high field imaging
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Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 424
Author(s):  
Francesco Sanvito ◽  
Antonella Castellano ◽  
Andrea Falini

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.


2020 ◽  
Author(s):  
Kyle M. Gilbert ◽  
L. Martyn Klassen ◽  
Alexander Mashkovtsev ◽  
Peter Zeman ◽  
Ravi S. Menon ◽  
...  

2020 ◽  
Vol 16 (S5) ◽  
Author(s):  
Joost M. Riphagen ◽  
Roy W.E. van Hooren ◽  
Linda H.G. Pagen ◽  
Benedikt A. Poser ◽  
Heidi I.L. Jacobs

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Elisa Zamboni ◽  
Valentin G Kemper ◽  
Nuno Reis Goncalves ◽  
Ke Jia ◽  
Vasilis M Karlaftis ◽  
...  

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.


BMC Neurology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
A. F. Wolters ◽  
M. Heijmans ◽  
S. Michielse ◽  
A. F. G. Leentjens ◽  
A. A. Postma ◽  
...  

2020 ◽  
Author(s):  
Enrico Schulz ◽  
Anne Stankewitz ◽  
Anderson M Winkler ◽  
Stephanie Irving ◽  
Viktor Witkovský ◽  
...  

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