Structural Mri
Structural Mri - Related Videos
06:06
Optogenetic Functional MRI
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Cited by 15 •
2016
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.
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.
08:20
MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
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Cited by 31 •
2015
Here we outline the procedure for MRI-guided repetitive transcranial magnetic stimulation to the dorsomedial prefrontal cortex as an experimental treatment for major depressive disorder.
05:07
Pulmonary Structural MRI using Free-Breathing, Self-Gated Ultra-short Echo Time Imaging
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2024
A protocol is described for generating high-resolution structural images of the lungs using ultra-short-echo time (UTE) Magnetic Resonance Imaging (MRI). This protocol allows for images to be acquired using a simple MRI pulse sequence during free-breathing.
06:58
Synthesis of an In vivo MRI-detectable Apoptosis Probe
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Cited by 3 •
2012
Early detection of apoptosis may identify at-risk cell populations in a variety of diseases. Here we demonstrate a method to link an early apoptosis-detection protein (Annexin V) to a MRI-detectable iron oxide nanoparticle (SPIO). This method may be extended to other proteins of interest to generate MRI-detectable molecular imaging probes.
FAQs
After radiofrequency pulses disturb hydrogen nuclei, the nuclei return toward equilibrium and emit detectable signals. Their relaxation behavior differs according to tissue composition, so the measured signals vary across anatomical regions. Image reconstruction converts these differences into contrast, allowing structures such as gray matter, white matter, muscle, and organs to appear distinctly within the same three-dimensional dataset.
Spatial encoding links each detected signal to a location within the subject. The system then reconstructs those location-specific signals into an image rather than treating them as a single undifferentiated measurement. This process supports three-dimensional visualization and permits researchers to examine the arrangement, boundaries, and morphology of biological tissues in anatomical context.
Tissue composition and relaxation behavior determine how strongly different regions contribute to the reconstructed image. Consequently, anatomical boundaries and tissue classes can be distinguished through signal contrast rather than by visual inspection alone. Interpreting these differences is important when mapping anatomy or comparing the morphology of gray matter, white matter, muscle, and organs.
The three-dimensional anatomical images provide a basis for mapping structures and assessing their size and shape. Researchers can use these data to measure tissue volume and characterize morphology, meaning the form and structural organization of anatomical regions. Such measurements support comparisons among tissues or subjects and help identify changes in biological structure.
A typical workflow places the subject in the magnetic field, applies radiofrequency pulses, detects signals produced as hydrogen nuclei return toward equilibrium, and reconstructs those signals into spatially organized images. The resulting dataset can then be examined for anatomical mapping, tissue-volume measurement, morphology, or evidence of structural abnormalities.
Its noninvasive character allows researchers to examine tissue anatomy in living organisms without relying only on destructive procedures. Because the method produces detailed three-dimensional views, investigators can relate biological structure to development, disease, or treatment-related change. This combination supports anatomical study while preserving the possibility of observing the same organism over time.
Repeated structural MRI assessments can document anatomical change across time. By comparing tissue volume, morphology, and other mapped features across scans, researchers can evaluate patterns associated with development, disease progression, or responses to treatment. The longitudinal perspective is especially useful because it focuses on change within an ongoing biological process rather than on a single anatomical snapshot.