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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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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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A Subtracted-Added-Divided Inversion Recovery (dSIR) Approach to Visualise the Effects of Microstructure on T1

Risto A Kauppinen¹, Jeromy Thotland², Pramod K Pisharady²

¹Department of Electric, Electronic and Mechanical Engineering, University of Bristol, Bristol, UK.

NMR in Biomedicine

|May 29, 2025

Summary

The novel dSIR technique enhances visualization of white matter (WM) microstructure in MRI. This method improves contrast at 7T compared to 3T, aiding in the evaluation of WM integrity.

Keywords:

T1 relaxation added and divided (dSIR)microstructure subtracted white matter

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Area of Science:

Neuroimaging
Biophysics
Magnetic Resonance Imaging

Background:

White matter (WM) microstructural features influence T1 relaxation, but visualizing these effects in vivo using standard T1-weighted MRI is challenging due to their small size.
Understanding WM microstructure is crucial for assessing neurological health and disease, yet current MRI techniques have limitations in resolving these fine details.

Purpose of the Study:

To investigate an algebraic approach, termed dSIR (difference-Summation/Integral of closely spaced inversion time images), for enhancing the visualization of WM microstructural effects on T1 relaxation in vivo.
To compare the performance of the dSIR approach at 3 Tesla (3T) and 7 Tesla (7T) magnetic field strengths.

Main Methods:

MP2RAGE MRI scans were acquired with short and long inversion times (TI) at both 3T and 7T.
The dSIR processing technique was applied by combining these closely spaced inversion time images.
dSIR signal intensities were quantitatively compared with absolute T1 relaxation time images.

Main Results:

A linear relationship was observed between dSIR signal intensity and T1 relaxation time across a range of approximately 200 ms at both 3T and 7T.
The slope of the dSIR versus T1 plot was 1.6 times greater at 7T than at 3T, indicating significantly higher dSIR contrast at 7T.
dSIR contrast successfully visualized WM tracts with high fiber-to-field angles (>75°) and revealed WM microstructural features, including axon orientation and the presence of large axons, correlating with T1 differences of ~50 ms.

Conclusions:

The dSIR signal effectively mimics T1 relaxation properties.
dSIR offers superior contrast at 7T compared to 3T, making it a promising tool for visualizing microstructural influences on T1 relaxation.
This approach holds potential for evaluating white matter integrity by making subtle microstructural effects more apparent in MRI.