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Michael Nelles

Researcher at University of Bonn

Publications -  26
Citations -  980

Michael Nelles is an academic researcher from University of Bonn. The author has contributed to research in topics: Stroke & Diffusion MRI. The author has an hindex of 13, co-authored 26 publications receiving 780 citations. Previous affiliations of Michael Nelles include University Hospital Bonn.

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Lomustine-temozolomide combination therapy versus standard temozolomide therapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter (CeTeG/NOA-09): a randomised, open-label, phase 3 trial

TL;DR: The results suggest that lomustine-temozolomide chemotherapy might improve survival compared with temozolmide standard therapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter.
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Dual-source parallel radiofrequency excitation body MR imaging compared with standard MR imaging at 3.0 T: initial clinical experience.

TL;DR: Dual-source parallel RF excitation body MR imaging enables reduced dielectric shading, improved homogeneity of the RF magnetic induction field, and accelerated imaging at 3.0 T.
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Diffusion tensor pyramidal tractography in patients with anterior choroidal artery infarcts.

TL;DR: DTT may explain resulting motor dysfunction in patients with AchoA infarcts with more notably decreased FA being an indicator for unfavorable outcome.
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Dual-source parallel RF transmission for clinical MR imaging of the spine at 3.0 T: intraindividual comparison with conventional single-source transmission.

TL;DR: While shortening examination times by approximately one-third, the dual-source parallel RF transmission mode in MR imaging of the spine yielded diagnostic image quality comparable to that with the conventional single-sourceRF transmission mode.
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Focal Liver Lesions at 3.0 T: Lesion Detectability and Image Quality with T2-weighted Imaging by Using Conventional and Dual-Source Parallel Radiofrequency Transmission

TL;DR: Compared with conventional RF transmission, parallel RF transmission significantly improved liver lesion detection rate, image quality, lesion conspicuity, and lesion contrast.