[38] Mitchel S Berger,et al. An extent of resection threshold for newly diagnosed glioblastomas. , 2011, Journal of neurosurgery.
[39] Yi Yan,et al. Quantitative analysis of glioma cell invasion by diffusion tensor imaging , 2010, Journal of Clinical Neuroscience.
[40] Akio Asai,et al. Morphological and flow cytometric analysis of cell infiltration in glioblastoma: a comparison of autopsy brain and neuroimaging , 2010, Brain Tumor Pathology.
[41] Alina Jurcoane,et al. Elevated peritumoural rCBV values as a mean to differentiate metastases from high-grade gliomas , 2010, Acta Neurochirurgica.
[42] J. Helpern,et al. MRI quantification of non‐Gaussian water diffusion by kurtosis analysis , 2010, NMR in biomedicine.
[43] C. Daumas-Duport,et al. Diffuse low-grade oligodendrogliomas extend beyond MRI-defined abnormalities , 2010, Neurology.
[44] H. Lanfermann,et al. Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. , 2010, Radiology.
[45] Naoki Kagawa,et al. Use of fractional anisotropy for determination of the cut-off value in 11C-methionine positron emission tomography for glioma , 2009, NeuroImage.
[46] Pieter Wesseling,et al. Diffuse glioma growth: a guerilla war , 2007, Acta Neuropathologica.
[47] Thomas L Chenevert,et al. Differentiation of recurrent brain tumor versus radiation injury using diffusion tensor imaging in patients with new contrast-enhancing lesions. , 2006, Magnetic resonance imaging.
[48] T. Carpenter,et al. Improved delineation of glioma margins and regions of infiltration with the use of diffusion tensor imaging: an image-guided biopsy study. , 2006, AJNR. American journal of neuroradiology.
[49] S. Brockstedt,et al. Tumor extension in high-grade gliomas assessed with diffusion magnetic resonance imaging: values and lesion-to-brain ratios of apparent diffusion coefficient and fractional anisotropy , 2006, Acta radiologica.
[50] B Stieltjes,et al. Detection of tumour infiltration in axonal fibre bundles using diffusion tensor imaging , 2005, The international journal of medical robotics + computer assisted surgery : MRCAS.
[51] J. Helpern,et al. Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.
[52] R. Henkelman,et al. Identification of human brain tumour initiating cells , 2004, Nature.
[53] Peter McGraw,et al. Peritumoral brain regions in gliomas and meningiomas: investigation with isotropic diffusion-weighted MR imaging and diffusion-tensor MR imaging. , 2004, Radiology.
[54] Mitchel S Berger,et al. 3D MRSI for resected high-grade gliomas before RT: tumor extent according to metabolic activity in relation to MRI. , 2004, International journal of radiation oncology, biology, physics.
[55] A. Bykanov,et al. [Magnetic resonance relaxometry in high-grade glioma subregion assessment - neuroimaging and morphological correlates]. , 2021, Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko.
[56] A. Potapov,et al. [Non-contrast ASL perfusion in preoperative diagnosis of supratentorial gliomas]. , 2018, Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko.
[57] Salvador Castaneda Vega,et al. In vivo molecular profiling of human glioma using diffusion kurtosis imaging , 2016, Journal of Neuro-Oncology.
[58] E. Melhem,et al. Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain. , 2014, AJR. American journal of roentgenology.