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Updated: Jul 9, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

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Cartesian MPnRAGE for Efficient Simultaneous Multi-Contrast and Quantitative Relaxometry Imaging.

Carly A Allen¹, Kevin M Johnson^1,2, Bernadette T Gillick^3,4

¹Department of Medical Physics, The University of Wisconsin-Madison, Madison, Wisconsin, USA.

Magnetic Resonance in Medicine

|July 8, 2026

Summary

This summary is machine-generated.

A new brain imaging sequence, Cartesian MPnRAGE, rapidly generates quantitative T1 maps and multiple T1-weighted images. This efficient method offers accurate tissue differentiation in under five minutes.

Keywords:

MPRAGE T1 mapping T1‐weighted imaging double inversion recovery inversion recovery quantitative imaging relaxometry

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Area of Science:

Magnetic Resonance Imaging (MRI)
Neuroimaging
Quantitative Imaging

Background:

T1-weighted images and T1 quantification aid in differentiating brain tissues.
Acquiring multiple images for this purpose is time-consuming.

Purpose of the Study:

To develop a rapid and robust brain imaging sequence.
To simultaneously acquire quantitative T1 maps and multiple T1-weighted images.

Main Methods:

A novel 3D Cartesian multi-parameter normalized acquisition fast gradient echo (MPnRAGE) sequence was developed.
Interleaved variable density Poisson sampling and varying flip angles were used for B1-corrected T1 quantification.
Phantom studies and in vivo scans in five participants were performed.

Main Results:

The Cartesian MPnRAGE sequence acquired 10 high-quality T1-weighted images with varied contrasts in under 5 minutes.
Accurate T1 values were obtained compared to gold standard T1 fitting, with low test-retest variation.
In vivo scans demonstrated the feasibility of the acquisition method.

Conclusions:

The Cartesian MPnRAGE sequence provides accurate and efficient whole-brain quantitative T1 mapping and multiple image contrasts.
This sequence offers a time-saving alternative to existing brain imaging approaches.