Keywords: Quantitative Imaging, Multi-Contrast, Artificial Intelligence; Quantitative Mapping; Ultra-fast Acquisition
Motivation: To enhance MRI efficiency for brain imaging, improve image quality, and enable multi-parametric mapping for diagnosing neurological diseases.
Goal(s): Develop a rapid imaging protocol using AI-accelerated multi-shot echo-planar imaging (msEPI) to simultaneously acquire multi-contrast images and quantitatively map R2, R2', R2*,R1, M0, and MTR across the entire brain.
Approach: Utilize msEPI with AI-enhanced reconstruction, scan five healthy volunteers, adjust parameters for different contrasts, and conduct whole-brain quantification using MATLAB.
Results: The acquisition technique collects FLAIR and FGATIR-like multi-contrast images with high SNR and enable multi-parameter quantification in just 5 minutes. This approach holds the potential to streamline diagnostics and enhance the patient’s experience.
Impact: Our multi-contrast fast quantification MRI protocol, founded on an AI-accelerated multi-shot echo-planar imaging sequence, substantially shortens scanning time while delivering high-quality multi-parametric brain images, offering a promising advancement in efficient and effective diagnostic processes for neurological diseases.
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