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Title:

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas.

Document type:
Journal Article
Author(s):
Eichinger, Paul; Alberts, Esther; Delbridge, Claire; Trebeschi, Stefano; Valentinitsch, Alexander; Bette, Stefanie; Huber, Thomas; Gempt, Jens; Meyer, Bernhard; Schlegel, Juergen; Zimmer, Claus; Kirschke, Jan S; Menze, Bjoern H; Wiestler, Benedikt
Abstract:
We hypothesized that machine learning analysis based on texture information from the preoperative MRI can predict IDH mutational status in newly diagnosed WHO grade II and III gliomas. This retrospective study included in total 79 consecutive patients with a newly diagnosed WHO grade II or III glioma. Local binary pattern texture features were generated from preoperative B0 and fractional anisotropy (FA) diffusion tensor imaging. Using a training set of 59 patients, a single hidden layer neural...     »
Journal title abbreviation:
Sci Rep
Year:
2017
Journal volume:
7
Journal issue:
1
Pages contribution:
13396
Language:
eng
Fulltext / DOI:
doi:10.1038/s41598-017-13679-4
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/29042619
Print-ISSN:
2045-2322
TUM Institution:
Fachgebiet Neuroradiologie (Prof. Zimmer); Neurochirurgische Klinik und Poliklinik
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