RESUME^N: A flexible class of multi-parameter qMRI protocols

Area of Science:

• Medical Imaging
• Neuroimaging
• Biophysics

Background:

• Quantitative MRI (qMRI) is crucial for characterizing brain tissue microstructure.
• Existing qMRI techniques can be time-consuming, limiting whole-brain coverage and resolution.

Purpose of the Study:

• Introduce RESUME^N, a novel class of fast 3D qMRI schemes.
• Enable thorough characterization of brain tissue microstructural properties.

Main Methods:

• Combined multi-echo GRE acquisition with optimized low flip-angle GRE sequences.
• Analytically derived longitudinal relaxation (R1) and free induction decay (R2*) rates, proton density (PD), and quantitative susceptibility mapping (QSM).
• Incorporated comprehensive modeling of excitation, B1- profiles, and RF-spoiling.

Main Results:

• RESUME^N maps demonstrated homogeneity across the field-of-view.
• Achieved comparable quantitative values and high signal-to-noise ratio (SNR) across N=1-4.
• Enabled whole-brain acquisition with 700 μm isotropic resolution in under 15 minutes.

Conclusions:

• RESUME^N schemes offer a robust and flexible approach for fast qMRI studies.
• Facilitates detailed microstructural analysis of brain tissues.
• Suitable for clinical and research applications requiring efficient, high-resolution imaging.