Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

4.9K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
4.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same authorSame journal

Dependence of the Extra-Cellular Diffusion Coefficient on the Fractions of Neurites and Cell Bodies in Gray Matter.

Magnetic resonance in medicine·2026
Same author

Axon Diameter Mapping in the Living Human Brain with Ultra-High-Gradient Diffusion MRI at 500 mT/m Gradient Strength.

Human brain mapping·2026
Same author

On the Utility of Foundation Models for Fast MRI: Vision-Language-Guided Image Reconstruction.

Magnetic resonance in medicine·2026
Same author

Visualizing cortical laminar architecture in the living human brain using next-generation ultra-high-gradient diffusion MRI.

Communications biology·2026
Same author

Complementary Sensitivity of Fixed-Time and Fixed-Oscillation Regimes to Exchange and Structural Disorder in the Human Brain Revealed Using Oscillating-Gradient Diffusion MRI With Ultra-Strong Gradients.

Magnetic resonance in medicine·2026
Same author

A Dynamic Shim Approach for Correcting Eddy Current Effects in Diffusion-Prepared MRI Acquisition Using a Multi-Coil AC/DC Shim-Array.

Magnetic resonance in medicine·2026
Same journal

A Comparison of Tissue Property Values Estimated Using Conventional Cardiac MRF and MT-Cardiac MRF.

Magnetic resonance in medicine·2026
Same journal

Triple-Pulse <sup>23</sup>Na MRI Sequence (TriNa) for Simultaneous Acquisition of Spin-Density-Weighted and Fluid-Attenuated Images.

Magnetic resonance in medicine·2026
Same journal

Evaluation of Phantom Doping Materials in Quantitative Susceptibility Mapping.

Magnetic resonance in medicine·2026
Same journal

Design of an 8-Channel Transmit 32-Channel Receive 11.7T Head Coil and Evaluation of SNR Gains.

Magnetic resonance in medicine·2026
Same journal

The Potential for Absolute Temperature Imaging Based on Brain Metabolites Using an FID-Shifting Approach in Gradient Echo Planar Spectroscopic Imaging (GREPSI).

Magnetic resonance in medicine·2026
See all related articles

Related Experiment Video

Updated: May 21, 2025

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

8.6K

Simultaneous 3D quantitative magnetization transfer imaging and susceptibility mapping.

Albert Jang1,2, Kwok-Shing Chan1,2, Azma Mareyam1,2

  • 1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.

Magnetic Resonance in Medicine
|March 17, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new MRI method to simultaneously measure magnetization transfer (MT), tissue susceptibility (χ), and T2* in the brain. The validated technique provides accurate, bias-free quantification of these key tissue properties.

Keywords:
magnetization transferquantitative imagingquantitative susceptibility mappingtissue modeling

More Related Videos

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

19.3K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.3K

Related Experiment Videos

Last Updated: May 21, 2025

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

8.6K
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

19.3K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.3K

Area of Science:

  • Magnetic Resonance Imaging
  • Biophysics
  • Medical Physics

Background:

  • Magnetization transfer (MT) and susceptibility mapping are crucial for characterizing brain tissue.
  • Current methods often require separate acquisitions, increasing scan time and potential for errors.
  • Simultaneous quantification of MT, susceptibility (χ), and T2* remains a challenge.

Purpose of the Study:

  • To develop and validate a unified MRI acquisition and modeling strategy.
  • To simultaneously quantify magnetization transfer (MT), tissue susceptibility (χ), and T2*.
  • To overcome limitations of separate measurement techniques and B1+ bias.

Main Methods:

  • Developed an RF-spoiled gradient-echo sequence with off-resonance irradiation for MT.
  • Incorporated multi-echo acquisition to capture signal magnitude and phase evolution.
  • Utilized a binary spin-bath MT model with B1+ inhomogeneity correction and analytical signal modeling.

Main Results:

  • Successfully acquired simultaneous 3D T1F, f, kF, χ, and T2* maps of the whole brain in vivo.
  • Demonstrated good agreement between regional analysis results and previously reported literature values.
  • Validated the method's feasibility and accuracy in five healthy subjects.

Conclusions:

  • A novel, unified acquisition and modeling strategy enables simultaneous MT, susceptibility, and T2* quantification.
  • The method leverages both signal magnitude and phase for comprehensive tissue characterization.
  • The approach provides accurate, B1+-bias-free measurements, advancing neuroimaging capabilities.