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Magnetic Susceptibility and Permeability

Magnetic Susceptibility and Permeability

In linear magnetic materials, like paramagnets and diamagnets, magnetization is proportional to the magnetic field intensity. The constant of proportionality, a dimensionless number, is called magnetic susceptibility. The value of the susceptibility depends on the type of material.
When diamagnetic materials are placed under an external magnetic field, the moments opposite to the field are induced. Hence, the susceptibility for diamagnets has a minimal negative value of 10-5–10-6. Since...

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Updated: Jul 20, 2025

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

Thin slab quantitative susceptibility mapping.

Nashwan Naji¹, Alan Wilman¹

¹Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.

Magnetic Resonance in Medicine

|August 1, 2023

Summary

This summary is machine-generated.

This study introduces a novel method for quantitative susceptibility mapping (QSM) using low-resolution data to improve high-resolution, thin slab reconstructions. This approach enables faster, focal QSM acquisitions with improved accuracy.

Keywords:

3T focal acquisition quantitative susceptibility mapping (QSM)thin slab

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Area of Science:

Medical Imaging
Biophysics
Neuroimaging

Background:

Quantitative Susceptibility Mapping (QSM) from thin slabs faces challenges like underestimation due to background-field removal errors.
Solving 3D-inversion problems with reduced data support, especially along the main magnetic field, is difficult.

Purpose of the Study:

To improve QSM reconstruction from thin slabs by incorporating additional low-resolution data.
To enable reliable QSM from focal acquisitions with reduced scan times.

Main Methods:

Proposed a method using rapid, low-resolution data with extended coverage to enhance background-field estimation.
Applied this to high-resolution, thin slab data for improved inversion regularization.
Tested with simulated and in-vivo brain data at 3T, comparing to standard large volume methods.

Main Results:

Achieved in-vivo high-resolution QSM from thin slabs (10.4 mm width) using a 24x coarser low-resolution dataset.
Simulations demonstrated consistent measurements from slabs of at least eight slices.
Optimized low-resolution data requirements for <5% mean ROI error.

Conclusions:

The proposed method facilitates focal QSM acquisitions at sub-millimeter resolution.
This enables significantly reduced acquisition times for targeted QSM imaging.