About this Research Topic
Magnetic resonance imaging (MRI) at 3T is a cornerstone for neuroscientific research due to its widespread availability and versatility. The advent of ultra-high field (≥7T) scanners has significantly advanced the spatial and temporal resolution capabilities of MRI, setting new benchmarks for imaging quality. However, recent technological advancements in data acquisition and processing have revitalized the potential of 3T MRI, making it a viable alternative for high-resolution imaging. Over the past 15 years, insights from 7T MRI have been instrumental in pushing the boundaries of what can be achieved at 3T. Despite these advancements, there remain significant gaps in fully leveraging 3T MRI for cognitive and clinical neuroscience, particularly in achieving sub-millimeter and sub-second resolution. Addressing these gaps requires innovative approaches to hardware, software, and imaging protocols to maximize the potential of 3T MRI.
This research topic aims to collect recent research on new methods and protocols that maximize the potential of 3T (f)MRI. We aim to also encourage high spatio-temporal MRI at 3T to become the new state-of-the-art for cognitive and clinical neuroscience applications. To that end, the implementation of optimal acquisition strategies will depend mainly on two aspects: adapting existing protocols available at higher field strengths (and overcoming the limitations imposed by a lower B0), and exploiting the strengths of 3T scanners compared to higher field scanners (e.g., wider availability, fewer artifacts, better patient comfort).
To gather further insights into the spatio-temporal limits of MRI at 3T, we welcome articles addressing, but not limited to, the following themes:
- High spatial and/or temporal resolution MRI (e.g., layer- columnar-fMRI, fast fMRI)
- New contrasts and novel applications which highlight different features of brain structure, function, and physiology (e.g., non-BOLD, diffusion, QSM)
- New methods, protocols, or analysis tools for high-resolution imaging at 3T
- Novel denoising or other image processing algorithms to improve robustness and reliability of responses
- Applications of high-resolution MRI to clinical and cognitive neuroscience questions, particularly in subcortical and brainstem structures.
Professor Norris is involved in a patent on Arterial Blood Contrast, that is held by Radboud University. The other editors do not declare any potential conflict of interests.
This research topic aims to collect recent research on new methods and protocols that maximize the potential of 3T (f)MRI. We aim to also encourage high spatio-temporal MRI at 3T to become the new state-of-the-art for cognitive and clinical neuroscience applications. To that end, the implementation of optimal acquisition strategies will depend mainly on two aspects: adapting existing protocols available at higher field strengths (and overcoming the limitations imposed by a lower B0), and exploiting the strengths of 3T scanners compared to higher field scanners (e.g., wider availability, fewer artifacts, better patient comfort).
To gather further insights into the spatio-temporal limits of MRI at 3T, we welcome articles addressing, but not limited to, the following themes:
- High spatial and/or temporal resolution MRI (e.g., layer- columnar-fMRI, fast fMRI)
- New contrasts and novel applications which highlight different features of brain structure, function, and physiology (e.g., non-BOLD, diffusion, QSM)
- New methods, protocols, or analysis tools for high-resolution imaging at 3T
- Novel denoising or other image processing algorithms to improve robustness and reliability of responses
- Applications of high-resolution MRI to clinical and cognitive neuroscience questions, particularly in subcortical and brainstem structures.
Professor Norris is involved in a patent on Arterial Blood Contrast, that is held by Radboud University. The other editors do not declare any potential conflict of interests.
Keywords: fMRI, high-resolution, fast fMRI, layers, columns, 3T, MRI, ASL, BOLD, VASO, vascular, diffusion, signal modelling, denoising, neurofluids, brain clearance, spectroscopy
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