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Magnetic Resonance Imaging

Magnetic Resonance Imaging

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...

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Related Experiment Video

Updated: Aug 5, 2025

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

Three-dimensional multi-parameter brain mapping using MR fingerprinting.

Rajiv G Menon¹, Azadeh Sharafi², Marco Muccio¹

¹New York University Grossman School of Medicine.

Research Square

|March 30, 2023

Summary

This summary is machine-generated.

This study introduces a 3D multi-parameter MR fingerprinting (MRF) technique for brain imaging. The method efficiently quantifies T1, T2, and T1ρ, aiding in neurological disease characterization.

Keywords:

MR fingerprinting brain imaging multiple sclerosis quantitative mapping white matter lesion

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Last Updated: Aug 5, 2025

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

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Published on: June 30, 2018

Area of Science:

Radiology and Biomedical Imaging
Neuroimaging
Magnetic Resonance Imaging

Background:

Accurate characterization of brain tissue properties is crucial for diagnosing neurological diseases.
Existing MRI techniques may require long scan times or lack the ability to simultaneously quantify multiple tissue parameters.

Approach:

Developed and tested a 3D multi-parameter MR fingerprinting (MRF) technique for simultaneous quantification of T1, T2, and T1ρ.
Validated the technique in standardized phantoms and applied it to healthy volunteers and multiple sclerosis (MS) patients.
Assessed repeatability using Bland-Altman plots and intra-class correlation coefficient (ICC), and compared results in MS patients using Student T-tests.

Key Points:

The 3D-MRF technique successfully generated quantitative parametric maps for T1, T2, and T1ρ.
Phantom studies showed excellent agreement with reference mapping techniques.
Repeatability assessments demonstrated the technique's reliability in quantifying tissue properties.

Conclusions:

The 3D-MRF technique offers simultaneous quantification of T1, T2, and T1ρ in clinically feasible scan times.
This multi-parametric approach enhances the potential for detecting and differentiating brain lesions.
The technique shows promise for advancing imaging biomarker research in neurological diseases like MS.