Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI.
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Emerging Techniques in Brain Tumor Imaging: What Radiologists Need to KnowDetecting tumor progression in glioma: Current standards and new techniques.Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software.Advanced MRI Techniques in the Monitoring of Treatment of Gliomas.Differentiation of pseudoprogression and real progression in glioblastoma using ADC parametric response maps.Advances in neuro-oncology imaging.Quantitative MRI for analysis of peritumoral edema in malignant gliomasStratification of pseudoprogression and true progression of glioblastoma multiform based on longitudinal diffusion tensor imaging without segmentation.Cerebral Microstructural Alterations after Radiation Therapy in High-Grade Glioma: A Diffusion Tensor Imaging-Based StudyMRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives.Assessment of early response to tumor-treating fields in newly diagnosed glioblastoma using physiologic and metabolic MRI: initial experience.Pseudoprogression as an adverse event of glioblastoma therapy.Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics.Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer.Commentary: Pitfalls in the Neuroimaging of Glioblastoma in the Era of Antiangiogenic and Immuno/Targeted Therapy.Diagnostic accuracy of proton magnetic resonance spectroscopy and perfusion-weighted imaging in brain gliomas follow-up: a single institutional experience.Conventional and advanced magnetic resonance imaging in patients with high grade glioma.Pseudoprogression of CNS metastatic disease of alveolar soft part sarcoma during anti-PDL1 treatment☆☆☆.Prediction of Pseudoprogression versus Progression using Machine Learning Algorithm in Glioblastoma
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P2860
Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI.
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2015 nî lūn-bûn
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2015年の論文
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年学术文章
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name
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@en
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@nl
type
label
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@en
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@nl
prefLabel
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@en
Differentiating Tumor Progress ...... c Susceptibility Contrast MRI.
@nl
P2093
P2860
P356
P1476
Differentiating Tumor Progress ...... ic Susceptibility Contrast MRI
@en
P2093
M Alonso-Basanta
R A Lustig
P2860
P356
10.3174/AJNR.A4474
P577
2015-10-08T00:00:00Z