Structural Mri Acquisition
Structural Mri Acquisition - Related Videos
11:00
Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
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Cited by 1 •
2021
This article provides a straightforward protocol for acquiring good quality electroencephalography (EEG) data during simultaneous EEG and functional magnetic resonance imaging by utilizing readily available medical products.
06:06
Optogenetic Functional MRI
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This protocol describes the steps and data analysis required to successfully perform optogenetic functional magnetic resonance imaging (ofMRI). ofMRI is a novel technique that combines high-field fMRI readout with optogenetic stimulation, allowing for cell type-specific mapping of functional neural circuits and their dynamics across the whole living brain.
12:27
Noninvasive In Vivo Small Animal MRI and MRS: Basic Experimental Procedures
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Cited by 9 •
2009
This work describes basic procedures of noninvasive small animal MRI and MRS in vivo.
16:20
Hyperpolarized Xenon for NMR and MRI Applications
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Cited by 28 •
2012
The production of hyperpolarized xenon by means of spin exchange optical pumping (SEOP) is described. This method yields a ~10000-fold enhancement of the nuclear spin polarization of Xe-129 and has applications in nuclear magnetic resonance spectroscopy and imaging. Examples of gas phase and solution state experiments are given.
08:16
High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem
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Cited by 5 •
2015
Here we present a protocol to determine the minimum number images that needed to be registered and averaged to resolve subcortical structures and test whether the individual layers of the LGN could be resolved in the absence of physiological noise.
FAQs
Sequence settings determine whether anatomical images emphasize T1- or T2-related tissue contrast. This changes the relative appearance of brain tissues and can make particular structural boundaries more distinguishable. Choosing an appropriate contrast therefore affects how clearly researchers assess anatomy, identify abnormalities, and perform downstream measurements such as cortical thickness or brain-volume estimation.
Spatial encoding assigns returning hydrogen-nucleus signals to specific locations, allowing the acquisition to represent anatomy as slices or a three-dimensional volume. The selected representation influences how researchers inspect brain structure and prepare images for quantitative analysis. Three-dimensional anatomical data are especially useful when measurements require consistent evaluation across multiple brain regions.
Motion can reduce the reliability of anatomical comparisons by disturbing the consistency of the acquired images. This matters when researchers compare cortical thickness or brain volume across individuals or studies, because apparent differences may reflect acquisition quality rather than anatomy. Careful motion control during scanning therefore supports more dependable structural estimates and interpretations.
Structural images provide an anatomical framework that can be aligned with functional or diffusion MRI data. This alignment connects measured brain activity or diffusion-related information with specific anatomical locations. In neuroscience studies, combining these data types helps place other imaging findings within the brain’s structural context without treating anatomical, functional, and diffusion measurements as interchangeable.
High-resolution anatomical images, appropriate tissue contrast, and controlled participant motion provide the foundation for structural measurements. Sequence settings such as T1 or T2 weighting help determine how tissues appear, while slice-based or three-dimensional encoding captures their spatial organization. These choices support analyses that estimate cortical thickness, assess brain volume, and compare anatomy across individuals.
A study first acquires anatomical images with selected sequence settings and controlled participant motion. The resulting slices or three-dimensional volumes can then be examined for abnormalities or analyzed quantitatively. Researchers may also align these structural data with functional or diffusion MRI, allowing anatomical measurements and other imaging findings to be interpreted together.
They are useful when the research question concerns differences or irregularities in brain anatomy. High-resolution views allow investigators to inspect structural organization and place potential abnormalities within a defined anatomical context. The same datasets can also support quantitative measurements, helping studies examine whether observed anatomical variation relates to cortical thickness or overall brain volume.
Consistent acquisition conditions make structural comparisons more interpretable. Differences in sequence settings, tissue contrast, spatial representation, or motion control can influence the resulting images and therefore affect anatomical measurements. Maintaining comparable approaches helps researchers distinguish biological variation from differences introduced during imaging, which is essential for reliable comparisons of cortical thickness and brain volume.