Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study-Reference-Cited by-同舟云学术

Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study

Published:2018-04-17 Issue:1 Volume:8 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Bisdas Sotirios^ORCID,Shen Haocheng,Thust Steffi,Katsaros Vasileios,Stranjalis George,Boskos Christos,Brandner Sebastian^ORCID,Zhang Jianguo

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-018-24438-4.pdf

Reference35 articles.

1. Patterson, D. M., Padhani, A. R. & Collins, D. J. Technology insight: water diffusion MRI–a potential new biomarker of response to cancer therapy. Nat Clin Pract Oncol 5, 220–233 (2008).

2. LaViolette, P. S. et al. Precise ex vivo histological validation of heightened cellularity and diffusion-restricted necrosis in regions of dark apparent diffusion coefficient in 7 cases of high-grade glioma. Neuro Oncol 16, 1599–1606 (2014).

3. Jensen, J. H. & Helpern, J. A. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23, 698–710 (2010).

4. Raab, P., Hattingen, E., Franz, K., Zanella, F. E. & Lanfermann, H. Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology 254, 876–881 (2010).

5. Van Cauter, S. et al. Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro Oncol 16, 1010–1021 (2014).

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