Direct Glyph-based Visualization of Diffusion MR Data Using Deformed Spheres

2008 ◽  
pp. 185-204 ◽  
Author(s):  
Martin Domin ◽  
Sönke Langner ◽  
Norbert Hosten ◽  
Lars Linsen
Keyword(s):  
Diffusion Mr

Determination of Residual Stress with Diffusion MR Method in Cortical and Trabecular Sections of Human Vertebral Bone Tissue

2021 ◽  
Vol 27 (3) ◽  
pp. 215-218
Author(s):  
Cemil Sert ◽  
◽  
Abdurrahim Dusak ◽  
Mehmet Akif Altay ◽  
◽  
...  
Keyword(s):  
Residual Stress ◽  
Bone Tissue ◽  
Vertebral Bone ◽  
Diffusion Mr

Segmentation of Prostate in Diffusion MR Images via Clustering

2017 ◽  
pp. 471-478 ◽  
Author(s):  
Junjie Zhang ◽  
Sameer Baig ◽  
Alexander Wong ◽  
Masoom A. Haider ◽  
Farzad Khalvati
Keyword(s):  
Mr Images ◽  
Diffusion Mr

scholarly journals Interpretation of Diffusion MR Imaging Data using a Gamma Distribution Model

2014 ◽  
Vol 13 (3) ◽  
pp. 191-195 ◽  
Author(s):  
Koichi OSHIO ◽  
Hiroshi SHINMOTO ◽  
Robert V. MULKERN
Keyword(s):  
Mr Imaging ◽  
Gamma Distribution ◽  
Distribution Model ◽  
Imaging Data ◽  
Diffusion Mr ◽  
Diffusion Mr Imaging

Diffusion MR of Acute Stroke

2010 ◽  
pp. 145-174
Author(s):  
Anne Catherine Kim ◽  
A. Kiruluta ◽  
R. Gilberto González ◽  
Pamela W. Schaefer
Keyword(s):  
Acute Stroke ◽  
Diffusion Mr

scholarly journals Diffusion Magnetic Resonance Imaging Phenotypes Predict Overall Survival Benefit From Bevacizumab or Surgery in Recurrent Glioblastoma With Large Tumor Burden

Neurosurgery ◽  
2020 ◽  
Vol 87 (5) ◽  
pp. 931-938 ◽  
Author(s):  
Kunal S Patel ◽  
Richard G Everson ◽  
Jingwen Yao ◽  
Catalina Raymond ◽  
Jodi Goldman ◽  
...  
Keyword(s):  
Overall Survival ◽  
Magnetic Resonance ◽  
Large Volume ◽  
Survival Benefit ◽  
Tumor Burden ◽  
Recurrent Glioblastoma ◽  
Large Tumor ◽  
Diffusion Mr ◽  
Large Tumor Burden ◽  
Mr Characteristics

Abstract Background Diffusion magnetic resonance (MR) characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-vascular endothelial growth factor (VEGF) therapy; however, its use in large volume recurrence has not been evaluated. Objective To determine if diffusion MR characteristics can predict survival outcomes in patients with large volume recurrent glioblastoma treated with bevacizumab or repeat resection. Methods A total of 32 patients with large volume (>20 cc or > 3.4 cm diameter) recurrent glioblastoma treated with bevacizumab and 35 patients treated with repeat surgery were included. Pretreatment tumor volume and apparent diffusion coefficient (ADC) histogram analysis were used to phenotype patients as having high (>1.24 μm2/ms) or low (<1.24 μm2/ms) ADCL, the mean value of the lower peak in a double Gaussian model of the ADC histogram within the contrast enhancing tumor. Results In bevacizumab and surgical cohorts, volume was correlated with overall survival (Bevacizumab: P = .009, HR = 1.02; Surgical: P = .006, HR = 0.96). ADCL was an independent predictor of survival in the bevacizumab cohort (P = .049, HR = 0.44), but not the surgical cohort (P = .273, HR = 0.67). There was a survival advantage of surgery over bevacizumab in patients with low ADCL (P = .036, HR = 0.43) but not in patients with high ADCL (P = .284, HR = 0.69). Conclusion Pretreatment diffusion MR imaging is an independent predictive biomarker for overall survival in recurrent glioblastoma with a large tumor burden. Large tumors with low ADCL have a survival benefit when treated with surgical resection, whereas large tumors with high ADCL may be best managed with bevacizumab.

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